The present study explores the effect of using two porous deflectors on the performance of the Savonius wind turbine compared to only one porous deflector. The numerical simulation is performed to solve the unsteady Navier-Stokes equations using the SST k-

Several therapeutic monoclonal antibodies are approved by FDA against the PD-1/PD-L1 (programmed death-1/programmed death ligand-1) immune checkpoint, which has been a great success in cancer treatment. However, existing therapeutics, including small molecules inhibitors against PD-L1 checkpoint have certain drawbacks such as high cost and drug resistance that challenge the current available anti-PD-L1 therapy. Thereof, this study presents the screening of 32552 compounds from Natural Product Atlas database against PD-L1, including three steps of structure-based virtual screening and binding free energy refinement for the selection of potent PD-L1 inhibitors. Subsequently, five natural compounds, i.e., Neoenactin B1, Actinofuranone I, Cosmosporin, Ganocapenoid A, and 3-[3-hydroxy-4-(3-methylbut-2-enyl)phenyl]-5-(4-hydroxybenzyl)-4-methyldihydrofuran-2(3H)-one, were collected based on the ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling and binding free energy (>-70 kcal/mol) for further computational investigation by comparison to co-crystallised ligand, i.e. JQT inhibitor. Based on interaction mapping, explicit 100 ns molecular dynamics simulation, and post binding free energy calculations, all the compounds exhibited intermolecular interactions (hydrogen and hydrophobic) with essential residues and substantial complex stability by comparison to the JQT inhibitor. Collectively, the calculated results advocate the selected natural compounds as the putative potent inhibitors of PD-L1 and, therefore, can be considered for further development of PD-L1 immune checkpoint inhibitor in cancer immunotherapy.

As one of the representatives of emerging metallic transition metal dichalcogenides, niobium ditelluride (NbTe₂) has attracted intensive interest recently due to its distorted lattice structure and unique physical properties. Here, we report on the ultrafast carrier dynamics in NbTe₂ measured using time-resolved pump-probe transient reflection spectroscopy. A thickness-dependent carrier relaxation time is observed, exhibiting a clear increase in the fast and slow carrier decay rates for thin NbTe₂ flakes. In addition, pump power dependent measurements indicate that the carrier relaxation rates are power-independent, with the peak amplitude of the transient reflectivity increasing linearly with pump power. Isotropic relaxation dynamics in NbTe₂ is also verified by performing polarization-resolved pump-probe measurements. These results provide an insight into the light-matter interactions and charge carrier dynamics in NbTe₂ and will pave the way for its applications to photonic and optoelectronic devices.

The seasonal and vertical spatial variation characteristics of total N, NH4+—N and NO3-—N in the soil in Picea mongolica forest at different stand ages were studied. The results showed that: (1) NH4+ —N in the soil in Picea mongolica forest was positively correlated with sample date, soil NO3-—N and forest age (P <0.05), and negatively correlated with soil depth (P < 0.01). NO3-—N in the soil in Picea mongolica forest was negatively correlated with sample date and forest age (P < 0.05), and significantly negatively correlated with soil depth (P < 0.01); (2) the content of NH4+—N is greater than that of NO3-—N in each soil layer of Picea mongolica forest at three forest ages. The correlation analysis showed which had an impact on the content of NH4+—N and NO3-—N in the soil in Picea mongolica forest. The content was lower in February and November, and higher in May and August；(3) The contents of total N, NH4+—N and NO3-—N in the soil of Picea mongolica forest in the three forest ages increased with the depth of soil layer (0-50cm), and showed an overall downward trend. The contents of NH4+—N in the soil layer of young forest (0-10cm, 10-20cm and 20-30cm, 30-40cm and 40-50cm) were significantly different (P＜0.05), and the contents of NO3-—N were also significantly different (P＜0.05), while their contents of middle-aged forest and near mature forest increased with the depth of soil layer, There was no significant difference in the content of NH4+—N; (4) The content of NH4+—N in the soil in Picea mongolica forest generally showed the following change trend near mature forest > middle-aged forest > young forest. The change trend of soil NO3-—N content is consistent with that of the content of NH4+—N in the soil in Picea mongolica forest.

Biodiversity conservation questions human practices towards biodiversity and, therefore, largely conflicts with ordinary societal aspirations. Decisions on the location of protected areas, one of the most convincing conservation tools, reflect such a competitive endeavor. Operations Research (OR) brings a set of analytical models and tools capable of resolving the conflicting interests between ecology and economy. Recent technological advances have boosted the size and variety of data available to planners, thus challenging conventional approaches bounded on optimized solutions. New models and methods are requested to use such a massive amount of data in integrative schemes addressing a large variety of concerns. Here, we provide an overview on the past, present and future challenges that characterize spatial conservation models supported by OR. By enlarging the spatial, temporal, taxonomic and societal horizons of biodiversity conservation planners navigate around multiple bio-socioeconomic equilibria and are able to decide on cost-effective strategies to improve biodiversity persistence.

It has been known that the performance of the High-Pressure Grinding Rolls (HPGR) varies as a function of method used to confine laterally the rolls, their diameter/length (aspect) ratio as well as their condition, if new or worn. However, quantifying these effects through direct experimentation in machines with reasonably large dimensions is not straightforward given the challenge, among others, of guaranteeing that the feed material remains unchanged. The present work couples the discrete element method (DEM) to multibody dynamics (MBD) and a novel particle replacement model (PRM) to simulate the performance of pilot-scale HPGRs grinding pellet feed. It shows that rotating side plates, in particular when fitted with studs, allow reaching more uniform forces along the bed, which also translates in a more constant product size along the rolls as well as higher throughput. It also shows that the edge effect is relatively constant with roll length, leading to substantially larger proportional edge regions for high-aspect ratio rolls. On the other hand, the product from the center region of such rolls was found to be finer when pressed at identical specific forces. Finally, rolls were found to have higher throughput, but generate a coarser product when worn following the commonly observed trapezoidal profile. The approach used in industry to compensate for roller wear by increasing the specific force and roll speed has then been demonstrated to be effective to maintain and potentially even increase product fineness and throughput, as long as the minimum safety gap is not reached.

We report the results of the characterization of local Monte Carlo (MC) dynamics of an equilibrium bond fluctuation model polymer matrix (BFM), in time interval typical for MC simulations of non-linear optical phenomena in host-guest systems. The study contributes to the physical picture of the dynamical aspects of quasi-binary mosaic states characterized previously in the static regime. The polymer dynamics was studied at three temperatures (below, above and close to the glass transition), using time-dependent generalization of the static parameters which characterize local free volume and local mobility of the matrix. Those parameters play the central role in the kinetic MC model of host-guest systems. The analysis was done in terms of the probability distributions of instantaneous and time-averaged local parameters. The main result is the characterization of time scales characteristic of various local structural processes. Slowing down effects close to the glass transition are clearly marked. The approach yields an elegant geometric criterion for the glass transition temperature. A simplified quantitative physical picture of the dynamics of guest molecules dispersed in BFM matrix at low temperatures offers a starting point for stochastic modeling of host-guest systems.

It has been more than a year since the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was found. This coronavirus has infected more than 110 million people worldwide by the end of February, 2021, and several virulent as well as more spreadable mutant forms of SARS-CoV-2 have emerged subsequently. In the latter group, three variants B.1.1.7, B.1.351, and P1 lineages, have been reported. Using computer simulation, the present paper investigates the structural differences between the wild type SARS-CoV-2 spike protein and its Asn501Tyr (N501Y) mutant variant. Time-based structural changes between the receptor binding domains of these two species are also examined. The N501Y mutation is common to all the three aforesaid mutant variants.

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim's offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.

Turbulent flow is the first and fundamental physical phenomena to evaluate when optimising cost and reducing emissions from an Anode Baking Furnace (ABF). Gas flow patterns, velocity field, pressure drop, shear stress, and turbulent dissipation rate variables are the main operational parameters to be optimised, considering a specific geometry. Computational Fluid Dynamics (CFD) allows simulating physical phenomena using numerical methods with computer resources. In particular, the finite element method is one of the most used methods to solve the flow equations. This method requires a discretisation of the geometry of the ABF, called mesh. Hence, mesh is the main input to the finite element method. A suitable mesh for applying a discretisation method determines whether the problem can be simulated or not. Generating an appropriate mesh remains a challenge to perform accurate simulations. In this work, a comparison between meshes generated using two mesh generation tools is presented. Results of different study cases are included.

Organic-organic interactions play important roles in the secondary organic aerosol formation, but the interactions are complex and poorly understood. Here we use environmental molecular beam experiments combined with molecular dynamics simulations to investigate the interactions between methanol and nopinone, as atmospheric organic proxies. In the experiments, methanol monomers and clusters are sent to collide with three types of surfaces, i.e., graphite, thin nopinone coating on graphite and multilayer surfaces, at temperatures between 140 K and 230 K. Methanol monomers are efficiently scattered from the graphite surface, whereas the scattering is substantially suppressed from nopinone surfaces. The desorption from the three surfaces is similar, suggesting that all the surfaces have weak or similar influences on the methanol desorption. The molecular dynamics results show that upon collisions the methanol clusters shatter, and the shattered fragments quickly diffuse and recombine to clusters. The desorption involves a series of processes, including detaching from clusters and desorbing as monomers. The experimental results also show that all trapped methanol molecules completely desorb within a short experimental time scale at temperatures of 180 K and above. At lower temperatures, the desorption rate decreases, and a long experimental time scale is used to resolve the desorption, where three desorption components are identified. The fast component is beyond the experimental detection limit. The intermediate component exhibits multi-step desorption character and has an activation energy of E_a = 0.18 ± 0.03 eV, in good agreement with simulation results. The slow desorption component is related to diffusion processes due to the weak temperature dependence.

Consumer products contain the chemical substances that threaten human health. The modeling methods and experimental methods have been used to estimate the inhalation exposure concentration by the consumer products. The model and measurement methods have the spatial property problem and time/cost consuming problem, respectively. For solving the problems due to the conventional methodology, this study performed the feasibility of applying CFD for evaluation of inhalation exposure by comparing the experiment results and the zero-dimensional results with CFD results. To calculate the aerosol concentration, the CFD was performed by combined the 3D Reynolds averaged Navier Stoke’s equation and discrete phased model using ANSYS FLUENT. As a result of comparing the three methodologies performed under the same simulation/experimental conditions, we found the zero-dimensional spray model shows approximately 5 times underestimated inhalation exposure concentration when compared with the CFD results and measurement results in near field. Also, the results of the measured concentration of aerosols at five locations and the CFD results at the same location were compared to show the possibility of evaluating inhalation exposure at various locations using CFD instead of experimental method. The CFD results according to measurement positions can predict rationally the measurement results with low error. In conclusion, in the field of exposure science, a guideline for exposure evaluation using CFD was found that complements the shortcomings of the conventional methodology, the zero-dimensional spray model and measurement method.

Arterial hypertension is a health problem that affects millions of people around the world. Particularly in Chile, according to the last health survey in 2019, 28.7% of the population had this condition, and arterial hypertension complications cause one in three deaths per year. In this work, we have used molecular simulation tools to evaluate new compounds designed in silico by our group as possible anti-hypertensive agents, taking Neutral Endopeptidase (NEP) as a target, a key enzyme in the arterial hypertension regulation at the level kidney. We use docking experiments, molecular dynamics simulation, free energy decomposition calculations (by MM-PBSA method), and ligand efficiency analysis to identify the best anti-hypertensive agent pharmacokinetic and toxicological predictions (ADME-Tox). The energetic components that contribute to the complexes stability are the electrostatic and Van der Waals components; however, when the ADME-Tox properties were analyzed, we conclude that the best anti-hypertensive candidate agents are Lig783 and Lig3444, taking Neutra Endopeptidase as a target.

Self-organized criticality (SOC) is a universal mechanism for self-sustained critical behavior in large-scale systems evolving outside equilibrium. Our report explores a tentative link between SOC and Lagrangian field theory, with the long-term goal of bridging the gap between complex dynamics and the non-perturbative behavior of quantum fields.

This paper deals with the characteristics of the cyclone separator from the Lagrangian perspective to design important dependent variables, develops a neural network model for predicting the separation performance parameter, and compares the predictive performance between the traditional surrogate model and the neural network model. In order to design the important parameters of the cyclone separator based on the particle separation theory, the force acting until the particles are separated was calculated using the Lagrangian-based CFD methodology. As a result, it was proved that the centrifugal force and drag acting on the critical diameter having a separation efficiency of 50% were similar, and the particle separation phenomenon in the cyclone occurred from the critical diameter, and it was set as an important dependent variable. For developing a critical diameter prediction model based on machine learning and multiple regression methods, Unsteady-RANS analyzes according to shape dimensions were performed. The input design variables for predicting the critical diameter were selected as four geometry parameters that affect the turbulent flow inside the cyclone. As a result of comparing the model prediction performances, the ML model showed the 32.5 % of improvement rate of R2 compared to the traditional MLR considering the nonlinear relationship between the cyclone design variable and the critical diameter. The proposed techniques have proven to be fast and practical tools for cyclone design.

Thermodynamics has been the foundation of many models of biological and technological systems. But thermodynamics is static and is misnamed. A more suitable name is thermostatics. Thermostatics does not include time as a variable and so has no velocity, flow or friction. Indeed, as usually formulated, thermostatics does not include boundary conditions. Devices require boundary conditions to define their input and output. They usually involve flow and friction. Thermostatics is an unsuitable foundation for understanding technological and biological devices. A time dependent generalization of thermostatics that might be called thermal dynamics is being developed by Chun Liu and collaborators to avoid these limitations. Electrodynamics is not restricted like thermostatics, but in its classical formulation involves drastic assumptions about polarization and an over-approximated dielectric constant. Once the Maxwell equations are rewritten without a dielectric constant, they are universal and exact. Conservation of total current, including displacement current, is a restatement of the Maxwell equations that leads to dramatic simplifications in the understanding of one dimensional systems, particularly those without branches, like the ion channel proteins of biological membranes and the two terminal devices of electronic systems. The Brownian fluctuations of concentrations and fluxes of ions become the spatially independent total current, because the displacement current acts as an unavoidable low pass filter, a consequence of the Maxwell equations for any material polarization. Electrodynamics and thermal dynamics together form a suitable foundation for models of technological and biological systems.

We prepared heterogeneous alumina-silicate glasses by consolidating nanoparticles using molecular dynamics simulations. Consolidated glasses from either low alumina content alumina-silicate glasses or high alumina content alumina-silicate glasses show significantly improved ductility around consolidation pressure of ~3 GPa. The introduced structural heterogeneities, namely over-coordinated network formers and their neighboring oxygen atoms, are identified as plasticity carriers due to their high rearrangement propensity. In addition, consolidated oxide glass from both 23.4Al₂O₃76.6SiO₂ and 73.1Al₂O₃26.9SiO₂ nanoparticles show improved flow strength (up to 1 GPa) due to the introduction of chemical heterogeneities. Last but not least, apparent hardening behavior appears upon cold work in consolidated glasses, with an increase of yield strength from ~3.3 GPa to ~6.4 GPa. This method is a big advancement toward ultra-strong and ultra-tough glasses by breaking the structure, composition and size limitations in traditional melt-quench process.

Droplet epitaxy allows the efficient fabrication of a plethora of 3D, III-V-based nanostructures on different crystalline orientations. Quantum dots grown on (311)A-oriented surface are obtained with record surface density, with or without a wetting layer. These are appealing features for quantum-dot lasing, thanks to the large density of quantum emitters and a truly 3D lateral confinement. However, the intimate photophysics of this class of nanostructures has not yet been investigated. Here we address the main optical and electronic properties of s-shell excitons in individual quantum dots grown on (311)A substrates with photoluminescence spectroscopy experiments. We show the presence of neutral exciton and biexciton as well as positive and negative charged excitons. We investigate the origins of spectral broadening, identifying them in spectral diffusion at low temperature and phonon-interaction at higher temperature, the presence of fine interactions between electron and hole spin, and a relevant heavy-hole/light-hole mixing. We interpret the level filling with a simple Poissonian model reproducing the power excitation dependence of the s-shell excitons. These results are relevant for the further improvement of this class of quantum emitters and their exploitation as single photon sources for low density samples as well as for efficient lasers for high density samples.

We used population reconstruction techniques to assess for the first time the population dynamics of a seagrass, Cymodocea nodosa, exposed to long-term elevated CO₂ near three volcanic seeps and compare them with reference sites away from the seeps. Under high CO₂, the density of shoots and of individuals (apical shoots), and the vertical and horizontal elongation and production rates, were higher. Nitrogen effects on rhizome elongation and production rates and on biomass, were stronger than CO₂ as these were highest at the location where the availability of nitrogen was highest. At the seep where the availability of CO₂ was highest and nitrogen lowest, density of shoots and individuals were highest, probably due to CO₂ effects on shoot differentiation and induced reproductive output, respectively. In all three seeps there was higher short- and long-term recruitment and growth rates around zero, indicating that elevated CO₂ increases the turnover of C. nodosa shoots.

This paper proposes the use of non-uniform extended surfaces installed externally to the tubes of the radiation section of fired heaters, in order to obtain a better heat flux distribution to the coils. To this end, the heat transfer mechanisms present in such equipment were studied through computational fluid dynamics (CFD), using simplified geometries that represent typical sizes of fired heaters. Also, a simplified model for the combustion was considered. Although this model oversimplifies the physics of the problem, it was able to give satisfactory results for the parameters being optimized, considering the main objective of this paper, that is to minimize the non-uniformity of heat flux in the tubes of the radiant section of fired heaters. It was possible to obtain optimized geometric parameters for different types of extended surfaces evaluated, coupling the results of these models with the Particle Swarm optimization method through the use of a response surface technique,. The results indicate a significant improvement in the uniformity of the heat flux distribution to the tubes through the use of the proposed extended surfaces. Thus, this solution reveals to be an interesting alternative to reduce the risks of fluid degradation and coking formation. Future studies must investigate the non-uniformity of the heat flux due to the presence of the flame and consider the interaction between the reactive flow and the participating medium. Nevertheless, this paper presents some results that justify the optimization of such extended surfaces taking into consideration thermal radiation.

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.

Most fully developed galaxies have vivid spiral structure, but the formation and evolution of spiral structure is still a mystery that is not fully understood in astrophysics. We find that the currently used equations of galactic dynamics contain some unreasonable components. In this paper, the following three working assumptions are introduced to simplify the galactic structural equations. 1. In the research of large-scale structure, the retarded potential of the gravitational field should be taken into account. The propagating time of the gravitational field from center to border is longer than the revolution periods of the stars near the center of galaxy. Newton's gravitational potential is unreasonable for such case, and the weak field and low velocity approximation of Einstein's field equation should be adopted. 2. The stars in a fully developed galaxy should be zero-pressure and inviscid fluid, and the equation of motion is different from that of ordinary continuum mechanics. Stars move along geodesics. 3. The structure of the galaxy is only related to the total mass density distribution. The equation of state of dark halo is different from that of ordinary luminous interstellar matter, so their trajectories are also very different. Dark halo and ordinary matter in galaxy are automatically separated. The total mass density distribution can be presupposed according to the observation data, and then it can be determined by comparing the solution of the equations with the observed data. These assumptions and treatments are supported by theory and observation. The variables of the equations of simplified galactic dynamics are separated from each other, and the equations are well-posed and can be solved according to a definite procedure. Therefore, this simplified dynamic equation system provides a more reasonable and practical framework for the further study of galactic structure, and can solve many practical problems. Besides, it is closely related to the study of dark energy and dark matter.

In this paper we show how to efficiently implement parallel discrete simulations on Multi-Core and GPU architectures through a real example of application: a cellular automata model of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with48cores and also an NVIDIA Tesla6V100 GPU, both running on Amazon Web Server (AWS) Cloud, and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results are compared and analysed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current Multi-Core CPUs with large core numbers can bring a performance very near to that of GPUs, even similar in some cases.

In our recently proposed theory of quantum gravity, a black hole arises from the spontaneous localisation of an entangled state of a large number of atoms of space-time-matter [STM]. Prior to localisation, the non-commutative curvature of an STM atom is described by the spectral action of non-commutative geometry. By using the techniques of statistical thermodynamics from trace dynamics, we show that the gravitational entropy of a Schwarzschild black hole results from the microstates of the entangled STM atoms and is given (subject to certain assumptions) by the classical Euclidean gravitational action. This action, in turn, equals the Bekenstein-Hawking entropy (Area/$4{L_P}^2$) of the black hole. We argue that spontaneous localisation is related to black-hole evaporation through the fluctuation-dissipation theorem.

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

Matrix Metaloproteinase-2 (MMP-2) is an extracellular Zn²⁺ protease specific to type I and IV collagens. Its expression is associated with several inflammatory, degenerative, and malignant diseases. Conformational properties, domain movements, and interactions between MMP-2 and its associated metal ions were characterized using a 1.0 µs molecular dynamics simulation. Dihedral principle component analysis revealed 10 families of conformations with the greatest degree of variability occurring in the link region connecting the catalytic and hemopexin domains. Dynamics cross correlation analysis indicated domain movements corresponding to opening and closing of the hemopexin domain in relation to the fibronectin and catalytic domains facilitated by the link region. Interaction energies were calculated using the MMPBSA-interaction entropy analysis method and revealed strong binding energies for the catalytic Zn²⁺ ion 1, Ca²⁺ ion 1, and Ca²⁺ ion 3 with significant conformational stability at the binding sites of Zn²⁺ ion 1 and Ca²⁺ ion 1. Ca²⁺ ion 2 diffuses freely away from its crystallographically defined binding site. Zn²⁺ ion 2 plays a minor role in conformational stability of the catalytic domain while Ca²⁺ ion 3 is strongly attracted to the highly electronegative sidechains of the Asp residues around the central β-sheet core of the hemopexin domain.

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

This article attempts to formulate a mathematical model for a potential explanation regarding the unavoidable impact of a rigid body's peculiar shape on the seamless flow over it. The solid body completely immersed in a Newtonian fluid and respectively has a relative open circuit flow on it will typically experience various observable phenomena like flow separation, flow transition, down-wash, stalling at the higher angle of attack, stalling velocity and how cambered airfoil can typically generate lift at a zero incidence angle. This article respectively represents an understanding of the laminar flow over a rigid body's external surface with due respect to its distinctive shape and size. This working paper formulates a more realistic and simplified mathematical model for open circuit laminar flow over a body, based on the historical data of aerodynamics and theoretical mechanics. This is intended to properly estimate forces on the continuous surface of the body in a laminar flow, to properly explain, understand and predict mentioned phenomena. Most of all the mechanism of streamline formation and its deformation with due regards to flow, shape and size of the body in an open-circuit laminar are formulated mathematically to enhance better design theory which can reduce experimentation while designing a streamlined body.

In order to perceive the behavior presented by the multiphase chemical reactors, the ant colony optimization algorithm was combined with computational fluid dynamics (CFD) data. This intelligent algorithm creates a probabilistic technique for computing flow and it can predict various levels of three-dimensional bubble column reactor (BCR). This artificial ant algorithm is mimicking real ant behavior. This method can anticipate the flow characteristics in the reactor using almost 30 % of the whole data in the domain. Following discovering the suitable parameters, the method is used for predicting the points not being simulated with CFD, which represent mesh refinement of Ant colony method. In addition, it is possible to anticipate the bubble-column reactors in the absence of numerical results or training of exact values of evaluated data. The major benefits include reduced computational costs and time savings. The results show a great agreement between ant colony prediction and CFD outputs in different sections of the BCR. The combination of ant colony system and neural network framework can provide the smart structure to estimate biological and nature physics base phenomena. The ant colony optimization algorithm (ACO) framework based on ant behavior can solve all local mathematical answers throughout 3D bubble column reactor. The integration of all local answers can provide the overall solution in the reactor for different characteristics. This new overview of modelling can illustrate new sight into biological behavior in nature.

In this research, the computational fluid dynamic (CFD) approach that has been used in wind power generation field was applied for the solution of the problems of local strong wind areas in railway fields, and the mechanism of wind generation was discussed. At the same time, the affectivity of the application of computational fluid dynamic approach to railway field was discussed. The problem of local wind that occurs on the railway line in winter was taken up in this research. A computational simulation for the prediction of wind conditions by LES was implemented and it was clarified that the local strong wind area is mainly caused by separated flows originating from the small‐scale terrain positioned at its upstream (at approximately 180.0 m above sea level). Meanwhile, the effects of the size of calculation area and spatial grid resolution on the result of calculation and the effect of atmospheric stability were also discussed. It was clarified that when the air flow characteristic of the separated flow originating from the small‐scale terrain (at altitude of approximately 180.0 m) targeted in this research is reproduced at high accuracy by computational simulation of wind conditions, approximately 10.0 m of spatial resolution of computational grid in horizontal direction is required. As a result of the computational simulation of wind conditions of stably stratified flow (Fr = 1.0), lee waves were excited at the downstream of the terrain over time. As a result, the reverse‐flow region lying behind the terrain that had been observed at a neutral time was inhibited. Consequently, local strong wind area was generated at the downstream of the terrain and the strong wind area passing through the observation mast was observed. By investigating the speed increasing rate of local strong wind area induced at the time of stable stratification, it was found that the wind was approximately 1.2 times stronger than what was generated at a neutral time.

This study aims to determine the optimal configuration (position and operation duration) for wall mounted mechanical mixers based on the comparison of three-dimensional computational fluid dynamics (CFD) modelling results and physical data collected from the treatment plant. A three-dimensional model of anoxic zone 1, 2 and 3 of Northern Wastewater Treatment Plant (WWTP) located at Cairns Regional Council, Cairns, Queensland, Australia was developed and validated. The model was used to simulate the flow pattern of the WWTP and the simulation results are in good agreement with the physical data varying between 0% to 15% in key locations. The anoxic zones were subject to velocities less than the desired 0.3 metres per second however results for suspended solids concentration indicate that good mixing is being achieved. Results for suspended solids concentrations suggest that the anoxic zones are towards the upper limits recommended by literature for specific power dissipation. The duration for operation of mechanical mixers was investigated and identified that the duration could be reduced from 900 seconds down to 150 seconds. Alternative mixer positioning was also investigated and identified positioning which would increase the average flow velocity with decreased duration (150 seconds). The study identified that Council may achieve savings of $24,000 per year through optimisation of the mechanical mixers.

Short-term (hours) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their geostationary orbits permit the collection of multiple images throughout each day. To assess the capability to detect changes in water properties caused by these processes, however, requires an understaning of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the variability during the day over a water region of low-productivity with the assumption that only small changes in the water properties occur during the day over the area of study. The complete GOCI mission data were processed using the SeaDAS/l2gen package. Filtering criteria were applied to assure the quality of the data. Relative differences with respect to the midday value were calculated for each hourly observation of the day. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was analyzed. We determined that the uncertainties in water-leaving “remote-sensing” reflectance ($R_\text{rs}$) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05$\times10^{-4}$, 5.49$\times10^{-4}$, 4.48$\times10^{-4}$, 2.51$\times10^{-4}$, 8.83$\times10^{-5}$, and 1.36$\times10^{-4}$ sr$^{-1}$, respectively, and 1.09$\times10^{-2}$ mg m$^{-3}$ for the chlorophyll-a concentration (Chl-{\it a}), 2.09$\times10^{-3}$ m$^{-1}$ for the absorption coefficient of chromophoric dissolved organic matter at 412 nm ($a_{\text{g}}(412)$), and 3.7 mg m$^{-3}$ for particulate organic carbon (POC). We consider these to be the floor values for detectable changes in the water properties due to biological, physical or chemical processes.

Filament wound composite pipes are frequently used in the field were transmission of high pressured chemical fluids, disposal of industrial wastes, oil and natural gas transmission takes place. In oil and gas industry, the pipelines transporting heavy crude oil are subjected to variable pressure waves causing fluctuating stress levels in the pipes. Computational Fluid Dynamics Analysis was performed using Ansys 15.0 Fluent software to study the effects of these pressure waves on some specified joints in the pipes. Depending on the type of heavy crude oil being used, the flow behavior indicated a considerable degree of stress levels in certain connecting joints, causing the joints to become weak over a prolonged period of use. In this research comparison of various pipe joints was done by using different material and the output result of the stress levels of the pipe joints were checked so that the life of the pipe joints can be optimized by the change of material.

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.

For condensed systems, the incorporation of quantum chemical solvent effects into molecular dynamics simulations has been a major concern. To this end, quantum mechanical/molecular mechanical (QM/MM) techniques are popular and powerful options to treat gigantic systems. However, they cannot be directly applied because of temporal and spatial discontinuity problems. To overcome these problems, in a previous study, we proposed a corrective QM/MM method, size-consistent multipartitioning (SCMP) QM/MM, and successfully demonstrated that, using SCMP, it is possible to perform stable molecular dynamics simulations by effectively taking into account solvent quantum chemical effects. The SCMP method is characterized by two original features: size-consistency of a QM region among all QM/MM partitioning and partitioning update. However, in our previous study, the performance was not fully elicited compared to the theoretical upper bound, and the optimal partitioning update protocol and parameters were not fully verified. To elicit the potential performance, in the present study, we simplified the theoretical framework and modified the partitioning protocol.

A new formulation for a proposed solution to the 3D Navier-Stokes Equations in cylindrical co-ordinates coupled to the continuity and level set convection equation is presented in terms of an additive solution of the three principle directions in the radial, azimuthal and z directions of flow and a connection between the level set function and composite velocity vector for the additive solution is shown. For the case of a vertical tube configuration with small inclination angle, results are obtained for the level set function defining the interface in both the radial and azimuthal directions. It is found that the curvature dependent part of the problem alone induces sinusoidal azimuthal interfacial waves wheras when the curvature together with the equation for the composite velocity is considered oscillating radial interfacial waves occur. The implications of two extremes indicate the importance of looking at the full equations including curvature.

Three cases of Day-Night Band (DNB) observations of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) are explored for applications to assess the ocean environment and monitor ocean dynamics. An approach to use the DNB radiance ratio was developed in order to better continuously assess the ocean diurnal and short-term environmental changes with VIIRS DNB observations. In the La Plata River Estuary, the sediment fronts showed 20–25 km diurnal inshore-offshore movements on March 13, 2017. In the waters off the Argentina coast in the South Atlantic, VIIRS DNB measurements provided continuous observations and monitoring of the algae bloom development and migration between 24–26 March 2016. This algae bloom generally kept the same spatial patterns, but moved nearly 20 km eastward in the three-day period. In the Yangtze River Estuary and Hangzhou Bay region in China’s east coast, VIIRS DNB observations also revealed the complicated coastal dynamic changes between 12–14 April 2017. Even though there are still some challenges and limitations for monitoring the ocean environment with VIIRS DNB observations, this study shows that satellite DNB observations can provide additional data sources for ocean observations, especially observations during the nighttime.

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

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.

After UV excitation, gas phase thymine returns to ground state in 5 to 7 ps, showing multiple time constants. There is no consensus on the assignment of these processes, with a dispute between models claiming that thymine is trapped either in the first (S1) or in the second (S2) excited states. In the present study, nonadiabatic dynamics simulation of thymine is performed on the basis of ADC(2) surfaces, to understand the role of dynamic electron correlation on the deactivation pathways. The results show that trapping in S2 is strongly reduced in comparison to previous simulations considering only non-dynamic electron correlation on CASSCF surfaces. The reason for the difference is traced back to the energetic cost for formation of a CO p bond in S2.

Robots in space are necessarily extremely light and lack structural stiffness resulting in natural frequencies of resonance so low as to reside inside the attitude controller’s bandwidth. A variety of input trajectories can be used to drive a controller’s attempt to ameliorate the control-structural interactions where feedback is provided by low-quality, noisy sensors. Traditionally, step functions are used as the ideal input trajectory. However, step functions are not ideal in many applications, as they are discontinuous. Alternative input trajectories are explored in this manuscript and applied to an example system that includes a flexible appendage attached to a rigid main body. The main body is controlled by a reaction wheel. The equations of motion of the flexible appendage, rigid body, and reaction wheel are derived. A feedback controller is developed to account for the rigid body modes. Additional filters are added to compensate for the system’s flexible modes. Sinusoidal trajectories are autonomously generated to feed the controller. Whiplash compensation is additionally implemented for comparison. The control method without random errors with the smallest error is the sinusoidal trajectory method, which showed a 97.39% improvement when compared to the baseline response when step trajectories were commanded, while the sinusoidal method was inferior to traditional step trajectories when sensor noise and random errors were present.

Oral drug absorption is the primary route for drug administration. However, this process hinges on multiple factors, including the drug’s physicochemical properties, formulation characteristics, and gastrointestinal physiology. Given its intricacy and the exorbitant costs associated with experimentation, the trial-and-error method proves prohibitively expensive. Theoretical models have emerged as a cost-effective alternative by assimilating data from diverse experiments and theoretical considerations. These models fall into three categories: data-driven models, encompassing classical pharmacokinetics, quantitative-structure models (QSAR), and machine/deep learning. Mechanism-based models include quasi-equilibrium, steady-state, and physiologically based pharmacokinetics, alongside first principles such as molecular dynamics and continuum models. This review provides an overview of recent modeling endeavors across these categories, evaluating their respective advantages and limitations. Additionally, a primer on partial differential equations and their numerical solutions is included in the supplementary materials, recognizing their utility in modeling physiological systems despite their mathematical complexity limiting their widespread application in this field.

Introduction: Papatasi fever, or three-day fever, is a viral disease transmitted by a species of female sandfly called Phlebotomus papatasi that has symptoms similar to influenza. Robat Karim County, due to the high abundance of Sandfly and climate change in recent years, provides a suitable environment for the growth and reproduction of Sandfly, especially Phlebotomus papatasi Therefore, the aim of this study was molecular monitoring of Papatasi fever virus in Sandfly of Robat Karim County, Tehran province. Materials and methods: In 7 selected areas in Robat Karim County, 679 Sandfly using sampling methods including traps and aspirators were caught and 500 samples were randomly selected according to the fishing location and transferred to the laboratory of the Medical Entomology Department. After fixing Sandfly on the slide surface, identification and percentage of frequency of sandfly species were determined and then by Real-time PCR method, molecular examination of Papatasi virus infection was performed at Tehran Pasteur Institute. Findings: Out of 679 samples taken, 310 (45.65%) belonged to males and 369 (54.35%) belonged to females. 7 species including 3 species of Sandfly of the genus Phlebotomus and 4 species of the genus Sergentomyia were identified among the samples, the highest percentage of catch belonged to Phlebotomus sergenti (28.57%). Of the 500 samples sent to the laboratory for testing for phleboviruses by Real-time PCR, no positive cases of Papatasi virus infection were observed in them. Conclusion: Robat Karim is one of the endemic areas of infectious diseases such as leishmaniasis. Due to climate change in this region that conditions for the growth and reproduction of Sandfly, especially Phlebotomus papatasi as a Vector of sandfly fever and since the sandfly fever disease is not vaccinated therefore, preventive measures to control and reduce diseases transmitted by Sandfly are important.

In patients with heart failure, the evaluation of left ventricular (LV) diastolic function is vital, offering crucial insights into hemodynamic impact and prognostic accuracy. Echocardiography stands as the primary imaging modality for diastolic function assessment, and using it effectively requires a profound understanding of the underlying pathology. This review covers four main topics: first, the fundamental driving forces behind each phase of normal diastolic dynamics, along with the physiological basis of two widely used echocardiographic assessment parameters, E/e' and mitral annulus early diastolic velocity (e'); second, the intricate functional relationship between the left atrium and LV in patients with varying degrees of LV diastolic dysfunction (LVDD); third, the role of stress echocardiography in diagnosing LVDD and the significance of parameter changes in this context; and fourth, the clinical utility of evaluating diastolic function from echocardiography images across diverse cardiovascular care areas.

Climate warming is expected to have pronounced effects on Arctic and Subarctic ecosystems, especially regions underlain by discontinuous and relatively warm permafrost. The main goal of this research is to evaluate the vulnerability and dynamics of permafrost under climate warming across the various ecotypes in respect of ecosystem stability, socioeconomic impact, and for better understanding possible future environmental changes. We suggested the new version of the spatially distributed permafrost dynamics model (GIPL2-MPI), which is developed in the Geophysical Institute, University of Alaska Fairbanks. This model is based on the ecosystem approach to simulate the permafrost dynamics, which we are discussing in this paper. We combined ground-based observations and numerical freeze/thaw modeling using climate-ecosystem-permafrost interactions to understand the physical processes and mechanisms controlling permafrost physical state. We predict the changes in permafrost conditions using output from two GCMs (NCAR-CCSM4 and GFDL-CM3) and Five-Model Average Ensemble for the RCP-4.5 and RCP-8.5 scaled down to 1 by 1 km spatial resolution (https://uaf-snap.org/) across entire Alaska. Our result shows that by the end of the current century widespread near-surface permafrost degradation could begin everywhere in Alaska southward of the Brooks Range as well as across some spots at the North Slope Alaska.

This manuscript presents a novel approach to estimating the potential within Schrödinger equations, with a particular focus on applications to the Navier-Stokes problem in fluid dynamics. By establishing new theoretical estimates, we delve into the intricate dynamics of fluid flow, aiming to unveil previously obscured aspects of the Navier-Stokes equations. Through a rigorous mathematical framework, we explore how these new potential estimates can provide a fresh perspective on fluid mechanics, contributing to the ongoing quest to solve some of its most persistent challenges.

As a widely used plastic, the aging and degradation of polyethylene (PE) are inevitable problems, whether the goal is to prolong the life of PE products or address the issue of white pollution. Molecular simulation is a vital scientific tool in elucidating the mechanisms and processes of chemical reactions. To obtain the distribution and evolution process of PE's thermal oxidation products, this work employs the self-consistent charge density functional tight binding (SCC-DFTB) method to perform molecular simulations of the thermal oxidation of PE with different crystallinity and branched structures. We discovered that crystallinity does not affect the thermal oxidation mechanism of PE, but higher crystallinity makes PE more susceptible to cross-linking and carbon chain growth, reducing the degree of PE carbon chain breakage. The branched structure of PE results in differences in pore size between the carbon chains, with larger pores leading to a concentrated distribution of O2 and free radicals subsequently formed. The breakdown of PE is slowed down when free radicals are localized in low-density regions of the carbon chain. The specifics and mechanism of PE's thermal oxidation are clearly revealed in this paper, which is essential for understanding the process in-depth and for the development of anti-aging PE products.

The attitude dynamics and orbit dynamics of large rigid space structures are coupled with each other under gravity gradient, which may affect the stability of the large rigid space structures. In this paper, the gravity gradient stability of a large rigid space structure is studied under both small and large disturbances. Based on the rigid body dynamics and orbit dynamics, an accurate dynamic model without any linearization of the large rigid space structure is established via the natural coordinate formulation (NCF), which is able to describe the large overall motions of the structures. By using the generalized-α algorithm, the gravity gradient stability of the large rigid space structure is simulated and analyzed via various examples, including the influence of large disturbance angles, the positions at the stabilization and unstabilization regions. Finally, the relationship between spinning stability and gravity gradient stability is also investigated via a large spinning space structure.

This article objective was to identify a centenary trend in the growth and development of girls in the metropolis of Moscow. Material and methods — The physical development (body length and weight, chest circumference, right hand muscle strength, and menstrual function development) of Moscow girls was studied during the period from 1920 to 2020. The amount of own observations was 4581 girls aged 8-17 years. Results – A comparative analysis of the physical development of Moscow school girls of different decades revealed a statistically significant increase in body length by 3-5 cm and a significant increase in chest circumference in all age groups of girls of the beginning of the XXI century, compared with their peers in the 1960s and 1980s, which indicates the completion of the gracialization processes that have been observed since the 1980s. However, in all age groups, a decrease in the muscle strength of the right hand is still being noticed. Earlier terms of menarshe onset in modern Moscow school girls (12 years 9 months) and a shift in growth jumps to earlier terms were established. It is shown that the age of menstruation depends on the level of family wealth. Conclusions. In Moscow girls in the centenary dynamics, a tendency to increase the total body size and shift the terms of biological maturation to earlier terms was revealed.

A new approach was presented in this study to simulate a stable atom along with subatomic particles in it. Subatomic particles in an atom are treated as conventional particles, exhibiting attraction and repulsion between them, giving a stable atom simulation. This new approach leads to developing new potentials for subatomic particles to simulate a stable atom. Subatomic particle dynamics (SPD) simulations were developed for within-atom simulations that give a stable atom structure for infinite time and provide many insights into electron trajectories and atom properties like energies and radius of the atom. The effect of protons and neutrons movement in the nucleus on electron trajectories was captured in SPD. Hydrogen and Carbon atom SPD were reported in this study. The Pilot-wave theory was implemented in this study to simulate the wave nature of subatomic particles in an atom. Electrons motion was guided by the interference pattern produced by the electron’s aether medium waves in SPD. SPD was implemented on molecules, resulting in a stable molecular structure giving insights into electron trajectories shared by multiple atoms.

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

Cholinesterase (ChE) and secretase (BACE) inhibitors, and fibril- and β-amyloid-suppressing medicines are used to treat Alzheimer's disease (AD) symptomatically. The prevalence and complex nature of AD have increased the urgent need for multi-targeted directed ligands (MTDLs). This is because MTDLs can prevent potential drug-drug interactions during poly-therapy and have a better therapeutic profile than single targeted agents. Using piperazine linker or spacer and two primary scaffolds, benzofuran and 8-hydroxyquinoline, a unique class of multi-targeted medicines was recently reported by our group. These compounds showed re-markable effectiveness in inhibiting Aβ1-42 aggregation and acting as iron chelators.The results prompted us to synthesize an additional series of compounds as multimodal anti-AD agents and investigate its inhibitor activities to ChE (AChE/BChE) and BACE1 enzymes. The resulting in-hibitory effects suggested that the compounds under study might be used to improve cognitive function. The docking analysis' findings revealed that the compounds bind to AChE and BChE by forming H-bond interactions with amino acid residues at binding sites and µ-stacking inter-actions with aromatic residues, whereas the binding to BACE1 only revealed H-bond interac-tions with amino acid residues at binding sites.

Despite ample warning and significant lead time, global society has not acted sufficiently to combat climate change, and global carbon dioxide emissions are now about 60% higher today than in 1990 [1]. This paper uses marine fisheries as an analog model to compare with the many similar management issues faced with global climate change. Both marine fisheries and global climate change are complex systems that have similar properties that make management very difficult. A simple fishery prototype model is used to educate citizens about similar issues of dynamic complexity found in climate change models. We highlight how our slow reaction time to global climate change can be thought of as a mismatch between our cognitive abilities and the nature of global collective problems. Understanding the history and system structure of marine fisheries can provide insight into managing global climate change. We suggest ways to improve communication between science and citizens for updating mental models and changing climate policy.

In addition to their importance in statistical thermodynamics, probabilistic entropy measurements are crucial for understanding and analyzing complex systems, with diverse applications in time series and one-dimensional profiles. However, extending these methods to two- and three-dimensional data still requires further development. In this study, we present a new method to classify spatiotemporal processes based on entropy measurements. To test and validate the method, we selected four classes of similar processes related to the evolution of random patterns: dynamic colored noises ((i)~white and (ii)~red); (iii)~weak turbulence from reaction-diffusion; (iv)~hydrodynamic fully developed turbulence, and (v)~plasma turbulence from MHD. Considering seven possible ways to measure entropy from a matrix, we present the method as a parameter space composed of the two best separating measures of the five selected classes. The results highlight better combined performance of Shannon Permutation Entropy ($S^p_H$) and a new approach based on Tsallis Spectral Permutation Entropy ($S^s_q$). Notably, our observations reveal the segregation of reaction terms in this $S^p_H \times S^s_q$ space, a result that identifies specific sectors for each class of dynamic process, and can be used to train machine learning models for automatic classification of complex spatiotemporal patterns.

If visible matter alone is present in the Universe, General Relativity (GR) and its Newtonian weak field limit cannot explain several pieces of evidence, from the largest to the smallest scales. The most investigated solution is the cosmological model ΛCDM, where GR is valid and two dark components are introduced, dark energy and dark matter, to explain the ∼70% and ∼25% of the mass-energy budget of the Universe, respectively. An alternative approach is provided by modified gravity theories, where a departure of the gravity law from ΛCDM is assumed and no dark components are included. This work presents refracted gravity (RG), a modified theory of gravity formulated in a classical way where the presence of DM is mimicked by a gravitational permittivity ϵ(ρ) monotonically increasing with the local mass density ρ, which causes the field lines to be refracted in small density environments. Specifically, the flatter the system the stronger the refraction effect and, thus, the larger the mass discrepancy if interpreted in Newtonian gravity. RG presented several encouraging results in modelling the dynamics of disk and elliptical galaxies and the temperature profiles of the hot X-ray emitting gas in galaxy clusters and a covariant extension of the theory seems to be promising.

This comprehensive review delves into gold market business management, covering historical perspectives, market dynamics, mining models, investment strategies, technology, regulations, global trends, and sustainability. Starting with a historical overview, it traces the gold market's evolution and analyzes supply-demand dynamics, price fluctuations, and geopolitical influences. The article scrutinizes gold mining models, evaluating environmental and social responsibilities, and explores financial management strategies, emphasizing risk and gold's role in portfolios. Examining technology's role, it highlights innovations in exploration, mining, and processing for improved efficiency and sustainability. The regulatory landscape analysis encompasses compliance challenges, environmental regulations, and ethical considerations, emphasizing global impacts. Global market trends are explored, identifying potential opportunities and challenges, offering strategic insights. The review concludes by evaluating sustainability practices, emphasizing environmental conservation, community engagement, and ethical sourcing.

Generating early warning signals of reduced resilience in ecosystems is crucial for conservation and management endeavors. However, the practical implications of such early warning signal systems are still limited by the lack of data and uncertainties associated with predicting complex systems such as ecosystems. This research aims to investigate the feasibility of developing an early warning system capable of identifying an upcoming critical transition within mangrove forest ecosystems. Using time series analysis of remote sensing images, the resilience of mangrove forests was explored across two distinct study sites. One site (Qeshm Island) has been adversely affected by land-use and land-cover changes, while the other (Gabrik) serves as a reference ecosystem. The study uses data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite to quantify three remotely sensed indices: the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), and the Modified Vegetation Water Ratio (MVWR). In addition, Landsat data has been used to explore temporal alterations in land-use and land cover. To identify early warning signals, indicators such as autocorrelation (acf(1)), standard deviation (SD), and skewness (SK) are applied. The findings indicate a signal of reduced resilience by a significant increase in NDVI statistical metrics (acf(1): 0.50, SD: 0.9). Although MNDWI showed significant early warning signals in Qeshm Island (acf(1); 0.86, SD: 0.90), it provided a false alarm in the reference study site. MVWR failed to generate early warning signals of reduced resilience (acf(1); -0.100, SD: -0.07, SK: -0.21). Land-use land-cover change may explain reduced resilience in the forests. This study not only emphasizes the potential of remote sensing in monitoring the state of mangrove forests but also contributes to advancing our understanding of ecosystem dynamics. The findings of this study can be integrated with ecosystem management tools to enhance the effectiveness of conservation efforts aimed at safeguarding mangroves. This is the first report of the successful application of remote sensing in generating early warning signals of reduced resilience within mangrove forests in the Middle East.

Atomic force microscopes are used, beside their principal function as surface imaging tools, in surface manipulation and measurement of interfacial properties. In particular, they can be modified to measure lateral friction forces that occur during the sliding of the tip against the underlying substrate. However, the shape, size, and deformation of the tips profoundly affect the measurements in a manner that is difficult to predict. In this work, we investigate the contribution of these effect to the magnitude of the lateral forces during sliding. The surface substrate is chosen to be few-layer AB-stacked graphene surface whereas the tip is initially constructed from face-centered cubic gold. In order to separate the effect of deformation from shape, rigid tips of three different shapes were considered first, namely a cone, a pyramid and a hemisphere. The shape was seen to dictate all aspects of the interface during sliding, from temperature dependence to stick-slip behavior. Deformation was investigated next by comparing a rigid hemispherical tip to one of identical shape and size but with all but the top three layers of atoms free to move. The deformation, as also verified by an indentation analysis, occurs by means of the lower layers collapsing on the upper ones, thereby increasing the contact area. This collapse mitigates the friction force and decreases it with respect to the rigid tip for the same vertical distance. Finally, the size effect is studied by means of calculating the friction forces for a much larger hemispherical tip whose atoms are free to move. In this case, the deformation is found to be much smaller but the stick-slip behavior is much more clearly seen.

This research provides a computationally efficient numerical tool for predicting 3-D turbulent flows over hydrofoils. It addresses a gap in existing numerical methods by extending the capabilities of the laminar VIScous Vorticity Equation (VISVE) solver to handle 3-D turbulent flow scenarios. The implementation integrates the k − ω SST model into the 3-D VISVE solver using the Finite Volume Method (FVM), extending its capability to handle turbulent flows. The turbulence model is also parallelized to improve computational efficiency. The application of the newly developed model to 3-D hydrofoil cases expands its scope and serves as preparatory work for future rotational propeller applications. Rigorous testing includes a convergence analysis concerning grid numbers and time step sizes, and validation against a Reynolds-Averaged Navier-Stokes (RANS) solver ensures the reliability and accuracy of the enhanced VISVE solver for turbulent flow simulations. The turbulent VISVE solver offers advantages such as reduced computational domain and costs through a vorticity-based approach. Turbulence concentration within boundary layers and free shear flows does not compromise the advantages of the small computational domain. The simplified meshing process, automatically generated by denoting the number of panels on the hydrofoil, makes the solver accessible for researchers and engineers.

Small submersible drainage pumps discharge leaking water and rainwater in buildings. In an emergency (e.g., heavy rain or accident), monitoring the flow rate in advance is necessary to enable optimal operation, considering the point where the pump operates abnormally when the water level increases rapidly. In another, pump performance optimization is crucial for energy saving policy. Therefore, it is necessary to meet the challenges of submersible pump systems, including sustainability and pump efficiency. The final goal of this study is to develop an energy-saving, high-efficiency submersible drainage pump capable of responding to emergencies. In particular, this paper targeted the hydraulic performance improvement of a submersible drainage pump model. Before the development of driving mode-related technology capable of emergency response, we first tried to find a way to improve the performance characteristics of the existing submersible drainage pump. Rather than designing a new pump, we disassembled the current pump and reverse engineering. Then, numerical simulation was performed to analyze the flow characteristics and efficiency of the pump. Then, the pump test was carried out to obtain the performance and validated with numerical results. Results revealed that changing the cross-sectional shape of the impeller reduced the flow separation and enhanced velocity and pressure distributions. Also, it reduced the power and increased efficiency. Results also showed that the pump's efficiency increased to 5.56% at a discharge rate of 0.17 m3/min, and overall average efficiency increased to 6.53%. In addition, the submersible pump design method could be suitable for the optimized pump's impeller and casing numerically. This paper can provide insight and information on the design optimization of pumps.

Redox-flow batteries are rechargeable batteries that store energy in two liquid electrolytes, separated by a membrane. During charging and discharging, the electrolytes flow through the membrane and undergo chemical reactions that generate or consume electrical energy. These batteries are known for their scalability and long cycle life and are versatile energy storage technologies developed to enhance efficiency and lower costs. Deep Eutectic Solvents (DES) are eco-friendly alternatives to traditional electrolytes, and their properties have been studied to improve the performance of redox-flow batteries. We investigated choline chloride/ethylene glycol (ChlCl/Eg) mixtures with LiPF6 salt at four concentrations through experimental and MD simulations. The thermophysical and transport properties of the mixture, including density, diffusion coefficient, viscosity, and ionic conductivity, were calculated across a temperature range of 298.15–398.5 K. Our findings indicate that an increase in salt concentration leads to a decrease in diffusion coefficients and ionic conductivity, while increasing the viscosity of the deep eutectic solvent. This research provides valuable insights into the behavior of DES mixtures and can aid in the design and optimization of DES-based processes for use in redox-flow batteries.

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

To address global warming, there is a worldwide effort to establish carbon-neutral energy plans. Given the characteristics of renewable energy generation, a diverse 'Energy Mix' consisting of various energy sources such as wind and solar power is crucial. In particular, the wind power is expected to continue expanding globally due to its sustainable nature. Furthermore, the expan-sion of offshore wind farm is making essential and a rapidly growing industry sector to be achieving carbon neutrality with limited land for construction. To facilitate the construction and operation of offshore wind farms, specialized vessels with dynamic positioning (DP) systems are essential such as Wind Turbine Installation Vessels (WTIVs) and Service Operating Vessels (SOVs). The purpose of this study is to predict and analyze the scale and structural changes in the fleet capacity of DP vessel, which is essential for offshore wind power construction as the offshore wind power industry develops using System Dynamics (SD) modeling. Specifically, this study aims to construct a demand forecasting model for DP vessel used in offshore wind farm con-struction based on SD methodology. The study aims to identify influencing factors by analyzing dynamic changes in system configurations over time and establishing causal relationships based on feedback structures. Instead of traditional time series analysis methods, causal relation-ship-based simulations were conducted for quantitative analysis. The results provide insights into the changes in the DP vessel market structure due to the emergence of the new industry and highlight areas that require improvement throughout the industry.

Autonomous Underwater Vehicles (AUVs) are emerging as pivotal tools in underwater applications such as seafloor exploration and the inspection of pipelines or cables. Traditional land-based avoidance methods prove insufficient when applied to the complex underwater environment, largely due to the unique constraints presented by marine environments and the specific dynamics of AUVs. In this study, we introduce an improved stream function-based obstacle avoidance algorithm specifically tailored for autonomous underwater vehicles. The proposed algorithm is based on a stream function that is derived from the stream function. The stream function is characterized by a radial histogram for the cost function. In addition, constraints related to the maximum path curvature are discussed to optimize the utility of the path. Our exhaustive simulation cases validate the robustness and adaptability of the proposed algorithm, demonstrating its ability to produce feasible and optimized avoidance paths in a variety of scenarios.

In order to balance the conflicts among mass flow rate, total pressure ratio, adiabatic efficiency and stall margin in a low-bypass transonic fan, the optimization of the rotor blade is implemented in this study. An advanced 3D optimization design system is adopted, and flow diagnostic methods based on vorticity dynamics are employed to discuss the flow field. Results indicate that by controlling the blade camber line curvature, significant improvements in the aerodynamic performance for the fan stage are achieved, the total pressure ratio is increased by 1.90%, while the adiabatic efficiency and mass flow rate are increased by 4.45% and 5.82%, respectively. Vorticity diagnosis suggest that there exists a close link between performance parameters and vorticity parameters in the axial fan/compressor, both azimuthal vorticity and boundary vortex flux have significant influences on the stage performance. Moreover, the boundary layer separation is accompanied by the spike of entropy and static pressure, while the derivation/gradient of these flow parameters would also suffer drastic changes under the effect of shock wave. The vorticity parameters could provide detailed flow information about the on-wall flow with high accuracy, which provides the researchers with a novel method for the turbomachinery aerodynamic design and analysis.

Polymerase chain reaction (PCR) technique is one of the molecular methods in amplifying DNA for the detection of malaria. However, the limitations of PCR especially when used for routine clinical practice can hamper its sensitivity and specificity. With that, this study focuses on designing a microfluidic device that will mimic the function of a conventional genus-specific PCR based on 18S rRNA gene to detect malaria parasites (Plasmodium falciparum) at low grade parasitemia. The design was drawn and simulated using ANSYS 14.5 Computational Fluid Dynamics (CFD). The simulation shows that adding loops to the design increases its relative deviation but to a minimal extent as compared to having only a straight path design, which indicates that looping is acceptable in designing a microfluidic device to minimize chip length. Also, increasing the cross-sectional area of the fluid path decreases the efficiency of the design, thus, the design with a relatively smaller cross-sectional area is favored. And lastly, among the three materials utilized, the chip made of polypropylene is the most efficient with a relative deviation of 0.94 as compared to polycarbonate and polydimethylsiloxane which have relative deviations of 2.78 and 1.92, respectively.

The status of vegetation and the impacts of mammalian herbivores on rangelands are complex, and such studies in Kenya are scanty. We investigated the dynamics of ground cover vegetation in Hell’s Gate National Park in relation to mammalian herbivory. Removal of palatable vegetation is postulated to enhance the development of invasive plant species. We investigated the influence of mammalian herbivores on vegetation diversity and dynamics in this rangeland. Three sampling blocks approximately 3 Km apart measuring 100 m x 50 m were established, each divided into three belt-transects (100 m x 10 m), and separated by a 10 m buffer zone. 2 m by 2 m quadrats at 20 m intervals were established in each transect. We measured composition the richness of plant and mammal species, and herbivory levels four times for six months (September 2018 to February 2019). Plant cover (P&lt; 0.001) and species diversity (P&lt; 0.001) differed significantly among sampling blocks and between seasons (P&lt; 0.001). Non-metric multidimensional scaling of plant species and herbivores showed co-occurrence of Zebras with Sida tenuicarpa and giraffes with Solanum incunum. We conclude that the removal of preferred plants through herbivory may be giving an edge to invasive species in the park.

The available direct gas dynamic tables provide the area ratio and the Prandtl-Meyer(P-M) angle of isentropic expansion of gas as functions of the Mach number. But finding the value of the Mach number in terms of area ratio or P-M angle requires an inverse function. Currently, the Mach number is determined by either interpolation from the direct gas dynamics tables, or the application of non-linear equation solvers using numerical methods. Both methods are approximate. In this paper inverse functions for Mach number in the form of Taylor’s series expansions are reported to develop the so-called inverse tables. The advantage of this approach is that the Mach number with a greater accuracy, referred to as nearly exact can be obtained by reading from the inverse table. In the presentation, the necessary equations and new tables that can be used by the scientific community will be disseminated. The data and computer programs are made available on GitHub through https://github.com/anillals/Inverse-gas-dynamic-tables- and-codes. A paper describing the complete mathematical steps in the derivation of the equations can be found at https://rdcu.be/dgrlf

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

Efficient natural convection-cooled heat sinks are vital to the future of electronics cooling due to their low energy demand in the absence of an external pumping agency in comparison to other cooling methods. The present study is aimed to identify the most effective fin design for enhancing heat transfer in natural convection applications. Initially, a baseline case with rectangular fins was considered in the present study and it was optimized with respect to fin spacing. This optimized baseline case is then validated against the semi-empirical correlation proposed by Elen-baas (1942) [2]. Upon good agreement, the validated model is used for comparative analysis of different heat sink configurations with rectangular, trapezoidal, curved, and angled fins. The optimised fin spacing obtained for the baseline case is also used for the other heat sink configura-tions and then the fin designs are further optimized for better performance. However, for the an-gled fin case, the optimized configuration proposed by Zhang et al. (2020) [3] is adopted in the present study. This study is carried out with Ansys Fluent for a Rayleigh number of 2.4 × 10^6. The proposed novel curved fin design with a shroud defined as Case C4 showed a 4.1% decrease in the system’s thermal resistance with an increase in the heat transfer coefficient of 4.4% when compared to the optimized baseline fin case. The obtained results are further non-dimensionalized with proposed scaling in terms of the baseline case for the two novel heat sink cases (trapezoidal, curved).

Friction has long been an important issue in multibody dynamics. Static friction models apply appropriate regularization techniques to convert the stick inequality and the non-smooth stick-slip transition of Coulomb’s approach into a continuous and smooth function of the sliding velocity. However, a regularized friction force is not able to maintain long-term stick. That is why, dynamic friction models were developed in the last decades. The friction force depends herein not only on the sliding velocity but also on internal states. The probably best known representative, the LuGre friction model, is based on a fictitious bristle but realizes a too simple approximation. The recently published second order dynamic friction model describes the dynamics of a fictitious bristle more accurately. Its performance is compared here to stick-slip friction models, developed and launched not long ago by commercial multibody software packages.

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

The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

Evolutionary ecology may be described as explaining ecology through evolution and vice versa, but one may also view it as an integration of the two fields, where one takes the view that ecology and evolution are inseparable, and one can only begin to understand the biology of organisms by synthesizing the two fields. An example of such a synthesis is the biology of high fecundity and the associated concept of sweepstakes reproduction, or skewed individual recruitment success. As an illustration we consider selection at linked sites under various dominance and epistasis mechanisms in a diploid population evolving according to random sweepstakes and experiencing recurrent bottlenecks. Using simulations we give a few examples of the impact of the stated elements on selection. We show that depending on the dominance mechanisms random sweepstakes can shorten the time to fixation (conditional on fixation) of the fit type at all sites. Bottlenecks tend to increase the fixation time, with random sweepstakes counteracting the effects of bottlenecks on the fixation time. Understanding the effect of random sweepstakes, recurrent bottlenecks, dominance mechanisms and epistasis on the fate of selectively advantageous mutations may help with explaining genetic diversity in natural highly fecund populations possibly evolving under sweepstakes reproduction.

Precise binding affinity predictions are essential for structure-based drug discovery (SBDD). Focal adhesion kinase (FAK) is a member of the tyrosine kinase protein family and is overexpressed in a variety of human malignancies. Inhibition of FAK using small molecules is a promising therapeutic option for several types of cancer. Here, we conducted computational modeling of FAK targeting inhibitors using 3-dimensional structure-activity relationship (3D-QSAR), molecular dynamics (MD), and hybrid topology-based free energy perturbation (FEP) methods. The structure-activity relationship (SAR) studies between the physicochemical descriptors and inhibitory activities of the chemical compounds were performed with reasonable statistical accuracy using CoMFA and CoMSIA. These are two well-known 3D-QSAR methods based on the principle of supervised machine learning (ML). Essential information regarding residue-specific binding interactions was determined using the MD and MM-PB/GBSA methods. Finally, physics-based relative binding free energy (〖∆∆G〗_RBFE^(A→B)) values of analogous ligands were estimated using the alchemical FEP simulation. An acceptable agreement was observed between the experimental and computed relative binding free energies. The overall results using ML and physics-based hybrid approaches could be useful for the rational optimization of accessible lead compounds with similar scaffolds targeting the FAK receptor.

The natural product Salvinorin A (SalA) was the first nitrogen-lacking agonist discovered for the opioid receptors and exhibits high selectivity for the kappa opioid receptor (KOR) turning SalA into a promising analgesic to overcome the current opioid crisis. Since SalA’s suffers from poor pharmacokinetic properties, particularly the absence of gastrointestinal bioavailability, fast metabolic inactivation and subsequent short duration of action, the rational design of new tailored analogs with improved clinical usability is highly desired. Despite being known for decades, the binding mode of SalA within the KOR remains elusive as several conflicting binding modes of SalA were proposed hindering the rational design of new analgesics. In this study, we rationally determined the binding mode of SalA to the active state KOR by in silico experiments (docking, molecular dynamics simulations, dynophores) in the context of all available mutagenesis studies and structure-activity relationship (SAR) data. To the best of our knowledge this is the first comprehensive evaluation of SalA’s binding mode since the determination of the active state KOR crystal structure. SalA binds above the morphinan binding site with its furan pointing towards the intracellular core while the C2-acetoxy group is oriented towards the extracellular loop 2 (ECL2). SalA is solely stabilized within the binding pocket by hydrogen bonds (C210ECL2, Y3127.35, Y3137.36) and hydrophobic contacts (V1182.63, I1393.33, I2946.55, I3167.39). With the disruption of this interaction pattern or the establishment of additional interactions within the binding site we were able to rationalize the experimental data for selected analogs. We surmise the C2-substituent interactions as important for SalA and its analogs to be experimentally active, albeit moderate frequency within MD simulations of SalA. We further identified the non-conserved residues 2.63, 7.35, and 7.36 responsible for the KOR subtype selectivity of SalA. We are confident that the elucidation of the SalA binding mode will promote the understanding of KOR activation and the facilitate the development of novel analgesics that are urgently needed.

The problem of fluid dynamics can be greatly simplified if, for every point in space, the strain-rate tensor is diagonalized. This tensor is introduced into the Navier-Stokes equations via material law and divergence of the stress tensor. This article shows that local SO(3)xU(1) gauge fields can be used to locally diagonalize the diffusion components of the strain-rate tensor. The gauge fields resulting from the connection can be interpreted as convection components of the flow, they show properties of quasiparticles and can be interpreted as elementary vortices. Thus, the proposed approach not only offers new insights for the solution and situative simplification of the Navier-Stokes equations, it also uncovers hidden symmetries within the flow convection, allowing - depending on boundary conditions - further interpretation.

Culture exploits the acquisition of meaningful content by crafting regimes of shared attention, determining what is relevant, valuable, and salient. Culture changes the field of relevant social affordances worthy of being acted upon in a context-sensitive manner. When relevant affordances are highly weighted, their attentional capture and their salience increase the probability of them being enacted due to the associated expectation for minimizing prediction error. This process is known as active inference. In the digital era, individuals need to infer the action-related attributes of digital cues, here characterized as digital affordances. The digital affordances of digital social platforms are of particular interest here. Digital social affordances are defined as online possibilities of social interactions. By their own nature, these are salient because they are related to social interactions and relevant social cues. However, the problem of digital social platforms is that they are not equivalent to situated social interactions because their structure is built, mediated, and defined by third-parties with diverse interests. The third-parties behind the digital social platforms are using the same mechanism exploited by culture to manipulate the shared patterns of attention. Moreover, digital social platforms are deliberately designed to be hyper-stimulating, making digital social affordances highly rewarding and increasingly salient. This appropriation, for economic purposes, is an issue of great importance, especially as the COVID-19 pandemic brought deep global changes, pushing societies to an online digital way of life. Here, we examined different types of digital social affordances under an active inference view, placing them into two categories, those for self-identity formation, and those for belief-updating. This paper aims to analyze digital social affordances in light of the prediction error dynamics they might elicit to their users. Although each of the analyzed digital social affordances allows different epistemic and instrumental digital actions, they all share the characteristic of having an "easy" and a fast expected rate of error reduction. Here, we aim to provide a new hypothesis about how the design behind digital social affordances is built on our natural attractiveness to minimize prediction error and the resulting positive embodied feelings when doing so. Finally, it is suggested that because digital social affordances are becoming highly weighted in the field of affordances, this might be putting at risk our context-sensitive grip on a rich, dynamic and varied field of relevant affordances.

This paper presents a novel theoretical and computational methodology for the generation of an onset turbulent field with prescribed properties in the numerical simulation of an arbitrary viscous flow. The methodology is based on the definition of a suitable distribution of volume force terms in the right–hand side of the Navier–Stokes equations. The distribution is represented by harmonic functions that are randomly variable in time and space. The intensity of the distribution is controlled by a simple PID strategy in order to obtain that the generated turbulent flow matches a prescribed turbulence intensity. A further condition is that a homogeneous isotropic flow is es- tablished downstream of the region where volume force terms are imposed. Although it is general, the proposed methodology is primarily intended for the computational modelling of hydrokinetic turbines in turbulent flows representative of tidal or riverine installations. A first numerical applica- tion is presented by considering the injection of homogeneous and isotropic turbulence with 16% intensity into a uniform unbounded flow. The analysis of statistical properties as auto-correlation, power spectral density, probability density functions, demonstrates that the generated flow tends to achieve satisfactory levels of stationarity and isotropy, whereas the simple control strategy used determines overestimated turbulent intensity levels.

Herein, we are proposing two chalcone molecules, (E)-1-(4-methoxyphenyl)-3-(p-tolyl) prop-2-en-1-one and (E)-3-(4-hydroxyphenyl)-1-(2,4,6-trihydroxyphenyl) prop-2-en-1-one, based on the anticancer bioactive molecule Xanthohumol, which are suitable for further in vitro and in vivo studies. Their ability to create stable complexes with the antiapoptotic X-linked IAP (XIAP) protein makes them promising anticancer agents. The calculations were based on ligand-based and structure-based virtual screening combined for the pharmacophore built. Additionally, the structures passed Lipinski's rule for drug use, and their reactivity was confirmed using density functional theory studies. The candidates were chosen between 10639400 compounds, and the docking protocols were evaluated using molecular dynamics simulations.

Zika virus (ZIKV) has been characterized as one of the potential pathogens and placed under future epidemic outbreaks by the WHO. However, lack of potential therapeutics can result in uncontrolled pandemic like other human pandemic viruses; therefore, prioritized effective therapeutics development has been recommended against ZIKV. In this context, the present study adopted the strategy to explore the lead compounds from Azadirachta indica against ZIKV via concurrent inhibition of the ZIKVpro and ZIKVRdRp proteins using molecular simulations. Initially, structure-based virtual screening of 44 bioflavonoids reported in Azadirachta indica against the crystal structures of targeted ZIKV proteins resulted in the identification of top four common bioflavonoids, viz. rutin, nicotiflorin, isoquercitrin, and hyperoside. These compounds showed substantial docking energy (-7.9 to -11.01 kcal/mol) and intermolecular interactions with essential residues of ZIKVpro (His51, Asp74, and Ser135) and ZIKVRdRp (Asp540, Ile799, and Asp665) by comparison to the reference compounds, O7N inhibitor (ZIKVpro) and Sofosbuvir inhibitor (ZIKVRdRp). Long interval molecular dynamics simulation (500 ns) on the selected docked poses reveals the stability of respective docked complexes contributed by intermolecular hydrogen bonds and hydrophobic interactions. The predicted complex stability was further supported by calculated end-point binding free energy using molecular mechanics generalized born surface area (MM/GBSA) method. Consequently, the identified common bioflavonoids are recommended as promising therapeutic inhibitors of ZIKVpro and ZIKVRdRp for further experimental assessment.

The main purpose of this study was to determine the size and direction of the seasonal dynamics of organic carbon (Сmicro) and nitrogen (Nmicro) biomass of microorganisms and microbial index (Cmicro : Corg) of natural and agrocenoses with their different uses. Field research methods involved taking of soil samples in 0-10-, 10-20- and 20-40 сm layers. Under laboratory conditions, the content of total soil carbon was determined by dry oxygen combustion on a Vario EL III analyzer (Elementar Analyzensysteme, Hanau, Germany). The carbon content of microbial biomass (Сmicro) was determined by chloroform fumigation extraction method (CFE). To freshly taken soil samples (2 hours) and soil samples after their 24-hour fumigation with chloroform vapors, 0.5 M K2SO4 was added to extract biomass lysis products of soil microorganisms. The content of organic carbon and nitrogen in the biomass of microorganisms in the obtained filtrates was determined on the Elementar Liqui TOC II, Analyzensysteme GmbH, Germany. The carbon content of microbial biomass was calculated from the difference between carbon in fumigated and control samples using a factor of 0,45 - for carbon and 0,54 – for nitrogen. The microbial index of soils was determined by the ratio between the carbon of microorganisms and the total organic carbon of the soil – Cmicro : Corg • 100 (%). Average values and confidence intervals were determined for each defined indicator. The Bonferoni method was used to correct the errors of multiple comparative samples of a one-way ANOVA analyze. K. Pearson’s linear correlation analysis was used to establish the relationships between the dynamics of carbon biomass of microorganisms and organic carbon of the soil during the growing season. Our research has shown the dynamics of Сmicro, Nmicro, Сmicro : Nmicro and Cmicro : Corg during the growing season. Analysis of the box plot showed the largest amplitude of Сmicro changes in the upper 0-10 cm layer of izogumusol. The smallest difference in the quartile range (IQR0,25-0,75) was for no-till and overhang (Ab) in the upper 0-10-, no-till (NT) and fallow (F) - in the layer 10-20- and plowing (CT) - in a layer of 20-40 cm. The content of organic carbon biomass of microorganisms in the upper layer of izogumusol at the beginning of the growing season had the highest values of Ab (577,79  1,64 mg/kg), NT (485,43  1,97 mg/kg) and CT (470,43  0,77 mg/kg), the smallest - for F (370,15  2,18 mg/kg). The content of Nmicro during this period decreased from Ab to Comb (combined tillage), NT, CT, Rot (rotary tillage), RT (reduced (ridge) tillage) and F, respectively. In the 20-40 cm layer, the highest values of Сmicro and Nmicro were observed in mid-July. The lowest values of Сmicro and Nmicro and the largest – Сmicro : Nmicro were found in late August for all variants and layers of the study. The dynamics of the microbial index resembled the trends of Сmicro and Nmicro. The largest share of Smicro in Sorghum during the growing season, on average was: - Ab (1,82  1,85 %) and NT (1,66  1,52 %) - in the layer 0-10-, - Ab (1,23  1,27 %) and NT (1,29  1,32 %) - in the layer 10-20- and - Ab (1,19  1,09 %) and F (1,11  1,077 %) - in a layer of 20-40 cm. Different use of izogumusol affected the amplitude of seasonal changes of Сmicro and Nmicro and did not affect on their direction. The maximum content of Сmicro and Nmicro was observed at the beginning of the growing season - in a layer of 0-10 cm and in mid-July - in a layer of 20-40 cm, the minimum - at the end of the summer period. During this period, the widest ratio of Сmicro : Nmicro was for F and CT - in the layer 0-20 cm and CT and Rot - in the layer 20-40 cm. The Pearson’s correlation coefficient between Сmicro and Corg increased from the upper 0-10- to the lower 20-40 cm layer of izogumusol. "Strong" and "high" negative correlations have been established between Сmicro and Corg, but no pattern has been found between the correlation coefficient and tillage technologies.

Sub-Saharan social-ecological systems are undergoing changes in environmental conditions, including modifications in rainfall pattern and biodiversity loss. Consequences of such changes depend on complex causal chains which call for integrated management strategies whose efficiency could benefit from ecosystem dynamic modelling. However, ecosystem models often require lots of quantitative information for estimating parameters, which is often unavailable. Alternatively, qualitative modelling frameworks have proved useful for explaining ecosystem response to perturbations, while requiring fewer information and providing more general predictions. However, current qualitative methods have some shortcomings which may limit their utility for specific issues. In this paper, we propose the Ecological Discrete-Event Network (EDEN), an innovative qualitative dynamic modelling framework based on "if-then" rules which generates many alternative event sequences (trajectories). Based on expert knowledge, observations and literature, we use this framework to assess the effect of permanent changes in surface water and herbivores diversity on vegetation and socio-economic transitions in an East African savanna. Results show that water availability drives changes in vegetation and socio-economic transitions, while herbivore functional groups had highly contrasted effects depending on the group. This first use of EDEN in a savanna context is promising for bridging expert knowledge and ecosystem modelling.

Heavy metal contamination of drinking water is a public health concern that requires the development of more efficient bioremediation techniques. Absorption technologies, including biosorption, provide opportunities for improvements to increase the diversity of metal ions removed and overall binding capacity. Microorganisms are a key component in wastewater treatment plants and they naturally bind metal ions through surface macromolecules but with limited capacity. The long-term goal of this work is to engineer capsule polymerases to synthesize molecules with novel functionalities. In previously published work, we showed that the Neisseria meningitidis serogroup W (NmW) galactose-sialic acid (Gal—NeuNAc) heteropolysaccharide binds lead effectively, thereby demonstrating the potential for using this capsular polysaccharide in environmental decontamination applications. In this study, computational analysis of the NmW capsule polymerase galactosyltransferase (GT) domain was used to gain insight into how the enzyme could be modified to enable the synthesis N-acetylgalactosamine-sialic acid (GalNAc—NeuNAc) heteropolysaccharide. Various computational approaches, including molecular modeling with I-TASSER and molecular dynamics simulations (MD) with NAMD, were utilized to identify key amino acid residues in the substrate binding pocket of the GT domain that may be key to conferring UDP-GalNAc specificity. Through these combined strategies and using BshA, a UDP-GlcNAc transferase, as a structural template, several NmW active site residues were identified as mutational targets to accommodate the proposed N-acetyl group in UDP-GalNAc. Thus, a rational approach for potentially conferring new properties to bacterial capsular polysaccharides is demonstrated.

There must exist a reformulation of quantum field theory which does not refer to classical time. We propose a pre-quantum, pre-spacetime theory, which is a matrix-valued Lagrangian dynamics for gravity, Yang-Mills fields, and fermions. The definition of spin in this theory leads us to an eight dimensional octonionic space-time. The algebra of the octonions reveals the standard model; model parameters are determined by roots of the cubic characteristic equation of the exceptional Jordan algebra. We derive the asymptotic low energy value 1/137 of the fine structure constant, and predict the existence of universally interacting spin one Lorentz bosons, which replace the hypothesised graviton. Gravity is not to be quantized, but is an emergent four-dimensional classical phenomenon, precipitated by the spontaneous localisation of highly entangled fermions.

In the current work, in continuation of our recent research [1] we synthesized and studied new chimeric compounds comprising the ribosome-targeting antibiotic chloramphenicol (CHL) and the membrane-penetrating cation triphenylphosphonium (TPP) connected by alkyl linkers of different lengths. Using various biochemical assays, we showed that these CAM-Cn-TPP compounds bind to the bacterial ribosome, inhibit protein synthesis in vitro and in vivo in a way similar to that of the parent CHL, and significantly decrease membrane potential. Similar to CAM-C4-TPP, the mode of action of CAM-C10-TPP and CAM-C14-TPP on bacterial ribosomes differ from that of CHL. By simulating the dynamics of complexes of CAM-Cn-TPP with bacterial ribosomes, we have proposed a possible explanation for the specificity of the action of these analogs on the translation process. CAM-C10-TPP and CAM-C14-TPP stronger inhibit the growth of the Gram-positive bacteria in comparison to the CHL and suppress some strains of CHL-resistant bacteria. Thus, we have shown that TPP derivatives of CHL are dual-acting compounds that target the ribosomes and the cellular membranes of bacteria. The TPP fragment of CAM-Cn-TPP compounds contributes to the inhibitory effect on bacteria. Moreover, since the mitochondria of eukaryotic cells have qualities similar to those of their prokaryotic ancestors, we demonstrate the possibility of targeting chemoresistant cancer cells with these compounds.

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and the third-leading cause of cancer-related mortality. Currently, the global burden of nonalcoholic fatty liver disease (NAFLD) has dramatically overcome both viral and alcohol hepatitis thus becoming the main cause of HCC incidence. NAFLD pathogenesis is severely influenced by lifestyle and genetic predisposition. Mitochondria are highly dynamic organelles which may adapt in response to environment, genetics and epigenetics in the liver (“mitochondrial plasticity”). Mounting evidence highlighted that mitochondrial dysfunction due to loss of mitochondrial flexibility, may arise before overt NAFLD and since the early stages of liver injury. Mitochondrial failure not only promotes hepatocellular damage, but also release signals (mito-DAMPs) which trigger inflammation and fibrosis, generating an adverse microenvironment in which several hepatocytes select anti-apoptotic programs and mutations that may allow survival and proliferation. Furthermore, one of the key events in malignant hepatocytes is represented by remodeling of glucidic-lipidic metabolism combined to reprogramming of mitochondrial functions, optimized to deal with energy demand. In sum, this review will discuss how mitochondrial defects may be translated into causative explanations of NAFLD-driven HCC, emphasizing future directions for research purposes and for development of potential preventive or curative strategies.

Spatiotemporal dynamics of the atmospheric kinetic energy and its components caused by the ordered and turbulent motions of air masses are estimated from minisodar measurements of three velocity vector components and their variances within the lowest 5–200 m layer of the atmosphere, with a particular emphasis on the turbulent kinetic energy. The layered structure of the total atmospheric kinetic energy has been established. From the diurnal hourly dynamics of the altitude profiles of the turbulent kinetic energy (TKE) retrieved from minisodar data, four layers are established by the character of the altitude TKE dependence, namely, the near-ground layer, the surface layer, the layer with a linear TKE increase, and the transitive layer above. In the first layer, the most significant changes of the ТКЕ were observed in the evening hours. In the second layer, no significant changes in the TKE values were observed. A linear increase in the TKE values with altitude was observed in the third layer. In the fourth layer, the TKE slightly increased with altitude and exhibited variations during the entire observation period. The altitudes of the upper boundaries of these layers depended on the time of day. The MKE values were much less than the corresponding TKE values, they did not exceed 50 m²/s². From two to four MKE layers were distinguished based on the character of its altitude dependence. The two-layer structures were observed in the evening and at night (under conditions of the stable atmospheric boundary layer). In the morning and daytime, the four-layer MKE structures with intermediate layers of linear increase and subsequent decrease in the MKE values were observed. Our estimates demonstrated that the ТКЕ contribution to the total atmospheric kinetic energy considerably (by a factor of 2.5–3) exceeded the corresponding МКЕ contribution.

There is a misconception about using the terms photon and electron. When the electron of the outer ring in the silicon atom executes interstate dynamics for only one cycle, it generates force and energy for the unit photon. The unit photon has a shape similar to a Gaussian distribution with turned ends. When a photon of suitable length interacts with the side of the laterally orientated electron of a semisolid or solid atom, it converts into heat. At an approximate angle of 90°, when a photon interacts with the tip of a laterally orientated electron, it divides into bits of energy with shapes similar to integral symbols. Solid or semisolid element atoms can reveal the phenomenon of heat energy if their electrons address the interactions of photons. In the neutral state silicon atom, the center acts as the reference point for electrons executing interstate dynamics, and the north-south tips of the electrons remain along the north-south poles. The energy shapes around the force tracing along the trajectory of electron dynamics. Two forces are exerted on the electron at one time. In interstate dynamics, the electron of the outer ring first reaches the maximum limit point, where the one-bit energy is shaped. In the remaining half cycle, that electron also generates energy of one bit. When there is an uninterrupted supply of heat energy to the silicon atom, electron dynamics generate photons with a shape-like wave. Path-independent but interstate-dependent forces assume the control of an electron. This electron executes dynamics nearly at the speed of light. In dynamics, conservative forces are exerted on position-acquiring electrons. A photon can be unending in length if the electron dynamics remain uninterrupted. The changing aspect of the electron reflects the auxiliary moment of inertia at each turning point. Atoms of suitable elements generate differently shaped photons when executing dynamics for the outer ring electrons. Thus, they can also reveal the phenomenon of photon energy.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pandemic. Prevention and control strategies require an improved understanding of SARS-CoV-2 dynamics. We did a rapid review of the literature on SARS-CoV-2 viral dynamics with a focus on infective dose. We sought comparisons of SARS-CoV-2 with other respiratory viruses including SARS-CoV-1 and MERS-CoV. We examined laboratory animal, and human studies. The literature on infective dose, transmission, and routes of exposure was limited specially in humans, and varying endpoints were used for measurement of infection. We propose the minimum infective dose of COVID-19 in humans, is higher than 100 particles, possibly slightly lower than the 700 particles estimated for H1N1 influenza. Despite variability in animal studies, there was some evidence that increased dose at exposure correlated with higher viral load clinically, and severer symptoms. Higher viral load measures did not reflect COVID-19 severity. Aerosol transmission seemed to raise the risk of more severe respiratory complications in animals. An accurate quantitative estimate of the infective dose of SARS-CoV-2 in humans is not currently feasible and needs further research. Further work is also required on the relationship between routes of transmission, infective dose, co-infection, and outcomes.

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

Streptococcus mutans is well known for having virulence factors associated with its cariogenic role, such as glucosyltransferases, which have been used as targets for the virtual screening of molecules with inhibitory capacity. The Antigen I/II of S. mutans is involved in the adhesion to the surface of the tooth and the bacterial co-aggregation in the biofilm formation, despite that, this protein has not been used as a target in a virtual strategy search for inhibitors. In this study we identified in silico and evaluated in vitro molecules with adhesion inhibitory potential on S. mutans Ag I/II. A virtual screening of 883,551 molecules was conducted, cytotoxicity analysis on fibroblast cells, S. mutans adhesion studies, scanning electron microscopy analysis for bacterial integrity, and molecular dynamics simulation were also performed. We have found three molecules (ZI-187, ZI-939, ZI-906) that were not cytotoxic and inhibited the adhesion of S. mutans to polystyrene microplates. Molecular dynamic simulation by 300 nanoseconds showed stability of the interaction between ZI-187 and Ag I/II (PDB: 3IPK). This work provides three new molecules that targets Ag I/II and have the capacity to inhibit in vitro the S. mutans adhesion on polystyrene microplates and provides a new computational line for the search and selection of safe inhibitory molecules against different pathogens.

Contemporary climate change is exposing plant populations to novel combinations of temperatures, drought stress, [CO₂] and other abiotic and biotic conditions. These changes are rapidly disrupting the evolutionary dynamics of plants. Despite the multifactorial nature of climate change, most studies typically manipulate only one climatic factor. In this opinion piece, we seek to explore how climate change factors interact with each other and with biotic pressures to alter evolutionary processes. We first explore the ramifications of climate change for key life history stages (germination, growth and reproduction). We then examine how mating system variation influences population persistence under rapid environmental change and propose that mixed mating could be advantageous in future climates. Furthermore, we discuss how spatial and temporal mismatches between plants and their mutualists and antagonists could promote or constrain adaptive responses to climate change. For example, plant-virus interactions vary from highly pathogenic to mildly facilitative, and are partly mediated by temperature, moisture availability and [CO₂]. Will host plants exposed to novel, stressful abiotic conditions be more susceptible to viral pathogens? Finally, we propose novel experimental approaches that could illuminate how plants will cope with unprecedented global change, such as resurrection studies combined with experimental evolution, genomics or epigenetics.

Room-temperature phosphorescent (RTP) materials have been attracted tremendous interest owing to their unique material characteristics and potential applications for state-of-the-art optoelectronic devices. Recently, we have reported a synthesis and fundamental photophysical properties of new RTP materials based on benzil, i.e., fluorinated monobenzil derivative and fluorinated and non-fluorinated bisbenzil derivative analogues [Yamada, S. et al, Beilstein J. Org. Chem. 2020, 16, 1154–1162.]. To further understand their RTP properties, here we investigated the excited-state dynamics and photostability of the derivatives by means of time-resolved and steady-state photoluminescence spectroscopies. For these derivatives, clear RTP emissions with lifetimes on the microsecond timescale were identified. Among them, the monobenzil derivative was found to be the most efficient RTP material, showing both the longest lifetime and highest amplitude RTP emission. Time-resolved photoluminescence spectra measured at 77 K and density functional theory calculations revealed the existence of a second excited triplet state in the vicinity of the first excited singlet state for the monobenzil derivative, indicative of the presence of a fast intersystem crossing pathway. A discussion of the correlation between the excited state dynamics, emission properties, and conformational flexibility of the three derivatives is presented.

Objective: The objective of this study is to determine the epidemic dynamics and clinical features of COVID-19 in southern Hainan Island, China, and provide experience for other tropical areas of the world. Methods: This retrospective study included confirmed cases of COVID-19 in southern Hainan. All enrolled patients were treated in Sanya, and data on epidemiological and clinical features of the disease and infection prevention and control measures adopted by the local government during the epidemic were collected. Results: Of the 74 cases, 71 (95.95%) were imported from Wuhan, Hubei Province (47, 63.51%), other cities in Hubei Province (11, 14.86%), or provinces other than Hubei and Hainan (13, 17.57%). Three (4.06%) patients were infected in southern Hainan, including one autochthonous case in Sanya. Fifty-four cases (72.97%) were detected in Sanya, and 27 cases (27.03%) were diagnosed in other cities. The rate of severe or critical cases was 28.38% (21/74), and mortality was 2.7% (2/74). The serum lactate levels and base excess of severe-critical patients were higher than those of patients with mild-moderate disease. Multivariate logistic regression analysis showed that chronic conditions were risk factors for severe and critical COVID-19. Seventy-four patients were diagnosed with COVID-19 over a 22-day period in Sanya, and the epidemic period in the city was 48 days. The outbreak was controlled rapidly because the local government adopted strict infection prevention and control measures. Conclusions: The clinical characteristics of COVID-19 in Hainan Island were similar to those reported in other regions. In Sanya, the rate of severe and very severe cases was higher than in other regions; however, most cases were imported, and there was only one autochthonous case. The rapid control of the outbreak in Sanya may be related to the tropical climate, adoption of strict infection prevention and control measures, daily reporting of new cases, increased public awareness about the epidemic, and other emergency actions implemented by the local government.

An important stage in SARS-CoV-2 life cycle is the fusion of spike(S) protein with the ACE2 host-cell receptor. Therefore, to explore conserved features in S protein dynamics and to identify potentially novel regions for drugging, we measured variability derived from 791 viral genomes and studied its properties by MD simulation. The findings indicated that S2 subunit (HR1, CH, and CD domains) showed low variability, low fluctuations in MD, and displayed a trimer cavity. By contrast, the RBD domain, which is typically targeted in drug discovery programmes, exhibits more sequence variability and flexibility. Interpretations from MD suggest that the monomer is in constant motion showing transitions up-to-down state, and the trimer cavity may function as a 'bouncing spring' that may facilitates S protein interactions with ACE2. Feasibility of trimer cavity for potential drug target was examined by SBVS screening. Several hits that have already been validated or suggested to inhibit the SARS-CoV-2 virus in cell systems were identified; in particular, the data suggest an action mechanism for such molecules including Chitosan and macrolide types. These findings identify a novel binding-site formed by the S protein, that might assist in future drug discovery programmes aimed at targeting the CoV family of viruses.

The hybrid bond graph has been studied in depth for scalar bond graphs, but how does this translate to the multi-bond graph? Here, the controlled junction – used to model structural switching such as contact – is extended to the multi-bond case. This is a simple process, assuming that all bonds switch simultaneously (which makes physical sense). A controlled 0-junction is applied to multi-bond graph of a car, which can lose contact with the ground in cornering. Dynamic causality features, but this can be accommodated using an equational submodel in 20-Sim (in a manner similar to that used with scalar bond graphs). The junction is proposed for subsequent work to develop a validated multi-body dynamics car model in cornering.

The global pandemic caused by the new SARS-COV-2 coronavirus makes it necessary to search for drugs for its control. Within of this research it has been known that the ivermectin drug, a FDA-approved drugs which is formulated as an 80:20 mixture of ivermectin B1a and B1b and used commonly for parasitic infections, has an inhibitory effect on viruses, includes SARS-COV-2 at in vitro level. In the particular case of SARS-COV-2 its mechanism of action remains elusive and controversial. Interestingly, the energy of interaction of ivermectin with any of the proteins the SARS-CoV-2 and the possible structural alterations at the protein level that this drug can cause have not been reported. In this sense, we carried out a bioinformatics study with docking strategies and molecular dynamics to predict the binding and disturbance induced by ivermectin in proteins associated with SARS-CoV-2. We use DockThor and Molegro docking scores. The DockThor server and myPresto software were used to build complexes and dynamics studies, respectively. The results obtained suggested that ivermectin is capable of docking with the 3CL protease and the HR2 domain, and may promote structural changes in these proteins by inducing unfolding/folding. Specifically, ivermectin brings protease to a significantly more deployed conformational state and the HR2 domain to a more compact state compared to the native state. Finally, it is shown that B1a and B1b macrocyclic lactones have a behavior different from to each target protein. These results suggest a possible inhibitory effect against SARS-CoV-2 due to a synergistic role of this drug to spontaneously bind to two important proteins involve in the proliferation of this virus. However, more studies are required on this possible mechanism of action.

We propose a Gauss model (GM), a map from time to the bell-shaped Gauss function to model the deaths per day and country, as a quick and simple model to make predictions on the coronavirus epidemic. Justified by the sigmoidal nature of a pandemic, i.e. initial exponential spread to eventual saturation, we apply the GM to existing data, as of April 2, 2020, from 25 countries during first corona pandemic wave and study the model's predictions. We find that logarithmic daily fatalities caused by Covid-19 are well described by a quadratic function in time. By fitting the data to second order polynomials from a statistical chi2-fit with 95\% confidence, we are able to obtain the characteristic parameters of the GM, i.e. a width, peak height and time of peak, for each country separately, with which we extrapolate to future times to make predictions. We provide evidence that this supposedly oversimplifying model might still have predictive power and use it to forecast the further course of the fatalities caused by Covid-19 per country, including peak number of deaths per day, date of peak, and duration within most deaths occur. While our main goal is to present the general idea of the simple modeling process using GMs, we also describe possible estimates for the number of required respiratory machines and the duration left until the number of infected will be significantly reduced.

The current outbreak of coronavirus disease (COVID-19) caused by SARS-CoV-2 in Wuhan, China has killed more than 2600 people since December 2019. Currently there is no effective treatment for this epidemic. Drug for anti SARS-CoV-2 are urgently needed. In this study we evaluated two compound libraries containing launched drugs and compounds from 300 kinds of Traditional Chinese Medicine in order to find anti SARS-CoV-2 drugs. Docking and then calculating binding free energy were performed as workflow against four key anti-SARS-CoV-2 drug targets, 3CLpro, PLpro and RdRp from SARSCoV-2, and AAK1 from human as well. As a result, drugs launched with potential for antiviral usage were selected in the hope of providing some knowledge for future drug discovery.