Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems.

The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H2O, N2, and F2 molecules. The method is based on Feynman's path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.

GeauxDock: A novel approach for mixed-resolution ligand docking using a descriptor-based force field.

Molecular docking is an important component of computer-aided drug discovery. In this communication, we describe GeauxDock, a new docking approach that builds on the ideas of ligand homology modeling. GeauxDock features a descriptor-based scoring function integrating evolutionary constraints with physics-based energy terms, a mixed-resolution molecular representation of protein-ligand complexes, and an efficient Monte Carlo sampling protocol. To drive docking simulations toward experimental conformations, the scoring function was carefully optimized to produce a correlation between the total pseudoenergy and the native-likeness of binding poses. Indeed, benchmarking calculations demonstrate that GeauxDock has a strong capacity to identify near-native conformations across docking trajectories with the area under receiver operating characteristics of 0.85. By excluding closely related templates, we show that GeauxDock maintains its accuracy at lower levels of homology through the increased contribution from physics-based energy terms compensating for weak evolutionary constraints. GeauxDock is available at http://www.institute.loni.org/lasigma/package/dock/.

What is the Valence of Mn in Ga(1-x)Mn(x)N?

We investigate the current debate on the Mn valence in Ga(1-x)Mn(x)N, a diluted magnetic semiconductor (DMS) with a potentially high Curie temperature. From a first-principles Wannier-function analysis, we unambiguously find the Mn valence to be close to 2+ (d(5)), but in a mixed spin configuration with average magnetic moments of 4µ(B). By integrating out high-energy degrees of freedom differently, we further derive for the first time from first-principles two low-energy pictures that reflect the intrinsic dual nature of the doped holes in the DMS: (1) an effective d(4) picture ideal for local physics, and (2) an effective d(5) picture suitable for extended properties. In the latter, our results further reveal a few novel physical effects, and pave the way for future realistic studies of magnetism. Our study not only resolves one of the outstanding key controversies of the field, but also exemplifies the general need for multiple effective descriptions to account for the rich low-energy physics in many-body systems in general.

Cooling Atomic Gases With Disorder.

Cold atomic gases have proven capable of emulating a number of fundamental condensed matter phenomena including Bose-Einstein condensation, the Mott transition, Fulde-Ferrell-Larkin-Ovchinnikov pairing, and the quantum Hall effect. Cooling to a low enough temperature to explore magnetism and exotic superconductivity in lattices of fermionic atoms remains a challenge. We propose a method to produce a low temperature gas by preparing it in a disordered potential and following a constant entropy trajectory to deliver the gas into a nondisordered state which exhibits these incompletely understood phases. We show, using quantum Monte Carlo simulations, that we can approach the Néel temperature of the three-dimensional Hubbard model for experimentally achievable parameters. Recent experimental estimates suggest the randomness required lies in a regime where atom transport and equilibration are still robust.

Equation of motion coupled cluster methods for electron attachment and ionization potential in fullerenes C60 and C70.

In both molecular and periodic solid-state systems there is a need for the accurate determination of the ionization potential and the electron affinity for systems ranging from light harvesting polymers and photocatalytic compounds to semiconductors. The development of a Green's function approach based on the coupled cluster (CC) formalism would be a valuable tool for addressing many properties involving many-body interactions along with their associated correlation functions. As a first step in this direction, we have developed an accurate and parallel efficient approach based on the equation of motion-CC technique. To demonstrate the high degree of accuracy and numerical efficiency of our approach we calculate the ionization potential and electron affinity for C60 and C70. Accurate predictions for these molecules are well beyond traditional molecular scale studies. We compare our results with experiments and both quantum Monte Carlo and GW calculations.

Application of the variational autoencoder to detect the critical points of the anisotropic Ising model.

We generalize the previous study on the application of variational autoencoders to the two-dimensional Ising model to a system with anisotropy. Due to the self-duality property of the system, the critical points can be located exactly for the entire range of anisotropic coupling. This presents an excellent test bed for the validity of using a variational autoencoder to characterize an anisotropic classical model. We reproduce the phase diagram for a wide range of anisotropic couplings and temperatures via a variational autoencoder without the explicit construction of an order parameter. Considering that the partition function of (d+1)-dimensional anisotropic models can be mapped to that of the d-dimensional quantum spin models, the present study provides numerical evidence that a variational autoencoder can be applied to analyze quantum systems via the quantum Monte Carlo method.

Influence of state reopening policies in COVID-19 mortality.

By the end of May 2020, all states in the US have eased their COVID-19 mitigation measures. Different states adopted markedly different policies and timing for reopening. An important question remains in how the relaxation of mitigation measures is related to the number of casualties. To address this question, we compare the actual data to a hypothetical case in which the mitigation measures are left intact using a projection of the data from before mitigation measures were eased. We find that different states have shown significant differences between the actual number of deaths and the projected figures within the present model. We relate these differences to the states different policies and reopening schedules. Our study provides a gauge for the effectiveness of the approaches by different state governments and can serve as a guide for implementing best policies in the future. According to the Pearson correlation coefficients we obtained, the face mask mandate has the strongest correlation with the death count than any other policies we considered.

Putative new lineage of west nile virus, Spain.

To ascertain the presence of West Nile virus (WNV), we sampled mosquitoes in 2006 in locations in southern Spain where humans had been infected. WNV genomic RNA was detected in 1 pool from unfed female Culex pipiens mosquitoes. Phylogenetic analysis demonstrated that this sequence cannot be assigned to previously described lineages of WNV.

Nonlocal effects on magnetism in the diluted magnetic semiconductor Ga1-xMnxAs.

The magnetic properties of the diluted magnetic semiconductor Ga1-xMnxAs are studied within the dynamical cluster approximation. We use the k x p Hamiltonian to describe the electronic structure of GaAs with spin-orbit coupling and strain effects. We show that nonlocal effects are essential for explaining the experimentally observed transition temperature and saturation magnetization. We also demonstrate that the cluster anisotropy is very strong and induces rotational frustration and a cube-edge direction magnetic anisotropy at low temperature. With this, we explain the temperature-driven spin reorientation in this system.

Effect of mitigation measures on the spreading of COVID-19 in hard-hit states in the U.S.

State government-mandated social distancing measures have helped to slow the growth of the COVID-19 pandemic in the United States. Many of the current predictive models of the development of COVID-19, especially after mitigation efforts, partially rely on extrapolations from data collected in other countries. Since most states enacted stay-at-home orders towards the end of March, the resulting effects of social distancing should be reflected in the death and infection counts by the end of April. Using the data available through April 25th, we investigate the change in the infection rate due to the mitigation efforts and project death and infection counts through September 2020 for some of the most heavily impacted states: New York, New Jersey, Michigan, Massachusetts, Illinois, and Louisiana. We find that with the current mitigation efforts, five of those six states have reduced their base reproduction number to a value less than one, stopping the exponential growth of the pandemic. We also project different scenarios after the mitigation is relaxed.

Computational feasibility of calculating the steady-state blood flow rate through the vasculature of the entire human body.

The human body contains approximately 20 billion individual blood vessels that deliver nutrients and oxygen to tissues. While blood flow is a well-developed field of research, no previous studies have calculated the blood flow rates through more than 5 million connected vessels. The goal of this study was to test if it is computationally feasible to calculate the blood flow rates through a vasculature equal in size to that of the human body. We designed and implemented a two-step algorithm to calculate the blood flow rates using principles of steady-state fluid dynamics. Steady-state fluid dynamics is an accurate approximation for the microvascular and venous structures in the human body. To determine the computational feasibility, we measured and evaluated the execution time, scalability, and memory usage to quantify the computational requirements. We demonstrated that it is computationally feasible to calculate the blood flow rate through 17 billion vessels in 6.5 hours using 256 compute nodes. The computational modeling of blood flow rate in entire organisms may find application in research on drug delivery, treatment of cancer metastases, and modulation of physiological performance.

Food Identities, Biocultural Knowledge and Gender Differences in the Protected Area "Sierra Grande de Hornachos" (Extremadura, Spain).

A food tradition not only corresponds to the vital need to be nourished every day, but is part of the particularity of a territory as a consequence of its history, traditions, natural heritage, and capacity for ecological and social resilience. In the search for culinary identity, a valorization of a rural territory of high identity potential is carried out, such as in the environmental protection area "Sierra Grande de Hornachos" (Extremadura, Spain), and specifically the town of Hornachos. For this purpose, a series of workshops and interviews were held for men and women who had lived most of their lives in Hornachos and who were older than 70. Information on the food uses of wild and cultivated plants, as determined by the Cultural Significance Index (CSI) for 79 species, was extracted from the interpretation of the data collected. In addition, new uses were collected in Extremadura for 16 plants and in Spain for 3, with some of these data being of particular significance in the culinary culture of Hornachega. We conclude that the area "Sierra Grande de Hornachos" forms an environment of great culinary identity that must be preserved, not only for its heritage interests but also for its agroecological ones, which could be translated into measures of wealth creation and development.

Mapeando en tiempos de la COVID-19 / Mapping out in COVID-19 times

Introducción y objetivos: La COVID-19 hace evidente la urgencia de crear un sistema equitativo en el acceso a la salud. Así, se decide realizar un enfoque salutogénico basado en los activos para la salud. Para ello, se pretende identificar los principales problemas de salud de nuestra comunidad y conocer los recursos comunitarios disponibles, con el fin de establecer alianzas y proyectos futuros de colaboración. Métodos: Inicialmente, el Grupo Promotor (GP) hace el diagnóstico de salud y delimita el área de intervención. Una vez ubicados los activos por internet, se representan en el mapa. Se elige la entrevista individual como técnica de recogida de información. Cuando la situación epidemiológica lo permite, se organiza una reunión con los representantes de los recursos comunitarios, donde se analizan los resultados y se identifican los problemas más emergentes. Resultados: A lo largo de 7 meses, se hicieron 16 entrevistas con distintos representantes sociales de la comunidad Los principales problemas encontrados fueron desempleo, migración, prostitución, adicción y suicidio. La mayoría de las actividades comunitarias se han visto interrumpidas durante el confinamiento por la COVID-19, aunque han surgido nuevas iniciativas. Conclusión/discusión: El mapeo de recursos comunitarios y diagnóstico en salud aporta una visión real de la comunidad. Además, implica a sus representantes, profesionales y ciudadanía en la búsqueda de soluciones, desarrollando mejores condiciones de vida. (AU)

Introduction and objectives. COVID-19 reveals the urgency of creating an equitable system in access to healthcare. Thus, it has been decided to perform a salutogenic approach based on health assets. For that to be accomplished, it is intended to identify our community’s main health problems and to ascertain the available community resources to establish alliances and future collaboration projects. Methodology. Initially, the Promoter Group (PG) performs the health diagnosis and defines the area of intervention. Once the assets are found on the internet, they are placed on the map. The data collection technique chosen was the individual interview. When the epidemiological situation enables this, a meeting is organized with the representatives of the community resources, where the results are analyzed and the most emerging problems are identified. Results. Over seven months, 16 interviews were held with different social representatives of the community. The fundamental problems detected were unemployment, migration, prostitution, addiction and suicide. Most community activities were interrupted during the COVID-19 lockdown, although new initiatives have arisen. Conclusion/Discussion. Asset mapping and diagnosis in health provides an actual vision of the Community. Furthermore, it involves its representatives, professionals and citizens in the search for solutions, providing a better quality of life. (AU)

Potentially Inappropriate Antihypertensive Prescriptions to Elderly Patients: Results of a Prospective, Observational Study.

INTRODUCTION: Previous studies of antihypertensive treatment of older patients have focused on blood pressure control, cardiovascular risk or adherence, whereas data on inappropriate antihypertensive prescriptions to older patients are scarce. OBJECTIVES: The aim of the study was to assess inappropriate antihypertensive prescriptions to older patients. METHODS: An observational, prospective multicentric study was conducted to assess potentially inappropriate prescription of antihypertensive drugs, in patients aged 75 years and older with arterial hypertension (HTN), in the month prior to hospital admission, using four instruments: Beers, Screening Tool of Older Person's Prescriptions (STOPP), Screening Tool to Alert Doctors to the Right Treatment (START) and Assessing Care of Vulnerable Elders 3 (ACOVE-3). Primary care and hospital electronic records were reviewed for HTN diagnoses, antihypertensive treatment and blood pressure readings. RESULTS: Of 672 patients, 532 (median age 85 years, 56% female) had HTN. 21.6% received antihypertensive monotherapy, 4.7% received no hypertensive treatment, and the remainder received a combination of antihypertensive therapies. The most frequently prescribed antihypertensive drugs were diuretics (53.5%), angiotensin-converting enzyme inhibitors (ACEIs) (41%), calcium antagonists (32.2%), angiotensin receptor blockers (29.7%) and beta-blockers (29.7%). Potentially inappropriate prescription was observed in 51.3% of patients (27.8% overprescription and 35% underprescription). The most frequent inappropriately prescribed drugs were calcium antagonists (overprescribed), ACEIs and beta-blockers (underprescribed). ACEI and beta-blocker underprescriptions were independently associated with heart failure admissions [beta-blockers odds ratio (OR) 0.53, 95% confidence interval (CI) 0.39-0.71, p < 0.001; ACEIs OR 0.50, 95% CI 0.36-0.70, p < 0.001]. CONCLUSION: Potentially inappropriate prescription was detected in more than half of patients receiving antihypertensive treatment. Underprescription was more frequent than overprescription. ACEIs and beta-blockers were frequently underprescribed and were associated with heart failure admissions.

Assessing the similarity of ligand binding conformations with the Contact Mode Score.

Structural and computational biologists often need to measure the similarity of ligand binding conformations. The commonly used root-mean-square deviation (RMSD) is not only ligand-size dependent, but also may fail to capture biologically meaningful binding features. To address these issues, we developed the Contact Mode Score (CMS), a new metric to assess the conformational similarity based on intermolecular protein-ligand contacts. The CMS is less dependent on the ligand size and has the ability to include flexible receptors. In order to effectively compare binding poses of non-identical ligands bound to different proteins, we further developed the eXtended Contact Mode Score (XCMS). We believe that CMS and XCMS provide a meaningful assessment of the similarity of ligand binding conformations. CMS and XCMS are freely available at http://brylinski.cct.lsu.edu/content/contact-mode-score and http://geaux-computational-bio.github.io/contact-mode-score/.

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

Accelerating the Pace of Protein Functional Annotation With Intel Xeon Phi Coprocessors.

Intel Xeon Phi is a new addition to the family of powerful parallel accelerators. The range of its potential applications in computationally driven research is broad; however, at present, the repository of scientific codes is still relatively limited. In this study, we describe the development and benchmarking of a parallel version of eFindSite, a structural bioinformatics algorithm for the prediction of ligand-binding sites in proteins. Implemented for the Intel Xeon Phi platform, the parallelization of the structure alignment portion of eFindSite using pragma-based OpenMP brings about the desired performance improvements, which scale well with the number of computing cores. Compared to a serial version, the parallel code runs 11.8 and 10.1 times faster on the CPU and the coprocessor, respectively; when both resources are utilized simultaneously, the speedup is 17.6. For example, ligand-binding predictions for 501 benchmarking proteins are completed in 2.1 hours on a single Stampede node equipped with the Intel Xeon Phi card compared to 3.1 hours without the accelerator and 36.8 hours required by a serial version. In addition to the satisfactory parallel performance, porting existing scientific codes to the Intel Xeon Phi architecture is relatively straightforward with a short development time due to the support of common parallel programming models by the coprocessor. The parallel version of eFindSite is freely available to the academic community at www.brylinski.org/efindsite.

Effective cluster typical medium theory for the diagonal Anderson disorder model in one- and two-dimensions.

We develop a cluster typical medium theory to study localization in disordered electronic systems. Our formalism is able to incorporate non-local correlations beyond the local typical medium theory in a systematic way. The cluster typical medium theory utilizes the momentum-resolved typical density of states and hybridization function to characterize the localization transition. We apply the formalism to the Anderson model of localization in one- and two-dimensions. In one-dimension, we find that the critical disorder strength scales inversely with the linear cluster size with a power law, Wc ∼ (1/Lc)(1/ν), whereas in two-dimensions, the critical disorder strength decreases logarithmically with the linear cluster size. Our results are consistent with previous numerical work and are in agreement with the one-parameter scaling theory.

First-principles Wannier function analysis of the electronic structure of PdTe: weaker magnetism and superconductivity.

We report a first-principles Wannier function study of the electronic structure of PdTe. Its electronic structure is found to be a broad three-dimensional Fermi surface with highly reduced correlation effects. In addition, the higher filling of the Pd d-shell, its stronger covalency resulting from the closer energy of the Pd d and Te p shells, and the larger crystal field effects of the Pd ion due to its near octahedral coordination, all serve to weaken significantly electronic correlations in the particle-hole (spin, charge, and orbital) channel. In comparison to the Fe chalcogenides, e.g. FeSe, we highlight the essential features (quasi-two-dimensionality, proximity to half-filling, weaker covalency, and higher orbital degeneracy) of Fe-based high-temperature superconductors.

[Predictive variables for mortality in elderly patients hospitalized due to heart failure with preserved ejection fraction]. / Variables predictoras de mortalidad en pacientes ancianos hospitalizados por insuficiencia cardiaca con fracción de eyección preservada.

BACKGROUND AND OBJECTIVES: The prevalence of heart failure (HF) increases with age. Even though the mortality of patients ≥ 80 years of age with HF and preserved left ventricle ejection fraction (LVEF) is very high, the predictor variables are not well-known. The main goal of this study was to evaluate the mortality predictor factors in this subgroup of the elderly population. PATIENTS AND METHODS: An observational and prospective study of patients hospitalized due to HF with preserved LVEF has been conducted. The demographic, clinical, functional and analytic factors were evaluated when the patients were admitted with special attention to the co-morbidities. The primary endpoint was the total mortality in the subgroup of patients ≥ 80 years of age after a year of follow-up. The predictor variables were studied by means of a multivariate Cox regression model. RESULTS: From a total of 218 patients with an average age of 75.6 (±8.7) years of age, 75 patients (34.4%) were ≥ 80 years. The mortality rate of patients ≥ 80 years of age totaled 42.7%, in relation to 26.6% for the lower age group (log-rank<.001). After a multivariate analysis using the Cox regression model in patients ≥ 80, the serum urea levels above the average (hazard ratio [HR] 3.93; 95% confidence interval [95% CI] 1.58-9.75; P = .003), the age (HR 1.17; 95% CI 1.07-1.28; P<.001), the hyponatremia (HR 3.19; 95% CI 1.51-6.74; P = .002) and a lower score on the Barthel index (BI) (HR 1.016; 95% CI 1.002-1.031; P = .034) were independent mortality predictors after an one-year follow-up. CONCLUSIONS: Serum urea levels, age, hyponatremia and a low BI score could be proposed as independent mortality predictors in patients ≥ 80 of age hospitalized for HF with preserved LVEF.