NACA 0015 and NACA 4415 aerofoil are most common four digits and broadly used aerodynamic shape. Both of the shapes are extensively used for various kind of applications including turbine blade, aircraft wing and so on. NACA 0015 is symmetrical and NACA 4415 is unsymmetrical in shape. Consequently, they have big one-of-a-kind in aerodynamic traits at the side of widespread differences of their utility and performance. Both of them undergo the same fluid principle while applied in any fluid medium giving dissimilar outcomes in aerodynamics behavior. On this work, experimental and numerical investigation of each NACA 0015 and NACA 4415 is done to decide their performance. For this purpose, aerofoil section is tested for a prevalence range attack of angle (AOA). The study addresses the performance of NACA 0015 and NACA 4415 and evaluates the dynamics of flow separation, lift, drag, pressure and velocity contour and so on. This additionally enables to layout new optimistic aerofoil, which is critical to enhance the efficiency and performance of an aircraft in terms of lift enhancement and drag reduction.

Process simulation represents an important tool for plant design and optimisation, either applied to well established or to newly developed processes. Suitable thermodynamic packages should be selected in order to properly describe the behaviour of reactors and unit operations and to precisely define phase equilibria. Moreover, a detailed and representative kinetic scheme should be available to predict correctly the dependence of the process on its main variables. This review points out some models and methods for kinetic analysis specifically applied to the simulation of catalytic processes, as a basis for process design and optimisation. Attention is paid also to microkinetic modelling and to the methods based on first principles, to elucidate mechanisms and calculate thermodynamic and kinetic parameters. Different case histories support the discussion. At first, we have selected two basic examples from the industrial chemistry practice, e.g. ammonia and methanol synthesis, which may be described through a relatively simple reaction pathway. Then, a more complex reaction network is deeply discussed to define the conversion of bioethanol into syngas/hydrogen or into building blocks, such as ethylene.

Performing optimisation and scale-up studies of crystallisation systems requires accurate and computationally efficient mathematical models. The assumption of the ideal mixing conditions in batch reactors typically produce inaccurate results while the computational expense of CFD models is still prohibitively high. Therefore, in this work, a new intermediary approach is proposed that takes into account the non-ideal mixing conditions in the reactor and requires less computational resources than full CFD simulations. Starting with the Danckwerts concept of the intensity of segregation, an analogy between its application to chemical reactions and the kinetics of the crystallisation phenomena (such as nucleation and growth) has been made. As a result, the modified kinetics expressions have been derived which incorporate the effect of non-idealities present in stirred reactors. This way, based on the experimental measurements of the mixing time using the Laser Induced Fluorescence (LIF) technique, computationally more efficient mathematical models can be developed in two ways: (1) the accurate semi-empirical correlations are available for standard mixing configurations with the most often used types of impellers, (2) CFD simulations can be utilised for estimation of the mixing time; in this case it is necessary to simulate only the mixing process. The benefits offered by the LIF experimental technique have been demonstrated and some frequent problems in its application analysed. The mixing time results for configurations with and without baffles for three types of impellers and four different rotational speeds have been presented. The false shorter mixing times in the non-baffled configurations have been observed and this phenomena explained by the existence of two segregated zones in the reactor and confirmed by additional experiments. The precise measurements in these cases have been shown as difficult using the LIF technique, particularly for higher rpms. The experimental data has been compared to the preliminary simulation results obtained from the Smoothed Particle Hydrodynamics method and the standard k-ε turbulence model with the modest success. The shortcomings of the SPH model have been recognized and the directions for the future work discussed.

The open source CFD code OpenFOAM has emerged as one of the most popular alternative to commercial CFD solvers. The recent version of OpenFOAM supports overlapping grids, so called Overset mesh. In this type of mesh, one or more sub-collection of control volumes (or cells) are allowed to overlap with other set of cells. This allows for great flexibility in modelling Fluid Structure Interaction (FSI) problems. Fluid mesh can be standard structured mesh of a rectangular/cuboidal/or cylindrical domain. The structure mesh can be generated separately by creating multiple layers around a given body. The overset mesh functionality allows for overlapping or immersing this structured mesh inside the fluid mesh and a relevant FSI or moving dynamics problems can be solved. The idea of overset mesh has been around since eighties but its support in OpenFOAM is very recent. Most CFD codes which support overset mesh have either been in-house or commercial CFD codes. OpenFOAM's support for overset is the first major open source code resource available for CFD problems. The aim of this research is to solve a classical benchmark airfoil problem using OpenFOAM overset mesh and compare the numerical results with experimental result. We report here flow simulations results around NACA 0018. The result obtained from overset mesh compares convincingly well with experimental results. Computations have been carried out for Reynolds numbers in the range of 10⁵ with angle of attack ranging from α= 5 degree to α= 30 degree with an interval of 5 degree. Turbulence is incorporated using k - ε turbulence model. This study helps developing confidence in using OpenFOAM overset support for more complicated flows and moving dynamics. This report is complemented with a brief description of finite volume discretization using overset mesh.

Network Simulators is typically used to study services and applications in complex scenarios due to the infeasibility of deploying real testbeds. Many problems can be solved by using network simulators such as NS-3. With this in mind, the aim of this article is to introduce new NS-3 users through detailed information. It is sometimes difficult to handle by new users the traditional manuals developed by NS-3 project official website. In this article, NS-3 for communication network and Eclipse Integrated Development Environment (IDE) for powerful programming language are integrated step-by-step, explaining the main features of these open source software packages and concluding with an example simulation. Our effort is to make it easy for a beginner to be part of the NS-3 research community and to maintain an open environment of knowledge.

This paper describes a case study for applying of hybrid-electric propulsion system for a general aviation aircraft. The work was performed by a joint team of CIRA and the Department of Industrial Engineering of the University of Naples “Federico II”. Electric and hybrid electric propulsion for aircraft has gained widespread and significant attention over the past decade. The driver for industry interest has principally been the need to reduce emissions of combustion engine exhaust products and noise, but increasingly studies revealed potential for overall improvement in energy efficiency and mission flexibility of new aircraft types. The project goal was to demonstrate feasibility of aeronautic parallel hybrid-electric propulsion for a Light aircraft varying the mission profiles and the electric configuration. Through a creation, and application, of a global model, with software AMESim^®, in which it can be represented everything about the components chosen by the industrial partners, some interesting considerations are carried out. In particular, it was confirmed that with the only integration of state of the art technologies, for some particular missions, the advantages of aircraft hybrid-electric propulsion, for light aircraft, are notable.

Star block-copolymers (SBCs) are macromolecules formed by a number of diblock copolymers anchored to a common central core, being the internal monomers solvophilic and the end monomers solvophobic. Recent studies have demonstrated that SBCs constitute a self-assembling building blocks with specific softness, functionalization, shape, and flexibility. Depending on different physical and chemical parameters the SBCs can behave as flexible patchy particles. In this paper, we study the rotational dynamics of isolated SBCs using a hybrid mesoscale simulation technique. We compare three different approaches to analyse the dynamics: the laboratory frame, the non-inertial Eckart's frame, and a geometrical approximation relating the conformation of the SBC to the velocity profile of the solvent. We find that the geometrical approach is adequate when dealing with very soft systems while in the opposite extreme, the dynamics is best explained using the laboratory frame. On the other hand, the Eckart frame is found to be very general and to reproduced well both extreme cases. We also compare the rotational frequency and the kinetic energy with the definitions of the angular momentum and inertia tensor different from recent publications.

Automotive aerodynamics comprises of the study of aerodynamics of road vehicles. Its main goals are reducing drag, minimizing noise emission, improving fuel economy, preventing undesired lift forces and minimizing other causes of aerodynamic instability at high speeds. The Ahmed body has the form of a highly simplified car, consisting of a blunt nose with rounded edges fixed onto a box-like middle section and a rear end that has an upper slanted surface, the angle of which can be varied. It retains vital features of real vehicles in order to study the flow fields around it and the related turbulence models which characterizes the actual flow at elevated Reynolds number. In the present study, the aerodynamic behavior of this body is investigated numerically by the aid of commercial CFD tool: Ansys Fluent. The results of the simulation are validated with available experimental data and results of the simulations from other literatures. The numerical data were obtained for a fixed free stream velocity of 25 m/s at the inlet. The simulations were performed at a fixed slant angle of 25 degree and zero yaw angle. The present study focuses on how local refinement of mesh inside the concerned body and the outside, helps affect the results and for which grid dependency test is the primary objective of this paper. The present study also helps demonstrate how the drag of the body behaves, which is mainly the effect of pressure drag force generated at the rear portion of the body. The study also focuses on important properties like the velocity magnitude at different locations for different meshing cases, and to capture the flow pattern in the front or near the wake region. The study can be further helpful to future researchers in determining resistance, fuel efficiency etc. helping designers to optimize in specialized areas for better efficiency.

Industries, which are mainly responsible for high energy consumptions, need to invest in research projects in order to develop new managing systems for rational energy use and to tackle the devastating effects of climate change caused by human behavior. The study reported in this paper concerns the forging industry, where the production processes generally start with the heating of the steel in furnaces and continue with other processes, such as heat treatments and mechanical machining. One of the most critical operations, in terms of energy loss, is the opening of the furnace doors for the insertion and extraction operations. During this time, the temperature of the furnaces decreases by hundreds of degrees in a few minutes. Because the dispersed heat needs to be supplied again through the combustion of fuel, increasing the consumption of energy and the pollutant emissions, the evaluation of the amount of the lost energy is crucial for the development of operating or mechanical systems able to contain this dispersion. To perform this study, CFD simulation software was used. Results show that at the door opening, because of temperature and pressure differences between the furnace and the ambient, turbulences are generated. Results also show that the amount of energy lost for an opening of 10 minutes for radiation, convection and conduction is equal to 5606 MJ where convection is the main contributor with 5020 MJ. The model created, after being validated, has been applied to perform other simulations in order to improve the energy performance of the furnace. Results show that a reduction of the opening time of the door allows energy savings and limits pollutant emissions.

We review and assess the classic SIR and SEIR epidemiological models regarding possible applications to the COVID-19 pandemic. In spite of numerous more complicated models, we show how the qualitative features of the solution to the SIR and SEIR models continue to provide valuable public health insights in some scenarios. Using estimated COVID-19 data as of this date, the SEIR model shows that if it were possible to reduce R₀ from 2.5 to 1.25 through social distancing and other measures, the maximum fraction of the population that would become infected at any particular time would drop from 17% to 4%, provided that all of the model assumptions are satisfied. Finally, we compare the classic SIR model with a recent stochastic model with favorable results. Since this comparison underscores the importance of underlying connectivity assumptions, we conclude with Monte-Carlo simulations with specific connectivity that reproduce the classical SIR model with standard incidence.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

Network Simulators (NS) is typically used to study services and applications in complex scenarios due to the infeasibility of deploying real testbeds. This is the case of Mobile Ad hoc Networks (MANETs) which can be extensively used in emergency situations or to gather information without infraestructure. An important factor to get realiable results in the MANETs’ simulations is the wireless channel module of NSs. In this report, we explain how thw wireless channel is implemented in NS-3 and it can be configured.

Computational fluid dynamics (CFD) has, in the last decade, being an essential problem solving tool in industries such as pharmaceutical, pulp, petrochemical as well as Oil and Gas processing. The use of CFD for mixer design is unpopular in many countries in Africa. Therefore, this study investigates the characteristics of Brine-Surfactant mixing in a horizontal pipeline using CFD. The CFD is conducted by AnsysFluent software (licensed). A T-junction pipe is created and meshed with unstructured tetrahedral elements using design modeler. Discretization is done by Finite Volume Method (FVM), cell-centered scheme with Second-Order Upwind Scheme. The pressure term is introduced into the continuity equation by SIMPLE (Semi-Implicit Method for Pressure Linked Equations) algorithm. The kinetic epsilon model, also known as k-e model is administered to define the properties of the fluid and geometry, such as velocity, species mole fraction, pipe diameter. The boundary conditions is selected based on filed data. The rate of fluid flow in the primary region is 650 bbl/day at 400psi in 4in diameter pipeline, which is 100m long. The numerical simulation was based upon the governing equations such s continuity, Navier’s stoke, energy as well as specie transport equations. The findings shows that higher concentration results in increased mixing time, while 2% conc. of surfactant reaches homogeneity in 20 minutes at 72 meters of the pipe length. The result validated with field detail and the empirical result from literature, and is consistent. This study provide insight on industrial mixer design, chemical injection system, as well as gas pipeline design and optimization, especially in multiphase scale transport.

In our previous works we have proposed design equations that can predict with reasonable accuracy the transition point from homogeneous to heterogeneous regime as well as the gas holdup and the mean Sauter diameter at the homogeneous regime. The validity of the proposed correlations was checked with data obtained using different geometrical configurations and several Newtonian and non-Newtonian liquids as well as the addition of surfactants. However, in all the experiments the gas phase was atmospheric air. This work investigates the effect of gas phase properties by conducting experiments employing various gases (i.e., air, CO₂, He) that cover a wide range of physical property values. Experiments revealed that only the use of low-density gas (He) has a measurable effect on bubble column performance. More precisely, when the low-density gas (He) is employed, the transition point shifts to higher gas flow rates and the gas holdup decreases, a fact attributed to the lower momentum force exerted by the gas. In view of the new data, the proposed correlations have been slightly modified to include the effect of gas phase properties and it is found that they can predict the aforementioned quantities with an accuracy of ±15%. It has been also proved that CFD simulations are an accurate means for assessing the flow characteristics inside a bubble column.

A common reactor type in the chemical and process industry is the fixed-bed reactor. Accurate modeling can be achieved with particle-resolved Computational Fluid Dynamic (CFD) simulations. However, the underlying bed morphology plays a paramount role. Synthetic bed-generation methods are much more flexible and faster than image-based approaches. In this study, we look critically at the two different bed generation methods: Discrete Element Method (DEM) (in the commercial software STAR-CCM+) and the rigid-body model (in the open-source software Blender). The two approaches are compared in terms of synthetically generated beds with experimental data of overall and radial porosity, particle orientation, as well as radial velocities. Both models show accurate agreement for the porosity. However, only Blender shows similar particle orientation than the experimental results. The main drawback of the DEM is the long calculation time and the shape approximation with composite particles.

In this work, we'll present the power spectra density, auto-correlation function, dentrended fluctuation analysis and multifractal spectrum are performed to the daily light curves of Blazars monitored by Fermi LAT. Some signs of power law are found.

In this paper we report a new development on the numerical model for aluminum-steam combustion. This model is based on diffusion flame of continuum regime and the thermal equilibrium between the particle and the flow field, which can be used to calculate the aluminum particle combustion model for two phase calculation conditions. The model prediction is in good agreement with the experimental data. A new type of vortex combustor was proposed for the combustion of aluminum and steam, and the mathematical model of the two phase reacting flow with in this combustor was established. The turbulence effects are modeled using the Reynolds Stress Model (RSM) with Linear Pressure-Strain approach, and the Eddy-Dissipation model is used to simulate the gas phase combustion. Aluminum particles are injected into the vortex combustor and form a swirling flow around the chamber and their trajectories are traced using the Discrete Phase Model (DPM). The simulation results show that the vortex combustor can achieve high efficient combustion of aluminum and steam. The influencing factors, such as the eccentric distance of the inlet of aluminum particles, particle size and steam inlet diameter, etc., are studied. The work described in this paper represents an attempt to the design of a vortex combustor in order to increase aluminum combustion efficiency.

Utilization of wasted heat instead of fuel combustion is effective to reduce primary energy consumption for mitigating global warming problem. Because wasted heat sources are not necessarily located close to areas of heat demand, one of the difficulties is that wasted heat has to be transferred from heat source side to heat demand side, which may require heat transportation over long distance. From this point we proposed and have examined new idea of heat transportation using ammonia-water as the working fluid which system is named Solution Transportation Absorption chiller, in short STA. Our previous studies of STA were mainly the experimental investigation with STA facility which cooling power was 25RT (90kW). As a result, the COP of STA was found almost same value 0.65 with the conventional absorption chiller without depending on the transportation distances. The simulation using AspenHYSYS also examined with same experimental condition. The experimental data showed good agreement with the simulation calculation. In this study, we examined the large-scale cooling power STA on simulation. The examination cooling powers were from 90 kW(25RT) to 3517 kW(1000RT). All cooling power achieved around COP 0.64 including pump power consumptions. In addition, we performed the dynamic simulation. As the results, there was no effect of pipeline size on the cooling capacities and mass flow rates. Furthermore, the stability time of the cooling capacities and mass flow rates were almost same regardless of the pipeline size and cooling capacity. In other words, STA may be achieved the same COP even though having various complex conditions compared with the conventional absorption chiller.

Caveolin-1 (Cav-1) is 22 kDa caveolae protein, acts as a scaffold within caveolar membranes. It interacts with alpha subunits of G-protein and thereby regulates their activity. Earlier studies reported elevated or up-regulated levels of caveolin-1 in the serum of prostate cancer patients. Secreted Cav-1 promotes angiogenesis, cell proliferation and anti-apoptotic activities in prostate cancer patients. Cav-1 upregulation is mainly related to prostate cancer metastasis. Keeping above facts in view, the present study was designed to explore Cav-1 as a target for prostate cancer therapy using computational approach. Molecular docking, structural base molecular modelling and molecular dynamics simulations were performed to investigate Cav-1 inhibitors. A predictive model was generated and validated to establish a stable structure. ZINC database of biogenic compounds was used for induced fit docking (IFD) and high throughput virtual screening. The H-bond interactions of the compounds with active site residues of Cav-1 were estimated by IFD and 100 ns long molecular dynamic simulations. The reported compounds showed significant binding and thus can be considered as potent therapeutic inhibitors of Cav-1. This study provides a valuable insight into biochemical interactions of Cav-1 for therapeutic applications and warrants for experimental validation of the predicted ‘active(s)’.

In this study, a basic study was performed to analyze the seasonal temperature status of a research room in the Global Environment Research Building where ceiling-embedded indoor units are installed to study the room temperature status of the building as well as to improve its thermal environment. In addition, a direction for improvement of the indoor thermal environment in the winter was proposed through a CFD (computational fluid dynamics) simulation and was proven by an additional experiment. Through the results of this study, it appeared that if the ceiling-embedded indoor unit was installed in the small indoor space without considering the thermal vulnerability of its perimeter boundary, the air temperature of the upper part was greatly different from that of the bottom part in the winter. Hence, in this study, as a means to improve it, convectors were installed to minimize the effect of the external thermal environment and angle-controllable air flowing fans were installed to mitigate the stratification distribution. With such result, it was intended to present the essential data for improvement of the thermal environment as well as conservation of heating energy in the winter for buildings by reviewing the use of the ceiling-embedded indoor unit in the future.

Based on K-ε Standard Wall turbulence model (2-Equation) and Navier-Stokes (N-S) equations defined for incompressible fluids, fluid flow behaviour around hyperloop pods in an evacuated tube was simulated using ANSYS fluent solver assuming steady state and two dimensional conditions. In this research, to develop the case studies, using combination of different head and tail shape profile, four kind of hyperloop pods were developed with the aid of SolidWorks. These four pods have been investigated for their aerodynamic behaviour as four different case scenarios. The results of simulation depicts that an atmospheric pressure of 100 Pa with blockage ratio of 0.36 in tube provides the best possible aerodynamic behaviour for the designed hyperloop pod models. This research finds that overall aerodynamic behaviour of hyperloop pods can be varied by changing the head and tail shape profile of pods and a particular combination of head and tail shape profile can provide optimally best aerodynamic capabilities. Thus, this research paper provides a novel method of obtaining best aerodynamic capabilities in hyperloop pods by designing head profile optimally in combination with tail profile. This outcome will provide major contribution towards the development of hyperloop pods in future with better aerodynamic behaviour resulting in lesser electrical energy required to propel the hyperloop pods in evacuated tube.

The global energy crisis has lead researchers explore other sources of energy like wind, resulting in a wide acceptance of wind turbines. Vertical axis wind turbines (VAWT) more suitable for small scale application in urban conditions than their horizontal-axis counterparts. A Helical bladed VAWT would reduce the ripple effect when compared to Straight bladed VAWT. The effect of the blade helix angle on the aerodynamic performance of VAWT using 3D numerical simulations is studied. Turbulence modelled using 4-Equation transition SST k-w model. Three different helix angles of 60, 90 and 120 of a 3 bladed VAWT operating across different tip speed ratios were studied. The 60 helical bladed VAWT was found to perform better than all other helical bladed and straight bladed VAWT. Standard deviation of the moment coefficient generated by a blade plotted against 360 of azimuth rotation revealed that the ripple effect on the shaft produced by cyclic loading of the straight blade is considerably reduced upon introduction of helix angle, with 120 helical blade giving lowest standard deviation. The analysis has been done for the percentage of power generated by each quartile of flow and the contribution of each section of the blade. A comparative study was also conducted between different helical bladed VAWT and straight bladed VAWT. Flow feature analysis also revealed the reasons behind secondary peaks and the performance improvement when tip speed ratio increases. Wake structure analysis and flow contours were also studied for a better understanding of the flow field.

Collision avoidance is an important feature in advanced driver-assistance systems, aiming at providing correct, timely and reliable warnings before an imminent collision (objects, vehicles, pedestrians, etc.). A co-simulation framework is proposed in this paper to address the design and evaluation of collision avoidances in a cyber-physical system. The co-simulation framework is supported on the interaction between SCANeR and Matlab/Simulink. From the best of authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip LIDAR sensors in a cyber-physical system (CPS) considering traffic scenarios is presented. The CPS is designed and implemented in SCANeR. Secondly, an obstacle recognition library with three specific Artificial Intelligence-based methods is also designed based on sensory information database provided by SCANeR. Three methods for collision avoidance detection are considered, i.e.; a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods for detecting obstacles before different weather conditions is done with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and fog conditions, the support vector machine in rainy and self-organized map in snowy conditions.

Blazars show rapid and high amplitude variability. In this work , Fermi daily light curve of 130 sources are analyzed, distribution of daily variability are compared with each other by using Kolmogorov-Smirnov (K-S) test. results show: 1)Some pairs of the distributions are similar; 2) In most cases, the distributions are not Gaussian.

Recently, there has been a growing interest in the production of electricity from renewable energy sources (RES). The RES investment is characterized by uncertainty, which is long-term, costly, depend on feed-in-tariff and support schemes. In this paper, we address the real option valuation (ROV) of a solar power plant investment. The real option framework is investigated. This framework considers the renewable certificate price, furthermore the cost of delay between establishing and operating the solar power plant. The optimal time of launching the project and assess the value of deferred option are discussed. The new three stage numerical methods are constructed, the Lobatto3C-Milstein (L3CM) methods. The numerical methods are integrated with concept of Black-Scholes option pricing theory, and applied in option valuation for solar energy investment with uncertainty. The numerical results of L3CM, finite difference and Monte Carlo methods are compared to show the efficiency of our methods. Our data set refers to the Arab Republic of Egypt.

It is a common practice to detect outliers in a financial time series in order to avoid the adverse effect of additive outliers. This paper investigated the performance of GARCH family models (sGARCH; gjrGARCH; iGARCH; TGARCH and NGARCH) in the presence of different sizes of outliers (small, medium and large) for different time series lengths (250, 500, 750, 1000, 1250 and 1500) using root mean square error (RMSE) and mean absolute error (MAE) to adjudge the models. In a simulation iteration of 1000 times in R environment using rugarch package, results revealed that for small size of outliers, irrespective of the length of time series, iGARCH dominated, for medium size of outliers, it was sGARCH and gjrGARCH that dominated irrespective of time series length, while for large size of outliers, irrespective of time series length, gjrGARCH dominated. The study further leveled that in the presence of additive outliers on time series analysis, both RMSE and MAE increased as the time series length increased.

Titanium’s accelerating usage in global markets is attributable to its distinctive combination of physical and metallurgical properties. The key to best utilizing titanium is to exploit these characteristics, especially as they complement one another in a given application, rather than to just directly substitute titanium for another metal. Titanium alloy are extensively used in aerospace applications such as components in aero-engines and space shuttles, mainly due to their superior strength to weight ratio. For these demanding applications functionality and reliability of components are of great importance. To increase flight safety, higher sensitivity inspections are sought for rotating parts. Increased sensitivity can be applied at the billet stage, the forging stage, or both. Inspection of the forging geometry affords the opportunity to apply the highest sensitivity due to the shorter material paths when compared to those required for billet inspections. Forging inspection is typically performed for titanium (Ti) rotating parts with immersion inspection and fixed-focus, single-element transducers. Increased gain is required with depth because the ultrasonic beam attenuates with distance and diverges beyond the focus position that is placed near the surface. The higher gain that is applied with depth has the effect of increasing the UT noise with depth. The relationships between the UT noise, selection of the examination technique and the smallest detectable defect are presented in this material.

The expansion of renewable energies is progressing strongly. The influence on the power supply networks by the volatility of the infeed must be met with new concepts. In this paper we investigate the possibilities of integrating microgrids as a cooperating unit in the power supply network to support further expansion of RES power plants. In this paper a differentiation of microgrids from similar network structures is established, a classification of proposed groups is made. Then, after the description of simulation of components in a microgrid, with practical advice, an example model is shown, which aids the dimensioning of the components within a microgrid to achieve a specified goal.

Lactoperoxidase (LP), which is a high-value minor whey protein, has recently drawn extensive attention from research scientists and industry due to its multi-function and potential therapeutic applications. In this study, the separation and optimization of two similar-sized proteins, LP and lactoferrin (LF) were investigated using strong cation exchange column chromatography. Optimization was started with central composite design based experiments to characterize the importance of different decision variables. The three variables used in the optimization were flow rate, length of gradient and final salt concentration in the linear elution gradient step. The obtained empiric functional model represented the effect of the significant factors on the yield as the objective function. Afterwards, the calibrated mechanistic model was employed to predict accurate optimal set of variables. The optimal operating points were found and the results were compared with validation experiments. Predictions respecting yield confirmed a very good agreement with experimental results while keeping purity, a product quality characteristic, equal or above to a predefined value.

In the present paper, laminar forced convection nanofluid flows in a uniformly heated horizontal tube were revisited by direct numerical simulations. Single and two-phase models were employed with constant and temperature-dependent properties. Comparisons with experimental data showed that the mixture model performs better than the single-phase model in the all cases studied. Temperature-dependent fluid properties also resulted in a better prediction of the thermal field. A particular attention was paid to the grid arrangement. The two-phase model was used then confidently to investigate the influence of the nanoparticle size on the heat and fluid flow with a particular emphasis on the sedimentation process. Four nanoparticle diameters were considered: 10, 42, 100 and 200 nm for both copper-water and alumina/water nanofluids. For the largest diameter dnp = 200 nm, the Cu nanoparticles were more sedimented by around 80 %, while the Al₂O₃ nanoparticles sedimented only by 2.5 %. Besides, it was found that increasing the Reynolds number improved the heat transfer rate, while it decreased the friction factor allowing the nanoparticles to stay more dispersed in the base fluid. The effect of nanoparticle type on the heat transfer coefficient was also investigated for six different water-based nanofluids. Results showed that the Cu-water nanofluid achieved the highest heat transfer coefficient, followed by C, Al₂O₃, CuO, TiO₂, and SiO₂, respectively. All results were presented and discussed for four different values of the concentration in nanoparticles, namely φ = 0, 0.6, 1 and 1.6%. Empirical correlations for the friction coefficient and the average Nusselt number were also provided summarizing all the presented results.

The second article in the series presents the application of the Smoothed Particle Hydrodynamics (SPH) method to modelling of batch crystallisation in stirred tanks. A methodology to integrate the population balance equations (PBE) in parallel and independently from the Navier-Stokes equations is demonstrated. The benefits of the proposed methodology in terms of computational requirements, accuracy and availability of the crystal size distribution are discussed. The specific formulation of the SPH equations where the resulting system of ordinary differential equations is solved using the weighted contributions rather than numerically by solving a linear system of equations allows for massive parallelisation and a very loose coupling of the population balance and the fluid dynamics. It has been demonstrated, that the population balance equations can be solved on a Shared Memory Architecture (SMA) system using the OpenMP interface while the fluid dynamics equations being computed independently on a General Purpose Graphics Processing Unit (GPGPU) using the NVidia CUDA technology. This way, a significant portion of the computational overhead due to the large number of additional transport equations resulting from the discretisation of the population balance was removed: the SPH simulation coupled with 200 population balance equations was only 40% slower compared to SPH-only simulation. Two methods for the solution of population balance equations that preserve full crystal size distribution were implemented: discretised population balance (DPB) and method of characteristics (MOCH). The DPB equations are solved using the high-resolution finite-volume method with flux limiter and the effect of a large number of different flux limiters have been investigated. Both methods were validated using the case studies from the literature where an analytical solution can be derived. The developed models were applied to a numerical solution of coupled computational fluid dynamics and population balance equations to model a batch crystallization process. The effect of the hydrodynamics on the local temperature/supersaturation and the resulting crystal size distribution was captured and compared to the ideal mixing case. The simulation results from the DPB and MOCH methods were compared in terms of computational requirements and accuracy and MOCH selected as computationally more efficient and accurate.

Unmanned Aerial Vehicles (UAVs) have gained significant attention in recent times due to their suitability to a wide variety of civil, military and societal missions. Development of an unmanned amphibious vehicle integrating the features of a multi-rotor UAV and a hovercraft is focus of the present study. Components and subsystems of the amphibious vehicle are developed with due consideration on aerodynamic, structural and environmental aspects. Finite element analysis (FEA) on static thrust conditions and skirt pressure are performed to evaluate the strength of structure. For diverse wind conditions and angles of attack (AOA), computational fluid dynamic (CFD) analysis is carried out to assess the effect of drag and suitable design modification is suggested. A prototype is built with a 7 kg payload capacity and successfully tested for stable operations in flight and water-borne modes. Internet of Things (IoT) based water quality measurement is performed in a typical lake and water quality is measured using pH, dissolved oxygen (DO), turbidity and electrical conductivity (EC) sensors. The developed vehicle is expected to meet functional requirements of disaster missions catering to the water quality monitoring of large water bodies.

This paper deals with the problem of real-time management of Smart Grids. For this sake, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. The proposed technique is tested with the help of an academic microgrid, so the results may be replicated.

Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consist of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to LNG terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly.

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data–driven grey–box identification approach provided the physically meaningful nonlinear continuous–time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte–Carlo analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model–based and data–driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.

An empirical model is presented for estimating discharge on the Ubombo Sugar Limited (USL) main gravity canal to enhance bulk water management and water use efficiency. It uses stage readings obtained from measuring flumes A, B, C, and UPS to simulate discharge. The rationale for the development of the mathematical flow simulation model is the significance of the UPS flume as it measures readings that influence the daily operations of the farm, and the experiences with the ultrasonic flow meter installed in the flume. The model also provides a first for the simulation of accurate flow rates for flumes A, B, and C. A spreadsheet program that enables express prediction of canal flow rates was developed to influence timely implementation of these water management decisions. Calibrations demonstrated that the model is capable of predicting discharge at high accuracy (p>95%), and can be reliably used as a decision support tool for bulk water management. It can also be expanded to include other water measuring structures along Canal 1 and Canal 2, as well as the development of a stand-alone water management application for desktop and mobile computers.

The total enthalpies of the 16 different spin configurations that can be realized in the unit cell of the archetype spin crossover complex [Fe(phen)₂(NCS)₂] (phen=1,2-phenanthroline) were calculated applying periodic density functional theory combined with the Hubbard model and the Grimme-D2 dispersion correction (DFT+U/D2). The obtained enthalpy differences between the individual spin configurations were used to determine spin couplings of an Ising-like model and subsequent Monte Carlo simulations for this model allowed to estimate the phenomenological interaction parameter Г of the Slichter-Drickamer model, which is commonly used to describe the cooperativity of the spin transition. The calculational procedure described here, which led to an estimate of about 3 kJ/mol⁻¹ for Г, in good agreement with experiment, may be used to predict from first principles how modifications of spin crossover complexes can change the character of the spin transition from gradual to abrupt and vice versa.

Project logistics is one of the specific logistics operations. Compared to other logistics operations, it needs more efficient planning and engineering applications in each operational process. On the other hand, each project logistics operation can be defined as tailor-made operations, since it has no similarity with other operations. Consequently, each project logistics operation should be planned and carried out according to its own conditions and parameters. This study focuses on the simulation of project logistics operations under the light of computerized applications from start to finish of the logistics operation. In this study, transportation operations of 600 tons of autoclave from the Petkim port to the Gördes building site were selected as a case study.

A numerical study of the flow over a NACA aerofoil is presented in this paper. The numerical simulations are achieved with the computer code CFX and the computational domain is created by the computer tool ANSYS ICEM CFD. The CFX code is based on the finite volume method to solve the equations of mass, momentum and energy. The purpose of this paper is to determine the pressure distribution, flow patterns and the forces acting on the airfoil. Effects of the attack angle and Reynolds number on the velocity and pressure distribution, on the lift and drag coefficients are also explored.

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China and has subsequently spread worldwide. In the absence of any antiviral or immunomodulatory therapies, the disease is spreading at an alarming rate. 5 to 10% of recovered patients in Wuhan test positive again; this suggest that for controlling COVID-19, vaccines may be better option than drugs. A clinical trial to evaluate an anti-COVID-19 vaccine has started recently. However, its efficacy and potency have to be evaluated and validated. As an alternative, we are presenting a first-of-its-kind, designed multi-peptide subunit based epitope vaccine against COVID-19. The vaccine construct comprise an adjuvant, CTL, HTL, and B-cell epitopes joined by linkers. The vaccine is non-toxic, non-allergenic, thermostable and immunogenic with the capability to elicit a humoral and cell-mediated immune response. The findings are validated with high-end computation-based methods. This unique vaccine is made up of 33 highly antigenic epitopes from three proteins that have a prominent role in host receptor recognition, viral entry, and pathogenicity. We advocate this vaccine must be synthesized and tested urgently as public health priority.

Considering the need to reduce greenhouse gas emissions, onshore wind energy is certain to play a major role in future energy systems. This topic has received significant attention from the research community, producing many estimations of Europe's onshore wind potential for capacity and generation. Despite this focus, previous estimates have relied on distribution assumptions and simulation schemes that summarily under predict both the amount of available future wind capacity as well as its performance. Foremost in this regard is the common use of contemporary, or at least near-future, turbine designs which are not fitting for a far-future context. To fulfill this role, an improved, transparent, and fully reproducible work flow is presented for determining European onshore wind potential. Within a scenario of turbine cost and design in 2050, 13.5 TWof capacity is found to be available, allowing for 34.4 PWh of generation. By sorting the explicitly-placed potential generation locations by their expected generation cost, national relations between turbine cost and performance versus a desired capacity are exposed. In this way, it is shown that all countries possess some potential for onshore wind energy generation below 4 €_ct kWh^-1. and, furthermore, that it is unlikely for these costs to exceed 6 €_ct kWh^-1.

There are numerous approaches to model an influence of manufacturing parameters on the dissolution and disintegration of solid dosage forms. A modern approach for modelling and simulating complex and heterogeneous systems such as pharmaceutical tablets focuses on computationally-intensive finite-element or discreet element methods. Industrial challenges such as Process Analytical Technology (PAT) and Quality by Design are stimulating computer-based technologies to design, control and improve the quality of pharmaceutical compacts and their performance. In this study the disintegration and dissolution model based on the numerical solutions of the Noyes-Whitney equation and cellular automata supported disintegration model are proposed and evaluated. The results from in vitro release studies of the mefenamic acid formulations were compared to the calculated release patterns from the tablet structures obtained from microtomography experiments and the purely algorithmically created virtual tablets.

Recent advances in sensor and platform technologies such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data is produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation (M&S) of the natural environment. M&S devices, such as flight simulators, traditionally require a variety of different databases to provide a synthetic representation of the world. M&S often requires integration of data from a variety of sources stored in different formats. Thus, for simulation of a complex synthetic environment, such as a 3D terrain model, tackling interoperability among its components (geospatial data, natural and man-made objects, dynamic and static models) is a critical challenge. Conventional approaches used local proprietary data models and formats. These approaches often lacked interoperability and created silos of content within the simulation community. Therefore, open geospatial standards are increasingly perceived as a means to promote interoperability and reusability for 3D M&S. In this paper, the Open Geospatial Consortium (OGC) CDB Standard is introduced. “CDB” originally refers to Common DataBase which is currently considered as a name with no abbreviation in the OGC community. The OGC CDB is an international standard for structuring, modeling, and storing geospatial information required in high performance modeling and simulation applications. CDB defines the core conceptual models, use cases, requirements, and specifications for employing geospatial data in 3D M&S. The main features of the OGC CDB Standard are described as run-time performance, full plug-and-play interoperable geospatial data store, usefulness in 3D and dynamic simulation environment, ability to integrate proprietary and open-source data formats. Furthermore, compatibility with the OGC standards baseline reduces the complexity of discovering, transforming, and streaming geospatial data into the synthetic environment and makes them more widely acceptable to major geospatial data/software producers. This paper includes an overview of OGC CDB version 1.0 which defines a conceptual model and file structure for the storage, access, and modification of a multi-resolution 3D synthetic environment data store. Finally, this paper presents a perspective of future versions of the OGC CDB and what the steps are for humanizing the OGC CDB standard with the other OGC/ISO standards baseline.

Lassa virus (LASV) is responsible for a type of acute viral haemorrhagic fever referred to as Lassa fever. Lack of adequate treatment and preventive measures against LASV resulted in a high mortality rate in its endemic regions. In this study, a multi-epitope vaccine was designed using immunoinformatics as a prophylactic agent against the virus. Following a rigorous assessment, the vaccine was built using T-cell (N_CTL=8 and N_HTL=6) and B-cell (N_LBL=4) epitopes from each LASV-derived protein with suitable linkers and adjuvant. The physicochemistry, immunogenic potency and safeness of the designed vaccine (~68 kDa) were assessed. In addition, chosen CTL and HTL epitopes of our vaccine showed 97.37% worldwide population coverage. Besides, disulphide engineering also improved the stability of the chimeric vaccine. Molecular docking of our vaccine protein with toll-like receptor (TLR2) showed binding efficiency followed by dynamic simulation for stable interaction. Furthermore, higher levels of cell-mediated immunity and rapid antigen clearance were suggested by immune simulation and repeated-exposure simulation, respectively. Finally, the optimized codons were used in in silico cloning to ensure higher expression within E. coli K12 bacterium. With further assessment both in vitro and in vivo, we believe that our proposed peptide-vaccine would be potential immunogen against Lassa fever.

The use of unmanned aerial vehicle (UAV) during emergency response of a disaster has been widespread in recent years and the terrain images captured by the cameras on board these vehicles are significant sources of information for such disaster monitoring operations. Thus, analyzing such images are important for assessing the terrain of interest during such emergency response operations. Further, these UAVs are mainly used in disaster monitoring systems for the automated deployment of sensor nodes in real time. Therefore, deploying and localizing the wireless sensor nodes optimally, only in the regions of interest that are identified by segmenting the images captured by UAVs, hold paramount significance thereby effecting their performance. In this paper, the highly effective nature-inspired Plant Growth Simulation Algorithm (PGSA) has been applied for the segmentation of such terrestrial images and also for the localization of the deployed sensor nodes. The problem is formulated as a multi-dimensional optimization problem and PGSA has been used to solve it. Furthermore, the proposed method has been compared to other existing evolutionary methods and simulation results show that PGSA gives better performance with respect to both speed and accuracy unlike other techniques in literature.

The next future using machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy and reliability. Nowadays, distortion and vibration problems are easily solved for the most common cases by sing models based on equations describing the physical laws dominating the machining process; however additional efforts are needed to overcome the gap between scientific research and the real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep knowledge and models” that aid the machine designer, the production engineer, or machinists to get the best of their machines. This article proposes a systematic methodology to reduce problems in machining by means of a simulation utility, which recognizes, collects and uses the main variables of the system/process as input data, and generates objective results that help in the proper decision-making. Direct benefits by such an application are found in a) the fixture/clamping optimal design, b) the machine tool configuration, c) the definition of chatter free optimum cutting conditions and the right programming of cutting tool path at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies.

Arylamine N-acetyltransferases (NATs) are cytosolic enzymes, highly polymorphic, present in both eukaryotes and prokaryotes. These enzymes play an important role in the detoxification and activation of xenobiotics as well as in the synthesis of endogenous compounds. Specific NATs have been pointed out in the literature as possible therapeutic targets. In particular, the human NAT1, for the treatment of certain cancers, and the NAT from M. tuberculosis (TBNAT), for the treatment of tuberculosis. This paper describes an in silico approach to prospect and select potentially inhibitors of NAT1 and TBNAT from the Traditional Chinese Medicine (TCM) using free available tools. A library with ligands from TCM was previously screened in order to select only compounds with optimal pharmacological properties. The affinity of the selected ligands with respect to NAT enzymes was then evaluated by virtual screening (VS). Subsequently, the complexes with the best ligands were submitted to molecular dynamics (MD) simulations aiming to obtain better quality information on affinity and selectivity. The results for one specific ligand, ZINC14690579, indicated its potential for affinity and selectivity. ZINC14690579 structure may represent the discovery of a new scaffold for future development of NAT inhibitors.

X-ray fluorescence is largely employed in the measurement of the thickness of coatings. Despite of its diffusion, the task is not straightforward because of the complex physics involved that results in high dependence on matrix effects. Thickness quantification is in practice accomplished using the Fundamental Parameters approach, adjusted with empirical measurements of standards with known composition and thickness. This approach has two major drawbacks: i) there are no standards for any possible coating and coating architecture and ii) even relying on standards, the quantification of unknown samples requires the precise knowledge of the matrix nature (e.g., in case of multilayer coatings the thickness and the composition of each underlayer). In this work, we describe a semiquantitative approach to coatings thickness measurement based on the construction of calibration curves through simulated XRF spectra built with Monte Carlo simulations. Simulations have been performed with the freeware software XMI-MSIM. We have assessed the accuracy of the methods by comparing the results with those obtained by i) XRF thickness determination with standards and ii) FIB-SEM cross-sectioning. Then we evaluated which parameters are critical in this kind of indirect thickness measurements.

In this work, we examined the effect of tropospheric emissions on tropospheric ozone (O₃) by conducting three-dimensional (3D) chemistry transport model (CTM) simulations. For the control run, the CTM model simulates tropospheric O₃ levels with a complete set of anthropogenic, biomass burning, and vegetation emissions [8]. For the no-emission simulation, all anthropogenic, biomass burning, and vegetation emissions were turned off. Comparisons of results from these two simulations exhibit the emission impacts on the tropospheric O₃. In the no-emission simulation, distinctive low surface O₃ with concentrations less than 5 ppbv prevail over the Amazon basin, tropical South America, tropical South Africa, Southeast Asia. Transport of air from these land areas downwind contributes to the low O₃ over the remote marine boundary layer. In contrast, elevated O₃ levels over the extra-tropical remote marine boundary layer are less supported by the anthropogenic and biomass burning emissions but more sustained by the downward transport of O₃ from the stratosphere. These results demonstrate that the northern hemisphere continental areas (north of 30^◦N ), polar regions, and tropical continental regions are more sensitive to the tropospheric emissions. The northern hemisphere winter is mostly dominated by the stratospheric processes, while the tropospheric emissions dominate over the southern hemisphere tropical continental areas from tropics to 30^◦S latitudinal bands. The northern hemisphere continental regions are increasingly dominated by tropospheric emissions from spring, to reach maxima in summer, and started to reduce in autumn months.

The present studies deliver the computational investigations of a 10 MW turbine with a diameter of 205.8 m developed within the framework of the AVATAR (Advanced Aerodynamic Tools for Large Rotors) project. The simulations were carried out using two methods with different fidelity levels, namely the computational fluid dynamics (CFD) and blade element and momentum (BEM) approaches. For this purpose, a new BEM code namely B-GO was developed employing several correction terms and three different polar and spatial interpolation options. Several flow conditions were considered in the simulations, ranging from the design condition to the off-design condition where massive flow separation takes place, challenging the validity of the BEM approach. An excellent agreement is obtained between the BEM computations and the 3D CFD results for all blade regions, even when massive flow separation occurs on the blade inboard area. The results demonstrate that the selection of the polar data can influence the accuracy of the BEM results significantly, where the 3D polar datasets extracted from the CFD simulations are considered the best. The BEM prediction depends on the interpolation order and the blade segment discretization.

Background: COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global pandemic affecting approximately 490,000 people and accounting for more than 22,000 deaths and has no generally acceptable cure. Here, the recently resolved 3D structure of SARS-CoV-2 receptor binding domain (RBD) in complex with its receptor-the angiotensin converting enzyme-2 (ACE-2) have provided the basis for screening chemical database for novel entry inhibitors. Methods: Molecular docking protocols have been used to rapidly screen FDA database for high affinity interaction at the SARS-CoV-2-RBD/ACE-2 interface. One of the top candidates, ubrogepant has been selected and further studied using atomistic molecular dynamics simulation method. Results: Molecular docking result showed that ubrogepant (UBR) and darunavir have binding energies of -10.4 kcal/mol. MMPBSA free energy analyses of UBR bound to RBD, ACE-2 and RBD/ACE-2 revealed RBD/ACE-2 > ACE-2 > RBD preference. Network analysis showed that interaction captured in the crystal structure were disrupted in UBR-bound state, hydration of the interface and increased atomic fluctuation within the RBD oligomerization interface and ACE-2 zinc binding site. Conclusions: The ability of ubrogepant to rupture the interaction at the RBD/ACE-2 interface residues of SARS-CoV-2 RBD/ACE-2 complex may result in loss of protein function with direct implication on oligomerization formation in RBD and loss of function in ACE-2 thus, making binding, cellular receptor recognition impossible. General Significance: Ubrogepant represents a new therapeutic candidate in the fight against COVID-19, as it binds with relatively high affinity with free RBD, ACE-2 receptor and SARS-CoV-2 RBD/ACE-2 complex based on binding affinity calculations.

In this study, we repositioned thiopurine drugs used for the treatment of acute leukaemia as new tyrosinase inhibitors. Tyrosinase catalyses two distinct and successive oxidations in melanin biosynthesis: the conversions of tyrosine to dihydroxyphenylalanine (DOPA) and DOPA to dopaquinone. Continuous efforts are underway to discover small molecule inhibitors of tyrosinase for therapeutic, cosmetic, and agricultural purposes. Structure-based virtual screening has predicted inhibitor candidates for mushroom tyrosinase from drugs approved by the US Food and Drug Administration (FDA). Enzyme assays have confirmed the thiopurine leukaemia drug, thioguanine, as a tyrosinase inhibitor. Two other thiopurine drugs, mercaptopurine and azathioprine, were also evaluated for their tyrosinase inhibitory activity; mercaptopurine caused stronger inhibition than thioguanine did, whereas azathioprine was a poor inhibitor. The inhibitory constants of thioguanine and mercaptopurine were calculated as 52 and 16 µM, respectively, and the value of mercaptopurine was comparable to that of the well-known inhibitor kojic acid (13 µM). The cell lysate and melanin content assay in B16F10 melanoma cells confirmed that the compounds inhibited mammalian tyrosinase. In particular, 50 µM thioguanine reduced the melanin content by 57% without cytotoxicity. Furthermore, the thiopurine drugs shared little chemical similarity with the known tyrosinase inhibitors.

The heavy demand of water resources from the Zarqa River Basin (ZRB) has resulted in a base-flow reduction of the River from 5m³/s to less than 1m³/s. This paper aims at predicting Curve Numbers (CN) as a baseline scenario and proposing restoration scenarios for ZRB. The method includes classifying the soil type and land use, predicting CNs, and proposing CN restoration scenarios. Prediction of existing CNs will be in parallel with the runoff prediction using the US Army Corps of Engineers HEC-1 Model, and Rainfall-Runoff Model (RRM). The models have been set up at the land use distribution of 0.3% water body, 9.3% forest and orchard, 71% mixture of grass, weeds, and desert shrubs, 7.0% crops, 4.0% urban areas, and 8.4% bare soil. The results show that CN under dry condition are 59, 78 under a normal condition and 89 under a wet condition. During vegetation period, CN are 52, 72 and 86 for the dry, normal and wet condition respectively. The restoration scenarios; CN decreases runoff, and increases soil moisture when using the contours, terraces and crop residues. Analyzing results of CN scenarios will be a fundamental tool to support end-users related to their targets to achieve watershed restoration.

The application of the sensors optical fiber in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking the frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum is analyzed and sensor´s properties were defined. Following, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolutions. Both resolutions are conceivable because the FDPA algorithm elaborates two evaluations of Bragg wavelength shift

The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models based on equations describing the physical laws of the machining processes; however additional efforts are needed to overcome the gap between scientific research and the real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep-knowledge and models” that aid machine designers, production engineers or machinists to get the best of the machine-tools. This article proposes a methodology to reduce problems in machining by means of a simulation utility, which uses the main variables of the system&process as input data, and generates results that help in the proper decision-making and machining planification. Direct benefits can be found in a) the fixture/clamping optimal design, b) the machine tool configuration, c) the definition of chatter-free optimum cutting conditions and d) the right programming of cutting toolpaths at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies and are explained in the paper.

The Galleon was considered a masterpiece of shipbuilding in the sixteenth century, but from a modern point of view, the shape of her hull looks archaic and primitive. However, how accurate is this perception? Is the hull form of Galleon primitive? What were the reasons for its unique design features? This article investigates these questions by directly analysing the hull’s features from the point of view of modern ship’s theory, as well as from a historical perspective. A careful evaluation of specific design criteria of a typical Galleon, together with analysing a 3D model of its hull on modern software, with further insight for the seakeeping behaviour of Galleon with a comparison to more modern full-rigged ship (Barque of 19 CE), showed that these features were not random, but instead had a good rationale behind it, and served specific and carefully decided functions, required at the time.

Energy dissipation is one of the most important factors in choosing stepped spillways. However, few studies are about energy dissipation with different horizontal face angles. In this paper, the realizable k-ε turbulence model was used to study the flow field and energy dissipation rates of different stepped spillways with five horizontal face angles in the skimming flow regions. It shows that the free water surfaces and energy dissipation rates change with horizontal face angles and the energy dissipation rates initially decrease and then increase as the horizontal face angle increases. And the horizontal face angles cause the great changes of flow field.

Full-order state-space models represent the starting point for the development of advanced control methods for wind turbine systems (WTSs). Regarding existing control-oriented WTS models, two research gaps must be noted: (i) There exists no full-order WTS model in form of one overall ordinary differential equation that considers all dynamical effects which significantly influence the electrical power output; (ii) all existing reduced-order WTS models are subject to rather arbitrary simplifications and are not validated against a full-order model. Therefore, in this paper, two full-order nonlinear state-space models (of 11th and 9th-order in the (a, b, c)- and (d, q)-reference frame, resp.) for variable-speed variable-pitch permanent magnet synchronous generator WTSs are derived. The full-order models cover all relevant dynamical effects with significant impact on the system’s power output, including the switching behavior of the power electronic devices. Based on the full-order models, by a step-by-step model reduction procedure, two reduced-order WTS models are deduced: A non-switching (averaging) 7th-order WTS model and a non-switching 3rd-order WTS model. Comparative simulation results reveal that all models capture the dominant system dynamics properly. The full-order models allow for a detailed analysis covering the high frequency oscillations in the instantaneous power output due to the switching in the power converters. The reduced-order models provide a time-averaged instantaneous power output (which still correctly reflects the energy produced by the WTS) and come with a drastically reduced complexity making those models appropriate for large-scale power grid controller design.

In this paper, a two-phase model of air shock wave induced by rock-fall was described. The model was made up of the uniform motion phase (velocity was close to 0 m·s^-1) and the acceleration movement phase. The uniform motion phase was determined by experience, meanwhile the acceleration movement phase was derived by the theoretical analysis. A series of experiments were performed to verify the two-phase model and obtained the law of the uniform motion phase. The acceleration movement phase was taking a larger portion when height of rock-fall was higher with the observations. Experimental results of different falling heights showed good agreements with theoretical analysis values. Computational fluid dynamics (CFD) numerical simulation had been carried out to study the variation velocity with different falling height. As a result of this, the two-phase model could accurately and convenient estimating the velocity of air shock wave induced by rock-fall. The two-phase model could provide a reference and basis for estimating the air shock waves' velocity and designing the protective measures.

The application of thermoelectric generators (TEG) on the nozzle of an aviation jet engine was studied by finite element TEG-simulations. Against the background of system-level requirements of the reference aircraft this work reports the resulting requirements on the TEG design with respect to applied thermoelectric (TE) element lengths and fill factors (F) within the TE modules in order to maintain a positive effect on the specific fuel consumption. Assuming a virtual optimized TE material and varying the convective heat transfer coefficients at the nozzle surfaces this work reports the achievable power output. System-level requirement on the gravimetric power density (> 100 Wkg-1) can only be met for F ≤ 21%. Extrapolating TEG coverage to the full nozzle surface, the power output reaches 1.65 kW per engine. Assessment of further potential is demonstrated by a parametric study on the fill factor, convective heat transfer coefficients, and materials performance. This study confirms a feasible design range for TEG installation on the aircraft nozzle with a positive impact on the fuel consumption. This application translates into a reduction of operational costs, allowing for an economically efficient installation of TEG in consideration of the cost-specific power output of modern thermoelectric materials.

We present observations from evaluation of internal environmental quality of industrial halls with priority on daylighting in combination with the integral lighting. The physical parameters related to indoor lighting in large industrial halls in winter and summer periods were analyzed using in situ measurements and computational methods. These are part of a comprehensive research on indoor environmental quality of industrial halls with the aims of saving energy and providing a comfortable environment for the workers while improving the productivity. The results showed that the procedures used for evaluation of residential or office buildings may not be used for industrial buildings. We also observed that the criteria of occupants’ comforts for indoor industrial buildings may differ from those of other kinds of buildings. Based on these results, an adequate attention is required for designing the industrial buildings. For this reason, appropriate evaluation methods and criteria should be created. We found the measured values of daylight factor very close to the skylight component of the total illumination. The skylight component was observed on average 30% that of the measured daylight factor values. Although the daylight is not emphasized when designing the industrial buildings and its contribution is small, but it is very important for the workers psychology and physiology. The workers must feel a connection with the exterior environment; otherwise, their productivity decreases.

The increasing complexity of the design and operation evaluation process of multi-energy grids (MEGs) requires tools for the coupled simulation of power, gas and district heating grids. Most tools analyzed in this paper either do not allow coupling of infrastructures, simplify the grid model or are not publicly available. We introduce the open source piping grid simulation tool pandapipes that – in interaction with pandapower - fulfills three crucial criteria: clear data structure, adaptable MEG model setup and performance. In an introduction to pandapipes we illustrate how it fulfills these criteria through its internal structure and demonstrate how it performs in comparison to STANET®. Then we show two case studies that have been performed with pandapipes already. The first case study demonstrates a peak shaving strategy as interaction of a local electricity and district heating grid in a small settlement. The second case study analyzes the potential of a power-to-gas device to serve as flexibility in a power grid under consideration of gas grid constraints. They both show the importance of a clear database, a simple simulation setup and good performance to set up different large and complex studies on grid infrastructure design and operation.

The water cushion depth of stilling basin with shallow-water cushion is a key factor that affects the flow regime of hydraulic jump in the basin. However, the specific depth at which the water cushion is considered as “shallow” has not be stated clearly for now, and only conceptual description is provided. This paper attempts to specify the best water cushion depth based on the flow regime of hydraulic jump and underflow speed; namely, in case of critical hydraulic jump in the basin, the best water cushion depth is located where the minimum distance to the bottom plate of the stilling basin is 1/5~1/4 of the water cushion depth. The theoretical analysis indicates, at different inclinations of discharge chute (θ) and depth ratios of inlet (m), instead of monotonic change, the Froude number (Fr) at inlet of the stilling basin with shallow-water cushion firstly reduces and then increases as the flow velocity at discharge chute inlet (V) increases; the parameters of inflection point (critical flow velocity and critical Fr) increase as the inclinations of discharge chute (θ) and depth ratios of inlet (m) increase. Such regularity is the theoretical basis for selecting representative study cases. The reliability of the large eddy simulation calculation results are verified by a model test; in the paper, 30 cases including five different Froude numbers and six shallow-water cushion depths are selected, for calculating the hydraulic factors such as flow profile, flow regime and flow velocity in the stilling basin with shallow-water cushion; and the varying pattern between the best depth of stilling basin with shallow-water cushion (depth-to-length ratio) and the inflow Froude number is obtained which indicates that the best depth of stilling basin with shallow-water cushion varies little as the change of the Froude number before reaching the critical Froude number; however, the best depth-to-length ratio of stilling basin with shallow-water cushion increases as the Froude number increases after the critical Froude number is reached. The study results in this paper are of reference significance to design and calculation of the stilling basin with shallow-water cushion.

In this paper we introduce a computational model for the simulation of hypervelocity impact (HVI) phenomena which is based on the Discrete Element Method (DEM). Our paper constitutes the first application of DEM to the modeling and simulating of impact events for velocities beyond 5 kms⁻¹. We present here the results of a systematic numerical study on HVI of solids. For modeling the solids, we use discrete spherical particles that interact with each other via potentials. In our numerical investigations we are particularly interested in the dynamics of material fragmentation upon impact. We model a typical HVI experiment configuration where a sphere strikes a thin plate and investigate the properties of the resulting debris cloud. We provide a quantitative computational analysis of the resulting debris cloud caused by impact and a comprehensive parameter study by varying key parameters of our model. We compare our findings from the simulations with recent HVI experiments performed at our institute. Our findings are that the DEM method leads to very stable, energy–conserving simulations of HVI scenarios that map the experimental setup where a sphere strikes a thin plate at hypervelocity speed. Our chosen interaction model works particularly well in the velocity range where the local stresses caused by impact shock waves markedly exceed the ultimate material strength.

Computationally modelling a nuclear reactor startup core for a benchmark against the existing models is highly desirable for an independent assessment informing nuclear engineers and energy policymakers. This work presents a startup core model of the UK’s first Evolutionary Pressurised Water Reactor (EPR) based on Monte Carlo simulations of particle collisions using Serpent 2, a continuous-energy Monte Carlo reactor physics burnup code. Coupling between neutronics and thermal-hydraulic conditions with the fuel depletion is incorporated into the multi-dimensional branches, obtaining the thermal flux and fission rate (power) distributions radially and axially from the three dimensional (3D) single assembly level to a 3D full core. Shannon entropy is employed to characterise the convergence of the fission source distribution, with 3 billion neutron histories tracked by parallel computing. Source biasing is applied for the variance reduction. Benchmarking the proposed Monte Carlo 3D full-core model against the traditional deterministic transport computation suite used by the UK Office for Nuclear Regulation (ONR), a reasonably good agreement within statistics is demonstrated for the safety-related reactivity coefficients, which creates trust in the EPR safety report.

This paper highlights the problems associated with daylight use in industrial facilities. In a case study of a multi-story textile factory, we report how to evaluate daylight (as part of integral light) in the production halls marked F and G. This study follows the article in the Buildings journal, where Hall E was evaluated (unilateral daylight). These two additional halls have large areas that are 54 × 54 meters and are more than 5 meters high. The daylight is only on the side through the attached windows in envelope structures in the vertical position. In this paper, we want to present two case studies of these two production halls in a textile factory in the eastern part of Slovakia. These are halls that are illuminated by daylight from two sides through exterior peripheral walls that are against or next to each other. The results of the case studies can be applied in similar production halls illuminated by a ‘double-sided’ (bilateral) daylight system. This means that they are illuminated by natural illumination through windows on two sides in a vertical position. Such a situation is typical for multi-storied industrial buildings. The proposed approximate calculation method for the daylight factor can be used to predict the daylight in similar spaces in other similar buildings.

The purpose of this paper is to simulate a two-dimensional Rayleigh-Taylor instability problem using the classical method of Finite Element analysis of a multiphase model using ANSYS FLUENT 19.2. The governing equations consist of a system of coupled nonlinear partial differential equations for conservation of mass, momentum and phase transport equations. The study focuses on the transient state simulation of Rayleigh Taylor waves and subsequent turbulent mixing in the two phases incorporated in the model. The Rayleigh Taylor instability is an instability of an interface between two fluids of different densities which occurs when the lighter fluid is pushing the heavier fluid in a gravitational field. The problem was governed by the Navier-Stokes and Cahn-Hilliard equations in a primitive variable formulation. The Cahn- Hilliard equations were used to capture the interface between two fluids systems. The objective of this article is to perform grid dependency test on Rayleigh Taylor Instability for 2 different mesh size and compare the results for the variation in Atwood Number. The results were validated with the observations from previous published literatures.

GNSS have been widely used in navigation, positioning and timing. Nowadays, the multipath errors previously considered detrimental may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), e.g. GPS- Multipath Reflectometry (GPS-MR). In this paper, a new element describing bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model linking the GPS observables (SNR, phase and pseudorange) with detailed vegetation parameters, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that wheat will decrease the amplitudes of GPS multipath observables, if we increase the vegetation moisture contents or the scatters sizes (stem or leaf), the amplitudes of GPS multipath observables (SNR, phase and code) decrease. Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with published results for environmental parameter detections with GPS-MR.

The difficult current environmental situation, caused by construction industry residues containing ceramic materials could be improved by using these materials as recycled aggregates in mortars, with their processing causing a reduction in their use in landfill, contributing to recycling and also minimizing the consumption of virgin materials. Although some research is currently being carried out into recycled mortars, little is known about their stress-strain (σ-ε); therefore this work will provide the experimental results obtained from recycled mortars with recycled ceramic aggregates (with contents of 0, 10, 20, 30, 50 and 100%), such as: the density, the compression strength, as well as the σ-ε curves representative of their behavior. The values obtained from the analysis process of the results are those of: σ (elastic ranges and failure maximum), ε (elastic ranges and failure maximum), and Resilience and Toughness; in order to finally obtain, through numerical analysis, the equations to predict their behavior (related to their recycled content). At the end of the investigation it is established that mortars with recycled ceramic aggregate contents of up to 20% could be assimilated just like mortars with the usual aggregates, and the prediction equations produced could be used in cases of similar applications.

This paper proposes a novel model for a PV cell with parameters variance dependency on temperature and irradiance included. The model relies on commercial available data, calculates the cell parameters for standard conditions and then extrapolates them for the whole operating range. An up-to-date review of the PV modeling is also included with series and parallel parasitic resistance values and dependencies discussed. The parameters variance is analyzed and included in the proposed PV model, where the self-heating phenomenon is also considered. Each parameter variance is compared to the results from different authors. The model includes only standard components and can be run on any SPICE-based simulator. Unlike other approaches that consider the internal temperature as a parameter, our proposal relies on air temperature as an input and computes the actual internal temperature accordingly. Finally, the model is validated via experiments and comparisons to similar approaches are provided.

To enable purposeful design and implementation of automated concrete technologies, precise assessment and prediction of the complex material flow at various stages of the process chain are necessary. This paper investigates the intermediate stage of the extrusion and deposition processes in extrusion-based 3D-concrete-printing, using a numerical model based on the Particle Finite Element Method (PFEM). In PFEM, due to the Lagrangian description of motion, remeshing algorithms and the alpha shape method are used to track the free surface during large deformation scenarios. The Bingham constitutive model was used for describing the rheological behaviour of fresh concrete. This model is validated by comparing the numerically predicted layer geometries with those obtained from laboratory 3D printing experiments. Extensive parametric studies were then conducted using the numerical simulation, delineating the influence of process and material parameters on the layer geometries, the dynamic surface forces generated under the extrusion nozzle and the inter-layer interactions.

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densities and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on different set of true values. Some real data sets were employed to show the usefulness and flexibility of the model which serves as generalization to many sub-models in the field of engineering, medical, survival and reliability analysis.

There is a potential for synergy effects in utilizing CO2 for both enhanced gas recovery (EGR) and geothermal energy extraction (CO2-plume geothermal, CPG) from natural gas reservoirs. This “combined CO2-EGR–CPG system” has been introduced as a feasible approach that constitutes a CO2 Capture double-Utilization and Storage (CCUUS) system. In this study, we carry out reservoir simulations, using TOUGH2, to evaluate the sensitivity of the natural gas recovery, pressure buildup, and geothermal power generation performance of the combined system to various key reservoir and operational parameters. The reservoir parameters include horizontal permeability, permeability anisotropy, reservoir temperature, and pore-size-distribution index; while the operational parameters include wellbore diameter and ambient surface temperature. Using an example of a natural gas reservoir model, we also investigate the effects of different strategies of transitioning from the CO2-EGR stage to the CPG stage on the energy-recovery performance metrics and on the two-phase fluid-flow regime in the production well. The simulation results show that overlapping the CO2-EGR and CPG stages and having a relatively brief period of CO2 injection but no production (which we call the CO2-plume establishment stage) achieves the best overall energy (natural gas and geothermal) recovery performance. Permeability anisotropy and reservoir temperature are the parameters the natural gas recovery performance of the combined system is most sensitive to. The geothermal power generation performance is most sensitive to the reservoir temperature and the production wellbore diameter. The results of this study pave the way for future CPG-based geothermal power-generation optimization studies. For a CO2-EGR–CPG project, the results can be a guide regarding the required accuracy of the reservoir parameters during exploration and data acquisition.

Subsurface temperature is the key parameter in geothermal exploration. An accurate estimation of the reservoir temperature is of high importance and usually done either by interpolation of borehole temperature measurement data or numerical modeling. However, temperature measurements at depths which are of interest for deep geothermal applications (usually deeper than 2 km) are generally sparse. A pure interpolation of such sparse data always involves large uncertainties and usually neglects knowledge of the 3D reservoir geometry or the rock and reservoir properties governing the heat transport. Classical numerical modeling approaches at regional scale usually only include conductive heat transport and do not reflect thermal anomalies along faults created by convective transport. These thermal anomalies however are usually the target of geothermal exploitation. Kriging with trend does allow including secondary data to improve the interpolation of the primary one. Using this approach temperature measurements of depths larger than 1,000 m of the federal state of Hessen/Germany have been interpolated in 3D. A 3D numerical conductive temperature model was used as secondary information. This way the interpolation result reflects thermal anomalies detected by direct temperature measurements as well as the geological structure. This results in a considerable quality increase of the subsurface temperature estimation.

Aurora kinase A (AURKA) is a normal cell proliferation-inducing enzyme encoded by AURKA gene, with over-expression observed in different types of malignancies. Hence, the goal is to find potential inhibitors against AURKA. In this study, molecular docking, Standard Precision and Extra Precision methods were employed. After the docking study, the ligands showed an extremely low binding score which suggested very high binding affinity of the ligands. Furthermore, Quantum polarized ligand docking (QPLD) was performed to predict the binding status of the molecules. Based on the binding affinity, the top four compounds were chosen for further analysis. The docked complexes were further analyzed in explicit water conditions using 100 ns molecular dynamics simulations and binding free energy calculation. Then, density functional theory (DFT) calculation was used to calculate the molecular properties of the molecules. Finally, systems biology experiments validated the molecular docking and molecular dynamics simulation studies and indicated that quercetin, kaempferol, luteolin and rutin could inhibit the AURKA. The results show that, these four molecules have high binding affinity to the AURKA and significant interactions (LEU139, GLU211and ALA213) were also identified with the hinge region of Aurora kinase A. Thus, LEU139, GLU211, and ALA213 were identified as the crucial protein mechanisms.

The Late Heavy Bombardment Period (4.1 to 3.8 billion years ago) of heightened impact cratering activity on young Earth is likely the driving force for the origin of life. During the Eoarchean, asteroids such as carbonaceous chondrites delivered the building blocks of life and water to early Earth. Asteroid collisions created innumerable hydrothermal crater lakes in the Eoarchean crust which inadvertently became the perfect cradle for prebiotic chemistry. These hydrothermal crater lakes were filled with cosmic water and the building blocks of life. forming a thick prebiotic soup. The unique combination of exogenous delivery of extraterrestrial building blocks of life, and the endogenous biosynthesis in hydrothermal impact crater lakes very likely gave rise to life. A new symbiotic model for the origin of life within the hydrothermal crater lakes is here proposed. In this scenario, life arose around four billion years ago through five hierarchical stages of increasing molecular complexity: cosmic, geologic, chemical, information, and biological. During the prebiotic synthesis, membranes first appeared in the hydrothermal crater lakes, followed by the simultaneous origin of RNA and protein molecules, creating the RNA/protein world. These proteins were noncoded protein enzymes that facilitated chemical reactions. RNA molecules formed in the hydrothermal crater basin by polymerization of the nucleotides on the montmorillonite mineral substrate. Similarly, the initial synthesis of abiotic protein enzymes was mediated by the condensation of amino acids on pyrite surfaces. The regular wet-dry cycles within the crater lakes assisted further concentration, condensation, and polymerization of the RNAs and proteins. Lipid membranes randomly encapsulated amino acids, RNA, and protein molecules from the prebiotic soup to initiate a molecular symbiosis inside the protocells, this led to the hierarchical emergence of several cell components. As the role of protein enzymes became essential for catalytic process in the RNA/protein world, Darwinian selection from noncoded to coded protein synthesis led to translation systems and the genetic code, heralding the information stage. In this stage, the biochemical pathways suggest the successive emergence of translation machineries such as tRNAs, aaRS, mRNAs, and of ribosomes for protein synthesis. The molecular attraction between tRNA and amino acid led to the emergence of translation machinery and the genetic code. tRNA is an ancient molecule that created mRNA for the purpose of storing amino acid information like a digital strip. Each mRNA strand became the storage device for genetic information that encoded the amino acid sequences in triplet nucleotides. As information became available in the digital languages of the codon within mRNA, biosynthesis became less random and more organized and directional. The original translation machinery was simpler before the emergence of the ribosome than that of today. We review three main concepts on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and adaptive theory. We believe that these three theories are not mutually exclusive, but are compatible with our coevolution model of translations machines and the genetic code. We suggest biosynthetic pathways as the origin of the translation machine that provided the framework for the origin of the genetic code. During translation, the genetic code developed in three stages coincident with the refinement of the translation machinery: GNC code with four codons and four amino acids during interactions of pre-tRNA/pre-aaRS /pre-mRNA, SNS code consisting of 16 codons and 10 amino acids appeared during the tRNA/aaRS/mRNA interaction, and finally the universal genetic code evolved with the emergence of the tRNA/aaRS/mRNA/ribosome machine. The universal code consists of 64 codons and 20 amino acids, with a redundancy that minimizes errors in translation. To address the question of the origin of the biological information system in the RNA/protein world, we converted letter codons into numerical codons in the Universal Genetic Code Table. We developed a software called CATI (Codon-Amino Acid-Translator-Imitator) to translate randomly chosen numerical codons into corresponding amino acids and vice versa, gaining insight into how translation might have worked in the RNA/protein world. We simulated the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. We used AnyLogic software to simulate and visualize the evolution of the translation machines and the genetic code. We conclude that the emergence of the information age from the RNA/protein world was a watershed event in the origin of life about four billion years ago.

Greenwater (splashing of water on the deck) loading is a classical problem faced by the designer of ship-shaped vessels, which becomes even worst when the vessel operates at harsh weather conditions for an extended period. Installation of breakwaters on the deck can play a crucial role in minimizing this impact. However, research on the design and optimization of the breakwater is still at its infancy, and this study aims at shedding further light on this area by proposing and analyzing the effectiveness of three breakwater designs on a fixed box-shaped vessel. Commercial CFD software is used for this investigation. However, the design model (without breakwater) was validated at first against experimental results of green water splashing, before performing the actual simulations with proposed breakwater design. A vertical plate is used as the deck structure, and greenwater pressure at several locations on that plate is measured to compare the effectiveness of various breakwater designs. Overall, breakwaters with openings (perforations, grillages etc.) found to be more effective in minimizing the pressure generated by the greenwater. Nevertheless, there are significant rooms for improvement on breakwater designs, and some topics for further research are also suggested in this regard.

The aim of this work is to introduce new ways to model the I-V characteristic of a PV cell or PV module using straight lines and Bézier curves. This is a complete novel approach, Bézier curves being previously used mainly for computer graphics. The I-V characteristic is divided in three sections, modeled with lines and a quadratic Bézier curve in the first case and with three cubic Bézier curves in the second case. The result proves to be accurate and relies on the fundamental points usually present in the PV cell datasheets: Voc (the open circuit voltage), Isc (the short circuit current), Vmp (the maximum power corresponding voltage) and Imp (the maximum power corresponding current) and the parasitic resistances Rsh0 (shunt resistance at Isc) and Rs0 (series resistance at Voc). The proposed algorithm completely defines all the implied control points and the error is analyzed. The temperature and irradiance influence is also analyzed. The model is also compared using the least squares fitting method. The final validation shows how to use Bézier cubic curves to accurately represent the I-V curves of an extensive range of PV cells and arrays.

Efficiency improvement is the new challenge in all fields of design. In this scenario the reduction of power losses is becoming more and more a main concern also in the design of power transmissions. Appropriate models to predict power losses are therefore from the earliest stages of the design phase. The aim of the project is to carry on lubrication simulations of several variants of a cylindrical-roller-bearing to understand the lubricant distribution and the related churning power losses. Several strategies to reduce the computational effort have been used. Among them the sectorial symmetry and three innovative meshing strategies (purely analytical with and without interfaces and analytical/subtractive) that have been implemented in the OpenFOAM® environment. The results of the different approaches were compared among them and with experimental observations showing good agreement and reasonable savings in terms of computational effort.

Fiber-metal laminates (FMLs) such as Kevlar reinforced aluminum laminate (ARALL), Carbon reinforced aluminum laminate (CARALL), and Glass reinforced aluminum laminate (GLARE) offer great potential for weight reduction applications in automobile and aerospace construction. In order to investigate the feasibility for utilizing such materials in the form of laminates, sheet hydro-bulging tests are studied under the condition of uniform blank holder force for three-layered aluminum and aluminum-composite laminates using orthogonal carbon and Kevlar as well as glass fiber in the middle. The experimental results validate the finite element results and they exhibited that the forming limit of glass fiber in the middle is the highest among the studied materials, while carbon fiber material performs the worst. Furthermore, the crack modes are different for the three kinds of fiber materials investigated in the research. This study provides fundamental guidance for the selection of multi-layer sheet materials in the future manufacturing field.

Aerodynamic performance of a floating offshore wind turbine (FOWT) is significantly influenced by platform surging motions. Accurate prediction of the unsteady aerodynamic loads is imperative for determining the fatigue life, ultimate loads on key components such as FOWT rotor blades, gearbox and power converter. The current study examines the predictions of numerical codes by comparing with unsteady experimental results of a scaled floating wind turbine rotor. The influence of platform surge amplitude together with the tip speed ratio on the unsteady aerodynamic loading has been simulated through unsteady CFD. It is shown that the unsteady aerodynamic loads of FOWT are highly sensitive to the changes in frequency and amplitude of the platform motion. Also, the surging motion significantly influences the windmill operating state due to strong flow interaction between the rotating blades and generated blade-tip vortices. Almost in all frequencies and amplitudes, CFD, LR-BEM and LR-uBEM predictions of mean thrust shows a good correlation with experimental results.

In networked driving simulation, two or more human drivers participate interactively within a shared virtual environment. Thereby, typical applications of driving simulation can be extended to consider multi-driver scenarios, where a much closer approximation of reality with its unpredictability is achieved. However, the utilized network is typically prone to a considerable amount of message traffic. In addition to restricted system scalability, the resulting degradation of network performance leads to invalid simulation outcomes or unacceptable system behavior. High-level architecture (HLA) is an IEEE standard for networked simulation. Data distribution management (DDM) is one of the service groups provided by HLA standard. The aim of the DDM service is to reduce network traffic and to save effort required to process unnecessary received data. However, different approaches for current DDM implementations show major drawbacks in terms of utilization complexity, inefficiency, and yet added network overhead. This paper presents a concept of an interest manager that takes over the DDM functionality and avoids these drawbacks. Simulation data is exchanged between the participating driving simulators only when it is necessary according to the driving situations. The concept is validated by analyzing the network load of two driving maneuvers with and without the interest manager.

Based on the geologic conditions of natural gas hydrate (NGH) accumulations in the Shenhu area, northern slope of the South China Sea, this paper used a method of combining reservoir stimulation technique (RST) with depressurization to investigate the conversion efficiency of marine NGH reservoirs in different intrinsic permeability and initial NGH saturation conditions, and analyze the influence of variably-stimulation effect on marine NGH conversion efficiency in different accumulation conditions, provided a reference scheme for improving the NGH conversion efficiency in the Shenhu area. In this work, we performed calculations for the variations in CH4 production rate and cumulative volume of CH4 in different initial NGH saturation, intrinsic permeability and stimulation effect conditions, variance analysis and range analysis methods were used to analyze the significance of these key factors and their interaction, and investigated the sensitivity of stimulation effect on NGH conversion efficiency, respectively. The simulation results showed that stimulation effect have a significant influence on NGH conversion efficiency, and the influence of interaction between these three factors were not obvious. Possibly most important, we clarified an optimum stimulation effect for higher NGH conversion efficiency under different accumulation conditions, especially in low-permeability and high-saturation, which corresponding stimulation effect were different.

The matrix converter converts the input line voltage into a variable voltage with an unrestricted output frequency without using an intermediate circuit, dc link circuit. A pure sine in and pure sine out is the unique feature of the matrix converter. This research paper also analyzes the basic operating principle and the simulation modeling of the direct matrix converter, which is controlled by the Space Vector Pulse Width Modulation technique by using the software which is known as MATLAB/Simulink. The most desirable features in the power frequency changes can be fulfilled by using the matrix converters, and this is the reason for the tremendous interest in the topology. Since the power electronic circuits which is known as the motor drives are used to operate the AC motors at the frequencies other than that of the supply.

MCrAlX (M: Ni or Co or both, X: minor elements) coatings have been widely used to protect hot components in gas turbines against oxidation and hot corrosion at high temperatures. Understanding the influence of the X-elements on oxidation behaviour is important in the design of durable MCrAlX coatings. In this study, NiCoCrAlX coatings doped with Y+Ru and Ce, respectively, were deposited on Inconel-792 substrate by HVOF. The samples were subjected to isothermal oxidation test in laboratory air at 9000, 1000, 1100 ºC and cyclic oxidation test between 100 ºC and 1100 ºC with 1 hour dwell time at 1100 ºC. It was observed that the coating with Ce shows a much higher oxidation rate than the coating with Y+Ru under both isothermal and cyclic oxidation tests. Besides, β-depletion due to interdiffusion between coating and substrate was significantly lower with Ru addition. Simulations results using both a moving phase boundary model and an established oxidation-diffusion model show that Ru stabilize β grains which reduces β-depletion of coating due to substrate interdiffusion. This paper presents a comprehensive study of the influence of Ce and Ru on oxidation behaviour including investigation of the microstructure evolution influenced by oxidation time at coating surface and coating-substrate interface combining experiment and simulation results.

Bimetallic nanoparticles are of interest since they lead to many interesting electrical, chemical, catalytic, and optical properties. They are particularly important in the field of catalysis since they show superior catalytic properties than their monometallic counterparts. The structures of bimetallic nanoparticles depend mainly on the synthesis conditions and the miscibility of the two components. In this work, PdPt alloyed-bimetallic nanoparticles (NPs) were synthesized through the polyol method, and characterized using spherical aberration (Cs) corrected scanning transmission electron microscopy (STEM). High-angle annular dark-field (HAADF)-STEM images of bimetallic nanoparticles were obtained. The contrast of images shows that nanoparticles have an alloy structure with an average size of 8.2 nm. Together with the characterization of nanoparticles, a systematic molecular dynamics simulations study, focused on the structural stability and atomic surface segregation trends in 923-atom PdPt alloyed-bimetallic NPs was carried out.

Lack of due attention to the orientation of streets and establishment of urban blocks without regard for climatic characteristics and conditions of the environment have an adverse effect on thermal comfort in open urban spaces. Construction of new settlements without taking into account climatic requirements undermines thermal comfort for pedestrians and other users, especially in cold regions. Considering the coldness of the region under study and the significance of the orientation of streets in absorbing radiation and providing heat to outdoor urban spaces, this study investigates the effect of the orientation of streets on microclimatic comfort in one of the residential towns of Hamadan City in Iran. For this purpose, microclimate simulation was performed using ENVI-met software. A residential block with four different orientations (the most common orientations of its surrounding buildings) were simulated in the coldest day of winter and the hottest day of summer. The results suggest that streets have different thermal behavior in different orientations. Orientation affects mean radiant temperature (Tmrt), the duration of exposure to direct sunlight, wind speed, and physiological equivalent temperature (PET), which are all important factors in thermal comfort. Based on these findings, north-south streets in Hamedan receive more radiant temperature during winter compared to other simulated orientations and provide more desirable thermal comfort. The average PET value on a winter day at a point on the north-south passage was 4.5-8 °C warmer than other orientations. In summer, streets with intercardinal orientations (i.e., northeast-southwest and northwest-southeast) provided the lowest PET (about 2 °C cooler than other orientations) and better thermal comfort

This paper analyses the health and performance of 12-stage axial compressor of the TV3-117VM/VMA turboshaft operated in a desert environment. The results of the dimensional control of 4,800 worn blades are analysed to model the wear process. Operational experience and numerical simulations are used to assess the effectiveness of an Inlet Particle Separator. Numerical modal analysis is performed to generate the Campbell diagram of worn blades and identify resonant blade vibration which can lead to high cycle fatigue (HCF). It is shown that the gradual loss of the stall margin over time determines the serviceability limits of compressor blades. Recommendations setting out go / no-go criteria are made to maintenance and repair organisations.

Traditional winglets are designed as fixed devices attached at the tips of the wings. The primary purpose of the winglets is to reduce the lift-induced drag, therefore improving aircraft performance and fuel efficiency. However, because winglets are fixed surfaces, they cannot be used to control lift-induced drag reductions or to obtain the largest lift-induced drag reductions at different flight conditions (take-off, climb, cruise, loitering, descent, approach, landing, and so on). In this work, we propose the use of variable cant angle winglets which could potentially allow aircraft to get the best all-around performance (in terms of lift-induced drag reduction), at different flight phases. By using computational fluid dynamics, we study the influence of the winglet cant angle and sweep angle on the performance of a benchmark wing at Mach numbers of 0.3 and 0.8395. The results obtained demonstrate that by adjusting the cant angle, the aerodynamic performance can be improved at different flight conditions.

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 aim of this study is to provide the scientists with a straightforward correlation that can be applied for predicting the Fanning friction factor and consequently the pressure drop during blood flow in small caliber vessels. Due to the small diameter of the conduit, the Reynolds numbers are low and thus the flow is laminar. The study has been conducted using CFD simulations validated with relevant experimental data acquired using an appropriate experimental set-up. The experiments concern pressure drop measurement during the flow of a blood analogue that follows the Casson model, i.e. an aqueous glycerol solution that contains a small amount of xanthan gum and exhibits similar behavior to blood, in a smooth, stainless steel microtube (L=5.6cm and D=400 μm). The interpretation of the resulting numerical data led to the proposal of a simplified model that incorporates the effect of the flow rate, the hematocrit value (35-55%) and the vessel diameter (300-1800 μm) and predicts with better than ±10% the Fanning friction factor and consequently the pressure drop during laminar blood flow in small caliber vessels.

Previous research has shown that the effectiveness of selecting filter set from a large set of commercial broadband filters by vector analyzing method based on maximum linear independence (MLI). However, the traditional MLI is suboptimal due to predefining the first filter of the selected filter set being the maximum ℓ2 norm among all those of the filters. An exhaustive imaging simulation is conducted to investigate the features of the most competent filter set. In the simulation, every filter in a subset of all the filters is selected serving as the first filter in turn. From the results of the simulation, we found there are remarkable characteristics for the most competent filter set. Besides smaller condition number, the geometric features of the best-performed filter set comprise the distinct peak of the transmittance of the first filter, the generally uniform distributing of the peaks of the transmittance curve of the filters, the substantial overlapping of the transmittance curves with those of the adjacent filer sets. Therefore, the best-performed filter sets can be decided intuitively by simple vector analyzing and just a few experimental verifications. This work would be useful for optimizing spectral sensitivity of broadband multispectral imaging sensors or SFA sensors.

Coal-fired thermal plants (CTPP) are known to pollute the atmosphere with emission of many greenhouse gases and particulate matter. The power generation from these thermal plants cannot be stopped completely because it forms the backbone of the grid power supply. It is necessary to study the dispersion patterns of pollutants that affect the health of the people. The dispersion patterns are location specific since they depend on local meteorological conditions. In this study, the dispersion of particulate matter (PM) and sulphur dioxide (SO₂) from a CTPP with 275 m high stack are studied under different atmospheric boundary layer (ABL) of neutral, stable and unstable conditions up to a distance of 30 km from the stack. The plume of the PM spreads under all conditions. During some parts of the day, PM settles around the stack while at other times PM keeps suspending in the air for the full distance under study. Sulphur dioxide dilutes to concentrations below the detection limits in about 12-13 km from the stack for neutral and unstable ABL whereas for the stable ABL, the dispersion is up to 30 km. The 24 h weighted average concentration of sulphur dioxide, at 10 m height from the ground, is 14.2 mg/m³ at a distance of 25 kms from the CTPP, which is comparable with the value of 9.2 mg/m³ measured at the Air Quality Stations located around the same distance. Based on the results policy changes that need to be implemented are suggested.

Most of the structures in flowing water are a challenge to their stability and sustainable with different flow conditions. Recent, renewable energy research and development covers ocean and river energy platform in which flow of water drag considered in various conversion devices towards the offshore and onshore establishment. Various energy platforms have been suggested for offshore development. However, the stability of these platforms in water is a serious concern. To study the water interaction over circular and square cross-section cascade system under the water has been carried out. Water flow around the pillars or column of the energy platform are analyzed through simulation software. Very low velocity 0.5 m/s has been considered to analyze the system. Total fifteen numbers of cascade pillars having circular and square cross-section area were considered. K-ε turbulence model is adopted to calculate the flow interaction to the column. A velocity, pressure, and energy fields are found around the column.

Curcumin is one of the bioactive metabolites of turmeric (Curcuma longa), known for its pleiotropic pharmacological actions, including antioxidant and anti-inflammation, anticholinesterase, immunomodulation, and neuroprotection. Substantial evidence suggests the therapeutic benefits of curcumin against neurodegenerative disorders, including Alzheimer’s disease (AD), acting on a diverse array of brain targets that make the molecular mechanisms complicated. System biology level-investigation could potentially present a comprehensive molecular mechanism to delineate the neuropharmacological action of curcumin. In this study, we used integrated system pharmacology and molecular simulation analysis to gain insights into the underlying mechanism of curcumin action against AD. Network pharmacology study identified curcumin-targeted potential cellular pathways such as phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) signaling, neurotrophin signaling, toll-like receptor (TLR) signaling, and autophagy, and proteins such as tropomyosin receptor kinase B (TrkB), liver X-receptor-beta (LXR-β), estrogen receptor-β (ER-β), mammalian target of rapamycin (mTOR), TLR-2, N-methyl-D-acetate receptor subunit 2B (GluN2B), β-secretase and glycogen synthase kinase-3β (GSK-3β), which are intimately associated with neuronal growth and survival, immune response, and inflammation. Moreover, the molecular modeling further verified that curcumin showed a significant binding affinity to mTOR, TrkB, LXR-β, TLR-2, ER-β, GluN2B, β-secretase, and GSK-3β, which are the crucial regulators of molecular and cellular processes associated with AD. Together, the present system pharmacology and in silico findings demonstrate that curcumin might play a significant role in modulating AD-pathobiology, supporting its therapeutic application for the prevention and treatment of AD.

Deep eutectic solvents (DESs) are one of the most rapidly evolving types of solvents, appearing in a broad range of applications such as nanotechnology, electrochemistry, biomass transformation, pharmaceuticals, membrane technology, biocomposite development, modern 3D-printing, and many others. The range of their applicability continues to expand, which demands the development of new DESs with improved properties. To do so requires an understanding of the fundamental relationship between the structure and properties of DESs. Computer simulation and machine learning techniques provide a fruitful approach as they can provide predictions, reveal physical mechanisms and readily be linked to experiments. This review is devoted to the computational research of DESs and describes technical features of DES simulations and the corresponding perspectives on various DES applications. The aim is to demonstrate the current frontiers of computational research of DESs and discuss future perspectives.

The study aims to analyze the performance criteria of the GR4J model to reproduce high water flows in the Ouémé watershed at Bonou's outlet which has been vulnerable to climate change in recent decades. The methodology focused on the use of daily climatological and hydrometric data extracted from files of National Directorate of Meteorology, and General Directorate of Water; they were supplemented by those of SIEREM/HSM dataset over the period 1961-2015. The rainfall was regionalized using Thiessen method. The performance of the GR4J model was assessed with NSE, RMSE and KGE criteria. The results indicate that the study area is marked by rainfall variabilities and detection of two breakpoints (1968 and 1987) which divide the series into three sub-periods; these discontinuities have repercussions on the streamflow. It's found that GR4J model overestimates the streamflow during the low water period and underestimates them in high water. However, the efficiency and performance criteria NSE, RMSE and KGE calculated on high water flow rates are better in calibration than in validation. The KGE values are range between 83-85% in calibration and 56-68% during validation, which gives to GR4J model the efficiency and performance to reproduce high flow rates in the study area

In this paper, the computational fluid dynamics (CFD) method has been used to simulate the gas flow and the catalytic hydrogenation process of the C-2 hydrogenation adiabatic reactor in a practical ethylene production unit of a chemical plant. The laminar finite-rate model was used for the chemical reaction model. The standard two-equation model was used for the turbulence model. The exponent-function kinetic model was used for the reaction dynamics model. The simulation results were in good agreement with the actual industrial data obtained from the C-2 hydrogenation reactor, and the distributions of reaction parameters such as temperature and component concentrations in the reactor were further analyzed. Based on the validated CFD models, the structure and operating conditions of the reactor, as well as hydrogen load distribution ratios, are simulated for comparing the comprehensive performance metrics of ethylene selectivity and acetylene conversion rate; as a result, we can obtain the optimal temperature of 312 K, the optimal hydrogen/acetylene ratio of 0.10 as well as the optimal hydrogen load distribution ratio of 4:4:2, and the diameter/height ratio exerts a marginal effect on the selectivity, conversion rate and harmonic mean of the reactor.

During speciation-with-gene-flow, a transition from single-locus to multi-locus processes can occur, as strong coupling of multiple loci creates a barrier to gene flow. Testing predictions about such transitions with empirical data requires building upon past theoretical work and the continued development of quantitative approaches. We simulated genomes under different evolutionary scenarios of gene flow and divergent selection, extending previous work with the additions of neutral sites and coupling statistics, allowing us to investigate if and how selected and neutral sites differ in the conditions they require for transitions during speciation. As the per-locus strength of selection grew and/or migration decreased, it became easier for selected sites to show divergence – and thus to rise in linkage disequilibrium (LD) with each other as a statistical consequence – farther in advance of the conditions under which neutral sites could diverge. Indeed, even very low rates of gene flow were sufficient to prevent differentiation at neutral sites. However, once strong enough, coupling among selected sites eventually reduced gene flow at neutral sites as well. To explore whether similar transitions might be detectable in empirical data, we used published genome resequencing data from three taxa of Heliconius butterflies. We found that allele-frequency outliers and F ST outliers exhibited stronger patterns of LD than the genomic background, as expected. The statistical characteristics of LD – likely indicative of the strength of coupling of barrier loci – varied between chromosomes and taxonomic comparisons. Broad qualitative agreement between the patterns we observed in the empirical data and our simulations suggests that selection drives rapid genome-wide transitions to multi-locus coupling, illustrating how divergence and gene flow interact along the speciation continuum.

Human factors are the most relevant issues contributing to adverse events in obstetrics. Specific training of Crisis Resource Management (CRM) skills (i.e., problem solving and team management, resource allocation, awareness of environment, and dynamic decision-making) are now widespread and are often based on High Fidelity Simulation. In order to be used as a guideline in simulated scenarios, they need to be translated into specific and observable behavioral markers. To this purpose, we developed a set of observable behaviors related to the main elements of CRM in the delivery room. The observational tool was then adopted in a two-days seminar on obstetric hemorrhage where teams working in obstetric wards of six Italian hospitals took part to simulations. The tool was used as guide for the Io and as a peer-to-peer feedback. It was then rated for its usefulness in facilitating the reflection upon one’s own behavior, its ease of use, and its usefulness for the peer-to-peer feedback. The ratings were highly positive, around 4 in a 5-point scale. The CRM observational tool is therefore a useful, quick and easy solution to facilitate the debriefing, the peer-to-peer feedback and, most of all, the transfer of safe behavior from simulation to everyday practice.