Single-crystal elastic constants of magnesium difluoride (MgF2) to 7.4 GPa

The six independent elastic constants (C₁₁, C₁₂, C₁₃, C₃₃, C₄₄, and C₆₆) of single-crystal MgF₂ in the rutile structure have been measured by Brillouin spectroscopy at room temperature from ambient conditions to 7.4 GPa. Measurements were performed on two monocrystals with perpendicular faces, (001) and (100). A quasi-linear fit from finite strain theory was applied to the experimental data revealing the pressure dependence of the six elastic constants of MgF₂. The shear modulus C_S=1/2(C₁₁−C₁₂), and the aggregate shear (Voigt–Reuss–Hill) modulus G show a softening with increasing pressure, indicating the approach of the rutile-to-CaCl₂-type structural phase transition at P~9 GPa. The adiabatic bulk modulus (Reuss average) and its pressure derivative have been determined: K_0S=105.1±0.3 GPa, (∂K_0S/∂P)_T=4.14±0.05. The pressure–volume equation of state of MgF₂ was computed self-consistently from the Brillouin data. Our results are in good agreement with X-ray diffraction data. As the phase transition is approached, MgF₂ becomes strongly anisotropic and develops partially auxetic behavior (a negative Poisson's ratio in certain directions).     

VOF simulations of the contact angle dynamics during the drop spreading: Standard models and a new wetting force model

Introduction

In this study,a novel numerical implementation for the adhesion of liquid droplets impacting normally on solid dry surfaces is presented. The advantage of this new approach, compared to the majority of existing models, is that the dynamic contact angle forming during the surface wetting process is not inserted as a boundary condition, but is derived implicitly by the induced fluid flow characteristics (interface shape) and the adhesion physics of the gas–liquid-surface interface (triple line), starting only from the advancing and receding equilibrium contact angles. These angles are required in order to define the wetting properties of liquid phases when interacting with a solid surface.

Methodology

The physical model is implemented as a source term in the momentum equation of a Navier-Stokes CFD flow solver as an “adhesion-like” force which acts at the triple-phase contact line as a result of capillary interactions between the liquid drop and the solid substrate. The numerical simulations capture the liquid–air interface movement by considering the volume of fluid (VOF) method and utilizing an automatic local grid refinement technique in order to increase the accuracy of the predictions at the area of interest, and simultaneously minimize numerical diffusion of the interface.

Results

The proposed model is validated against previously reported experimental data of normal impingement of water droplets on dry surfaces at room temperature. A wide range of impact velocities, i.e. Weber numbers from as low as 0.2 up to 117, both for hydrophilic (θ_adv = 10° – 70°) and hydrophobic (θ_adv = 105° – 120°) surfaces, has been examined. Predictions include in addition to droplet spreading dynamics, the estimation of the dynamic contact angle; the latter is found in reasonable agreement against available experimental measurements.

Conclusion

It is thus concluded that theimplementation of this model is an effective approach for overcoming the need of a pre-defined dynamic contact angle law, frequently adopted as an approximate boundary condition for such simulations. Clearly, this model is mostly influential during the spreading phase for the cases of low We number impacts (We < ˜80) since for high impact velocities, inertia dominates significantly over capillary forces in the initial phase of spreading.     

A comparison of three random disciplines

Consider a general system (or subsystem) with a single queue. In this context, we compare three different disciplines:ROS (Random Order of Service),RI (Random Insertion), andRAP (Randomly Assigned Priorities). The first of these (ROS) is a classical discipline; the other two are introduced in this paper. It turns out that the waiting time distributions for two of these disciplines are exactly the same, while the third discipline has strikingly different characteristics.Work done by this author while he was with IBM Zurich Research Laboratory.     

Therapeutic Intervention of COVID-19 by Natural Products: A Population-Specific Survey Directed Approach

To date very few promising leads from natural products (NP) secondary metabolites with antiviral and immunomodulatory properties have been identified for promising/potential intervention for COVID-19. Using in-silico docking studies and genome based various molecular targets, and their in vitro anti-SARS CoV-2 activities against whole cell and/or selected protein targets, we select a few compounds of interest, which can be used as potential leads to counteract effects of uncontrolled innate immune responses, in particular those related to the cytokine storm. A critical factor for prevention and treatment of SARS-CoV-2 infection relates to factors independent of viral infection or host response. They include population-related variables such as concurrent comorbidities and genetic factors critically relevant to COVID-19 health disparities. We discuss population risk factors related to SARS-CoV-2. In addition, we focus on virulence related to glucose-6-phosphate dehydrogenase deficiency (G6PDd), the most common human enzymopathy. Review of data on the response of individuals and communities with high prevalence of G6PDd to NP, prompts us to propose the rationale for a population-specific management approach to rationalize design of therapeutic interventions of SARS-CoV-2 infection, based on use of NP. This strategy may lead to personalized approaches and improve disease-related outcomes.     

Shall I Work with Them? A Knowledge Graph-Based Approach for Predicting Future Research Collaborations

We consider the prediction of future research collaborations as a link prediction problem applied on a scientific knowledge graph. To the best of our knowledge, this is the first work on the prediction of future research collaborations that combines structural and textual information of a scientific knowledge graph through a purposeful integration of graph algorithms and natural language processing techniques. Our work: (i) investigates whether the integration of unstructured textual data into a single knowledge graph affects the performance of a link prediction model, (ii) studies the effect of previously proposed graph kernels based approaches on the performance of an ML model, as far as the link prediction problem is concerned, and (iii) proposes a three-phase pipeline that enables the exploitation of structural and textual information, as well as of pre-trained word embeddings. We benchmark the proposed approach against classical link prediction algorithms using accuracy, recall, and precision as our performance metrics. Finally, we empirically test our approach through various feature combinations with respect to the link prediction problem. Our experimentations with the new COVID-19 Open Research Dataset demonstrate a significant improvement of the abovementioned performance metrics in the prediction of future research collaborations.     

Structural parameters of the ground states of the quasi‐stable diatomic anions CO−, BF−, and BCl− as obtained by conventional Ab Initio methods

The experimental electron affinity (EA) of CO(X¹Σ⁺) is ?1.5 eV, signifying the metastability of the CO^?(X²Π) anion. The electronic structure and bonding of CO^?, BF^?, and BCl^? vis‐à‐vis their neutral counterparts have been studied by conventional coupled‐cluster (CCSD(T)) and multireference (MRCI) methods. Our results are in agreement with experiment for the CO/CO^? system, indicating as well the metastable nature of the BF^?(X²Π) and BCl^?(X²Π) anions, their MRCI EAs being ?0.8 ± 0.1 and ?0.3 ± 0.1 eV, respectively. Our work clearly shows the usefulness of stationary state ab initio methods to the elucidation of metastable species. © 2015 Wiley Periodicals, Inc.     

Singlet Fission in Pyrene-Fused Azaacene Dimers

Singlet fission has emerged as a promising strategy to avoid the loss of extra energy through thermalization in solar cells. A family of dimers consisting of nitrogen-doped pyrene-fused acenes that undergo singlet fission with triplet quantum yields as high as 125 % are presented. They provide new perspectives for nitrogenated polycyclic aromatic hydrocarbons and for the design of new materials for singlet fission.     

Antiparasitic and antimicrobial isoflavanquinones from Abrus schimperi

The EtOH extract of Abrus schimperi (Fabaceae), collected in Kenya, demonstrated significant activity against Leishmania donovani promastigotes with IC50 value of 3.6 microg/mL. Bioassay-guided fractionation of CHCl3 fraction using Centrifugal Preparative TLC afforded two antiparasitic isoflavanquinones, namely amorphaquinone (1) and pendulone (2). They displayed IC50 values of 0.63 microg/mL and 0.43 microg/mL, respectively, against L. donovani promastigotes. Both the compounds were also evaluated against L. donovani axenic amastigotes and amastigotes in THPI macrophage cultures. In addition, compounds 1 and 2 showed antiplasmodial activity against Plasmodium falciparum D6 and W2 strains, while 2 displayed antibacterial activity against Staphylococcus aureus and methicillin-resistant S. aureus (each IC50 1.44 microg/mL). The 1H and 13C data of 1, not fully assigned previously, were unambiguously assigned using 1D and 2D NMR HMBC and HMQC experiments. In addition, the absolute stereochemistry of the isolated compounds 1 and 2 was revised as C-(3S) based on Circular Dichroism experiments. This appears to be the first report of amorphaquinone (1) and pendulone (2) from the genus Abrus.