Magnetic Domain Wall Motion: Numerical Simulation and Collective Coordinate Modeling

Manipulating magnetic domain walls in nanostructures has been linked with applications in spintronic logic, sensing and storage devices. Recent studies of domain wall motion have focused on perpendicular magnetic anisotropy heterostructures of ultrathin ferromagnets sandwiched between a heavy metal layer and an oxide, in which spin-orbit coupling and broken inversion symmetry can dominate domain wall motion. Specifically, chiral domain walls are stabilized in these systems due to the Dzyaloshinskii-Moriya interaction, and current-driven domain wall motion is enhanced due to the spin Hall effect. The chirality of the domain walls in such systems may be partially influenced by the application of external in-plane magnetic fields. Such magnetic fields are used in bubble expansion experiments to assess the strength of the Dzyaloshinskii-Moriya interaction. In addition, bombarding the ferromagnetic layer with heavy metal ions can induce local changes in material properties such as magnetic anisotropy which could be used to manipulate local pinning properties. While computational micromagnetic simulations can help elucidate the behavior of domain walls, their computational cost prohibits extensive studies. As such, assessing the strength of the Dzyaloshinskii-Moriya interaction, extracting material parameters and understanding the behavior of the domain wall to an extent depends on simpler models of domain wall motion based on collective characteristics of the domain wall, and derived from applying model reduction methods to the more complex micromagnetic model. Several Lagrangian-based collective coordinate models exist to describe domain wall motion, namely the $q-\phi$, $q-\phi-\Delta$, and $q-\phi-\chi$ models. While these models can describe domain wall motion with acceptable accuracy, they fail to replicate results of micromagnetic simulations specially for domain wall motion under the application of in-plane fields in heterostructures of interest. Moreover, recent advances in domain wall motion such as pinning due to irradiation have not been included in these models. In this work, we will first present the process for developing Lagrangian-based collective coordinate models, culminating in the derivation of a four collective coordinate model for domain wall motion (the $q-\phi-\chi-\Delta$ model). We show how this model can be extended for cases where in-plane magnetic fields are present to correctly account for the physics; this extension involved introducing the canting induced by the in-plane fields in the domains. We also extend these models to describe the dynamics of magnetic bubbles. In-plane field cases are specifically studied to help identify specific conditions which could help measure properties of the magnetic material. We also compare the equations derived using our Lagrangian-based approach to another reduced model developed through the application of statistical methods to the LLG equation, shedding light on the shortcomings of our approach. The work culminates with a summary of how these models may be made more realistic, through the inclusion of pinning and thermal effects within the model

Prospective Acid Reflux Study of Iran (PARSI): Methodology and study design

<p>Abstract</p> <p>Background</p> <p>Gastroesophageal reflux disease is a common and chronic disorder but long term, prospective studies of the fate of patients seeking medical advice are scarce. This is especially prominent when looking at non-erosive reflux disease (NERD) patients.</p> <p>Methods</p> <p>We designed a prospective cohort to assess the long term outcome of GERD patients referring to gastroenterologists. Consecutive consenting patients, 15 years of age and older, presenting with symptoms suggestive of GERD referring to our outpatient clinics undergo a 30 minute interview. Upper gastrointestinal endoscopy is performed for them with protocol biopsies and blood samples are drawn. Patients are then treated according to a set protocol and followed regularly either in person or by telephone for at least 10 years.</p> <p>Discussion</p> <p>Our data show that such a study is feasible and follow-ups, which are the main concern, can be done in a fairly reliable way to collect data. The results of this study will help to clarify the course of various subgroups of GERD patients after coming to medical attention and their response to treatment considering different variables. In addition, the basic symptoms and biological database will fuel further molecular epidemiologic studies.</p

Development of Surrogates for Aviation Jet Fuels

Surrogate fuels are mixtures of pure hydrocarbons that mimic specific properties of a real fuel. The use of a small number of pure compounds in their formulation ensures that chemical composition is well controlled, helping increase reproducibility of experiments and reduce the computational cost associated with numerical modeling. In this work, surrogate mixtures were developed for Jet A fuel based on correlations between fuel properties (cetane number, smoke point, threshold sooting index (TSI), density, viscosity, boiling point and freezing point) and the nuclear magnetic resonance (NMR) spectra of the fuel as a measure of the fuel's chemical composition. Comparison of the chemical composition and target fuel properties of the surrogate fuels developed in this work to a Jet A fuel sample and other surrogate fuels proposed in the literature revealed the superiority of these surrogate fuels in mimicking the fuel properties of interest.MAS

Fuzzy stochastic Data Envelopment Analysis with application to NATO enlargement problem

Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of Decision Making Units (DMUs) with multiple deterministic inputs and multiple outputs. However, in real-world problems, the observed values of the input and output data are often vague or random. Indeed, Decision Makers (DMs) may encounter a hybrid uncertain environment where fuzziness and randomness coexist in a problem. Hence, we formulate a new DEA model to deal with fuzzy stochastic DEA models. The contributions of the present study are fivefold: (1) We formulate a deterministic linear model according to the probability–possibility approach for solving input-oriented fuzzy stochastic DEA model, (2) In contrast to the existing approach, which is infeasible for some threshold values; the proposed approach is feasible for all threshold values, (3) We apply the cross-efficiency technique to increase the discrimination power of the proposed fuzzy stochastic DEA model and to rank the efficient DMUs, (4) We solve two numerical examples to illustrate the proposed approach and to describe the effects of threshold values on the efficiency results, and (5) We present a pilot study for the NATO enlargement problem to demonstrate the applicability of the proposed model

A Note on Ranking Fuzzy Numbers with an Area Method using Circumcenter of Centroids

In this study, we show that ranking fuzzy numbers with the area method using circumcenter of centroids presented by Rao and Shankar failed to rank effectively the generalized fuzzy numbers. By proving a theorem and using some numerical examples, we demonstrate that their proposed method cannot rank consistently some fuzzy numbers or is not consistent with human intuition

A New Method for Solving Dual DEA Problems with Fuzzy Stochastic Data

Data envelopment analysis (DEA) is a widely used mathematical programming technique for measuring the relative efficiency of decision-making units which consume multiple inputs to produce multiple outputs. Although precise input and output data are fundamentally used in classical DEA models, real-life problems often involve uncertainties characterized by fuzzy and/or random input and output data. We present a new input-oriented dual DEA model with fuzzy and random input and output data and propose a deterministic equivalent model with linear constraints to solve the model. The main contributions of this paper are fourfold: (1) we extend the concept of a normal distribution for fuzzy stochastic variables and propose a DEA model for problems characterized by fuzzy stochastic variables; (2) we transform the proposed DEA model with fuzzy stochastic variables into a deterministic equivalent linear form; (3) the proposed model which is linear and always feasible can overcome the nonlinearity and infeasibility in the existing fuzzy stochastic DEA models; (4) we present a case study in the banking industry to exhibit the applicability of the proposed method and feasibility of the obtained solutions

EFFECT OF MODEST WEIGHT LOSS ON CARDIOVASCULAR INFLAMMATORY MARKERS IN OBESE WOMEN

&nbsp; Abstract INTRODUCTION: Obesity is associated with an increased risk of coronary heart disease. It is believed that adipose tissue inflammatory substances contribute to the pathogenesis of cardiovascular disease. To find out the metabolic benefits of weight loss in reducing cardiovascular risk, we assessed the effect of modest weight loss on plasma inflammatory markers in obese women. methods: In a clinical trial, 42 obese women underwent a 10 week restricted diet program. Body weight, fasting glucose, insulin, total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c) and plasma inflammatory cytokines were measured at baseline and after 10 weeks. results: Weight, BMI, fasting blood glucose, insulin, cholesterol and triglyceride had significant reductions. No significant changes were observed in HDL-c and LDL-c concentrations. All plasma inflammatory proteins improved significantly except CRP level. CONCLUSIONS: Modest weight loss (&asymp;5%) is associated with favorable changes in plasma inflammatory markers. &nbsp; &nbsp; Keywords: Obesity, weight loss, inflammatory markers, cardiovascular disease.</div

Active debris removal: overview and figures of merit of debris grabbing strategies

During the last two decades the problem of space debris and safe access to Low Earth Orbit has been one of the most controversial and discussed issue in the space community. Along with mitigation actions (e.g. the 25-year Post Mission Disposal rule currently adopted by most agencies), analyses of the current situation and future projections have shown the necessity of active debris removal (ADR) operations aimed to a direct intervention in relatively short time as a remediation action. Apart from the problem of considering the potential political and legal consequences of dealing with spent space objects, many methods have been proposed for the despinning and grabbing phases of ADR missions, but in spite of the variety in the ideas and concepts on the ground, not all of them are ready to be sent to space. Starting from an overview on the different approaches proposed for in-orbit grabbing of uncooperative targets, this work analyses the current status of the solutions designed so far, both in terms of technical readiness and methodological maturity, and identifies the characteristics that can be used as a metric for the quality and feasibility of those systems. From these figures of merit, different scenarios will be simulated to obtain additional supporting data in order to validate the results of the preliminary analyses