AA-cation control of magnetoelectric quadrupole order in AA(TiO)Cu4_4(PO4_4)4_4 (AA = Ba, Sr, and Pb)

Ferroic magnetic quadrupole order exhibiting macroscopic magnetoelectric activity is discovered in the novel compound $A$(TiO)Cu$_4$(PO$_4$)$_4$ with $A$ = Pb, which is in contrast with antiferroic quadrupole order observed in the isostructural compounds with $A$ = Ba and Sr. Unlike the famous lone-pair stereochemical activity which often triggers ferroelectricity as in PbTiO$_3$, the Pb$^{2+}$ cation in Pb(TiO)Cu$_4$(PO$_4$)$_4$ is stereochemically inactive but dramatically alters specific magnetic interactions and consequently switches the quadrupole order from antiferroic to ferroic. Our first-principles calculations uncover a positive correlation between the degree of $A$-O bond covalency and a stability of the ferroic quadrupole order.Comment: 7 pages, 4 figure

Clinical Outcomes in Men and Women following Total Knee Arthroplasty with a High-Flex Knee: No Clinical Effect of Gender

While it is generally recognized that anatomical differences exist between the male and female knee, the literature generally refutes the clinical need for gender-specific total knee prostheses. It has been found that standard, unisex knees perform as well, or better, in women than men. Recently, high-flex knees have become available that mechanically accommodate increased flexion yet no studies have directly compared the outcomes of these devices in men and women to see if gender-based differences exist. We retrospectively compared the performance of the high-flex Vanguard knee (Biomet, Warsaw, IN) in 716 male and 1,069 female knees. Kaplan-Meier survivorship was 98.5% at 5.6–5.7 years for both genders. After 2 years, mean improvements in Knee Society Knee and Function scores for men and women (50.9 versus 46.3; 26.5 versus 23.1) and corresponding SF-12 Mental and Physical scores (0.2 versus 2.2; 13.7 versus 12.2) were similar with differences not clinically relevant. Postoperative motion gains as a function of preoperative motion level were virtually identical in men and women. This further confirms the suitability of unisex total knee prostheses for both men and women

Study Of Inertia And Stoichiometric Effect On Surface Diffusion By Monte Carlo Method

In this work, we investigate the inertia and stoichiometric effect on surface diffusion of adsorbates particles. The study is done by means of Monte-Carlo simulation in the framework of the lattice gas model. Only first neighboring repulsive pair interaction is considered. We concentrate on the behaviour of the tracer diffusion coefficient Dt(θ), as a function of surface coverage θ in the case where two type of particles A and B are adsorbed. A and B are only different by their mass. The results shows that θt ordering phenomenon is not strongly influenced. However the diffusion process is decreased by inclusion of heavy particles.w.In this work, we investigate the inertia and stoichiometric effect on surface diffusion of adsorbates particles. The study is done by means of Monte-Carlo simulation in the framework of the lattice gas model. Only first neighboring repulsive pair interaction is considered. We concentrate on the behaviour of the tracer diffusion coefficient Dt(θ), as a function of surface coverage θ in the case where two type of particles A and B are adsorbed. A and B are only different by their mass. The results shows that θt ordering phenomenon is not strongly influenced. However the diffusion process is decreased by inclusion of heavy particles.w

Phase-field modelling of dendritic growth behaviour towards the cooling / heating of pure nickel

We are interested in modelling the dendritic growth occurring during the solidification process of a pure material and especially to see the effect of the cooling / heating on the growth behaviour of this dendrite. For this purpose we use a phase-field model. The obtained partial differential equations are solved numerically by a finite difference method. In order to appreciate the shape of the resulting dendrites we expose some figures obtained from simulations in 2D.We are interested in modelling the dendritic growth occurring during the solidification process of a pure material and especially to see the effect of the cooling / heating on the growth behaviour of this dendrite. For this purpose we use a phase-field model. The obtained partial differential equations are solved numerically by a finite difference method. In order to appreciate the shape of the resulting dendrites we expose some figures obtained from simulations in 2D

Data-Driven Models for studying the Dynamics of the COVID-19 Pandemics

This paper seeks to study the evolution of the COVID-19 pandemic based on daily published data from Worldometer website, using a time-dependent SIR model. Our findings indicate that this model fits well such data, for different chosen periods and different regions. This well-known model, consisting of three disjoint compartments, susceptible , infected , and removed , depends in our case on two time dependent parameters, the infection rate $\beta(t)$ and the removal rate $\rho(t)$. After deriving the model, we prove the local exponential behavior of the number of infected people, be it growth or decay. Furthermore, we extract a time dependent replacement factor $\sigma_s(t) ={\beta(t)}s(t)/{\rho(t) }$, where $s(t)$ is the ratio of susceptible people at time $t$. In addition, $i(t)$ and $r(t)$ are respectively the ratios of infected and removed people, based on a population of size $N$, usually assumed to be constant. Besides these theoretical results, the report provides simulations on the daily data obtained for Germany, Italy, and the entire World, as collected from Worldometer over the period stretching from April 2020 to June 2022. The computational model consists of the estimation of $\beta(t)$, $\rho(t)$ and $s(t)$ based on the time-dependent SIR model. The validation of our approach is demonstrated by comparing the profiles of the collected $i(t), r(t)$ data and those obtained from the SIR model with the approximated parameters. We also consider matching the data with a constant-coefficient SIR model, which seems to be working only for short periods. Thus, such model helps understanding and predicting the evolution of the pandemics for short periods of time where no radical change occurs.Comment: 59 page