Spin-lattice interaction parameters from first principles: theory and implementation

A scheme is presented to calculate on a first-principles level the spin-lattice coupling (SLC) parameters needed to perform combined molecular-spin dynamics (MSD) simulations. By treating changes to the spin configuration and atomic positions on the same level, closed expressions for the atomic SLC parameters could be derived in a coherent way up to any order. The properties of the SLC parameters are discussed considering separately the symmetric and antisymmetric parts of the SLC tensor. The changes due to atomic displacements of the spin-spin exchange coupling (SSC) parameters estimated using the SLC parameters are compared with the SSC parameters calculated for an embedded cluster with the central atom displaced, demonstrating good agreement of these results. Moreover, this allows to study the impact of different SLC contributions, linear and quadratic with respect to displacements, on the properties of the modified SSC parameters. In addition, we represent an approach to calculate the site-diagonal SLC parameters characterizing local magnetic anisotropy induced by a lattice distortion, which is a counterpart of the approach based on magnetic torque used for the investigations of magneto-crystalline anisotropy (MCA) as well as for calculations of the MCA constants. In particular, the dependence of the induced magnetic torque on different types of atomic displacements is analyzed.Comment: 16 page

Dimensional structural constants from chiral and conformal bosonization of QCD

We derive the dimensional non-perturbative part of the QCD effective action for scalar and pseudoscalar meson fields by means of chiral and conformal bosonization. The related structural coupling constants L_5 and L_8 of the chiral lagrangian are estimated using general relations which are valid in a variety of chiral bosonization models without explicit reference to model parameters. The asymptotics for large scalar fields in QCD is elaborated, and model-independent constraints on dimensional coupling constants of the effective meson lagrangian are evaluated. We determine also the interaction between scalar quarkonium and the gluon density and obtain the scalar glueball-quarkonium potential.Comment: 21 pages, LaTe

Calculating spin-lattice interactions in ferro- and antiferromagnets: the role of symmetry, dimension and frustration

Recently, the interplay between spin and lattice degrees of freedom has gained a lot of attention due to its importance for various fundamental phenomena as well as for spintronic and magnonic applications. Examples are ultrafast angular momentum transfer between the spin and lattice subsystems during ultrafast demagnetization, frustration driven by structural distortions in transition metal oxides, or in acoustically driven spin-wave resonances. In this work, we provide a systematic analysis of spin-lattice interactions for ferro- and antiferromagnetic materials and focus on the role of lattice symmetries and dimensions, magnetic order, and the relevance of spin-lattice interactions for angular momentum transfer as well as magnetic frustration. For this purpose, we use a recently developed scheme which allows an efficient calculation of spin-lattice interaction tensors from first principles. In addition to that, we provide a more accurate and self consistent scheme to calculate ab initio spin lattice interactions by using embedded clusters which allows to benchmark the performance of the scheme introduced previously

Rotationally invariant formulation of spin-lattice coupling in multi-scale modeling

In the spirit of multi-scale modeling, we develop a theoretical framework for spin-lattice coupling that connects, on the one hand, to ab initio calculations of spin-lattice coupling parameters and, on the other hand, to the magneto-elastic continuum theory. The derived Hamiltonian describes a closed system of spin and lattice degrees of freedom and explicitly conserves the total momentum, angular momentum and energy. Using a new numerical implementation that corrects earlier Suzuki-Trotter decompositions we perform simulations on the basis of the resulting equations of motion to investigate the combined magnetic and mechanical motion of a ferromagnetic nanoparticle, thereby validating our developed method. In addition to the ferromagnetic resonance mode of the spin system we find another low-frequency mechanical response and a rotation of the particle according to the Einstein-de-Haas effect. The framework developed herein will enable the use of multi-scale modeling for investigating and understanding a broad range of magneto-mechanical phenomena from slow to ultrafast time scales

Back to the Future: Student Time Period Analyses

This newsletter began with the Fall 2015 Honors English class. These students were challenged to initiate research over a topic they thought was interesting and show how it related to our campus, Stephen F. Austin State University. It is our hope that this cumulative research will help readers look at SFA a little differently

Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study

Aim Gastric cancer (GC) is a tumor entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesized that GC primary tissue contains information that is predictive of lymph node status and patient prognosis and that this information can be extracted using Deep Learning (DL). Methods Using three patient cohorts comprising 1146 patients, we trained and validated a DL system to predict lymph node status directly from hematoxylin-and-eosin stained GC tissue sections. We investigated the concordance between the DL-based prediction from the primary tumor slides (aiN score) and the histopathological lymph node status (pN). Furthermore, we assessed the prognostic value of the aiN score alone and when combined with the pN status. Results The aiN score predicted the pN status reaching Area Under the Receiver Operating Characteristic curves (AUROCs) of 0.71 in the training cohort and 0.69 and 0.65 in the two test cohorts. In a multivariate Cox analysis, the aiN score was an independent predictor of patient survival with Hazard Ratios (HR) of 1.5 in the training cohort and of 1.3 and 2.2 in the two test cohorts. A combination of the aiN score and the pN status prognostically stratified patients by survival with p-values <0.05 in log-rank tests. Conclusion GC primary tumor tissue contains additional prognostic information that is accessible using the aiN score. In combination with the pN status, this can be used for personalized management of gastric cancer patients after prospective validation

The Extended Chiral Quark Model and QCD

We consider the low energy effective action of QCD below the chiral symmetry breaking scale, including, in Wilson's spirit, all operators of dimensionality less or equal to 6 which can be built with quark and chiral fields. The effect of the residual gluon interactions is contained in a number of coupling constants, whose running is studied. The resulting model is an extension of both the chiral quark model and the Nambu-Jona-Lasinio one. Constraints on the coefficients of the effective lagrangian are derived from the requirement of chiral symmetry restoration at energies above the chiral symmetry breaking scale, from matching to QCD at intermediate scales, and by fitting some hadronic observables. In this model two types of pseudoscalar states (massless pions and massive \Pi-mesons), as well as one scalar one arise as a consequence of dynamical chiral symmetry breaking. Their masses and coupling constants are studied. We also predict a number of low energy structural constants. We find out that QCD favours a low-energy effective theory which is largely dominated by the simplest chiral quark model, whereas higher dimensional operators (such as those of the Nambu-Jona-Lasinio type) can be assumed to be small.Comment: 43 pages, Sec.7 is slightly corrected, fit and conclusions are unchange

Grip strength values and cut-off points based on over 200,000 adults of the German National Cohort - a comparison to the EWGSOP2 cut-off points

BACKGROUND: The European Working Group on Sarcopenia in Older People (EWGSOP) updated in 2018 the cut-off points for low grip strength to assess sarcopenia based on pooled data from 12 British studies. OBJECTIVE: Comparison of the EWGSOP2 cut-off points for low grip strength to those derived from a large German sample. METHODS: We assessed the grip strength distribution across age and derived low grip strength cut-off points for men and women (peak mean -2.5 × SD) based on 200,389 German National Cohort (NAKO) participants aged 19–75 years. In 1,012 Cooperative Health Research in the Region of Augsburg (KORA)-Age participants aged 65–93 years, we calculated the age-standardised prevalence of low grip strength and time-dependent sensitivity and specificity for all-cause mortality. RESULTS: Grip strength increased in the third and fourth decade of life and declined afterwards. Calculated cut-off points for low grip strength were 29 kg for men and 18 kg for women. In KORA-Age, the age-standardised prevalence of low grip strength was 1.5× higher for NAKO-derived (17.7%) compared to EWGSOP2 (11.7%) cut-off points. NAKO-derived cut-off points yielded a higher sensitivity and lower specificity for all-cause mortality. CONCLUSIONS: Cut-off points for low grip strength from German population-based data were 2 kg higher than the EWGSOP2 cut-off points. Higher cut-off points increase the sensitivity, thereby suggesting an intervention for more patients at risk, while other individuals might receive additional diagnostics/treatment without the urgent need. Research on the effectiveness of intervention in patients with low grip strength defined by different cut-off points is needed

Temporal and tissue-specific variability of SMN protein levels in mouse models of spinal muscular atrophy

textabstractSpinal muscular atrophy (SMA) is a progressive motor neuron disease caused by deleterious variants in SMN1 that lead to a marked decrease in survival motor neuron (SMN) protein expression. Humans have a second SMN gene (SMN2) that is almost identical to SMN1. However, due to alternative splicing the majority of SMN2 messenger ribonucleic acid (mRNA) is translated into a truncated, unstable protein that is quickly degraded. Because the presence of SMN2 provides a unique opportunity for therapy development in SMA patients, the mechanisms that regulate SMN2 splicing and mRNA expression have been elucidated in great detail. In contrast, how much SMN protein is produced at different developmental time points and in different tissues remains under-characterized. In this study, we addressed this issue by determining SMN protein expression levels at three developmental time points across six different mouse tissues and in two distinct mouse models of SMA ('severe' Taiwanese and 'intermediate' Smn2B/mice). We found that, in healthy control mice, SMN protein expression was significantly influenced by both age and tissue type.When comparing mouse models of SMA, we found that, despite being transcribed from genetically different alleles, control SMN levels were relatively similar. In contrast, the degree of SMN depletion between tissues in SMA varied substantially over time and between the two models. These findings offer an explanation for the differential vulnerability of tissues and organs observed in SMA and further our understanding of the systemic and temporal requirements for SMN with direct relevance for developing effective therapies for SMA

Challenges of operational river forecasting

Skillful and timely streamflow forecasts are critically important to water managers and emergency protection services. To provide these forecasts, hydrologists must predict the behavior of complex coupled human–natural systems using incomplete and uncertain information and imperfect models. Moreover, operational predictions often integrate anecdotal information and unmodeled factors. Forecasting agencies face four key challenges: 1) making the most of available data, 2) making accurate predictions using models, 3) turning hydrometeorological forecasts into effective warnings, and 4) administering an operational service. Each challenge presents a variety of research opportunities, including the development of automated quality-control algorithms for the myriad of data used in operational streamflow forecasts, data assimilation, and ensemble forecasting techniques that allow for forecaster input, methods for using human-generated weather forecasts quantitatively, and quantification of human interference in the hydrologic cycle. Furthermore, much can be done to improve the communication of probabilistic forecasts and to design a forecasting paradigm that effectively combines increasingly sophisticated forecasting technology with subjective forecaster expertise. These areas are described in detail to share a real-world perspective and focus for ongoing research endeavors