Quantum splines

A quantum spline is a smooth curve parameterised by time in the space of unitary transformations, whose associated orbit on the space of pure states traverses a designated set of quantum states at designated times, such that the trace norm of the time rate of change of the associated Hamiltonian is minimised. The solution to the quantum spline problem is obtained, and is applied in an example that illustrates quantum control of coherent states. An e cient numerical scheme for computing quantum splines is discussed and implemented in the examples

A jetlet hierarchy for ideal fluid dynamics

European Research Council Advanced Grant 267382 FCCA

Long-Term SGRQ Stability in a Cohort of Individuals with Alpha-1 Antitrypsin Deficiency-Associated Lung Disease

Radmila Choate,1 Kristen E Holm,2,3 Robert A Sandhaus,2,3 David M Mannino,4 Charlie Strange3,5 1University of Kentucky College of Public Health, Lexington, Kentucky, USA; 2Department of Medicine, National Jewish Health, Denver, Colorado, USA; 3Alphanet, Inc., Coral Gables, Florida, USA; 4University of Kentucky College of Medicine, Lexington, Kentucky, USA; 5Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Medical University of South Carolina, Charleston, South Carolina, USACorrespondence: Radmila Choate, University of Kentucky College of Public Health, Lexington, Kentucky, USA, Tel +1 859-218-2237, Email [email protected]: Health-related quality of life (HRQoL) assessments such as St. George’s Respiratory Questionnaire (SGRQ) are often used as outcome measures to evaluate patient-perceived changes in health status among individuals with lung disease. Several factors have been linked to deterioration in SGRQ, including symptoms (dyspnea, wheezing) and exercise intolerance. Whether these findings apply to individuals with alpha-1 antitrypsin deficiency (AATD) remains incompletely studied. This longitudinal study examines the trajectory of SGRQ scores in a cohort of United States individuals with AATD-associated lung disease and defines factors associated with longitudinal change.Methods: Individuals with AATD-associated lung disease enrolled in AlphaNet, a disease management program, who had ≥ 3 SGRQ measurements collected between 2009 and 2019, and baseline data for clinically important variables were included in these analyses. Data collected after lung transplants were excluded. Mixed-effects model analyses were used to evaluate the changes in SGRQ total and subscale scores over time and by modified Medical Research Council (mMRC) Scale, use of oxygen, age, sex, productive cough, and exacerbation frequency at baseline. Sensitivity analyses were conducted to examine the potential effect of survivor bias.Results: Participants (n=2456, mean age 57.1± 9.9 years, 47% female) had a mean SGRQ total score of 44.7± 18.9 at baseline, 48% used oxygen regularly, and 55% had ≥ 2 exacerbations per year. The median length of follow-up was 6 (IQR 3– 9) years. The SGRQ total score and subscales remained stable throughout the observation period. Age, mMRC categories, presence or absence of productive cough, frequency of exacerbations, and use of oxygen at baseline were significantly associated with the rate of change of SGRQ total (p< 0.0001).Conclusion: We observed long-term stability in HRQoL and an association between the rate of change in SGRQ and baseline mMRC, exacerbation frequency, productive cough, and use of oxygen in this cohort of individuals with AATD-associated lung disease.Keywords: COPD, alpha-1 antitrypsin deficiency, quality of lif

Weak dual pairs and Jetlet methods for ideal incompressible fluid models in n≥2 dimensions

We review the role of dual pairs in mechanics and use them to derive particle-like solutions to regularized incompressible fluid systems. In our case we have a dual pair resulting from the action of diffeomorphisms on point particles (essentially by moving the points). We then augment our dual pair by considering the action of diffeomorphisms on Taylor series, also known as jets. The augmented weak dual pairs induce a hierarchy of particle-like solutions and conservation laws with particles carrying a copy of a jet group. We call these augmented particles jetlets. The jet groups serve as finite-dimensional models of the diffeomorphism group itself, and so the jetlet particles serve as a finite-dimensional model of the self-similarity exhibited by ideal incompressible fluids. The conservation law associated to jetlet solutions is shown to be a shadow of Kelvin’s circulation theorem. Finally, we study the dynamics of infinite time particle mergers. We prove that two merging particles at the zeroth level in the hierarchy yield dynamics which asymptotically approach that of a single particle in the first level in the hierarchy. This merging behavior is then verified numerically as well as the exchange of angular momentum which must occur during a near collision of two particles. The resulting particle-like solutions suggest a new class of meshless methods which work in dimensions [Math Processing Error] n≥2 and which exhibit a shadow of Kelvin’s circulation theorem. More broadly, this provides one of the first finite-dimensional models of self-similarity in ideal fluids

Analysis of Group Randomized Trials with Multiple Binary Endpoints and Small Number of Groups

The group randomized trial (GRT) is a common study design to assess the effect of an intervention program aimed at health promotion or disease prevention. In GRTs, groups rather than individuals are randomized into intervention or control arms. Then, responses are measured on individuals within those groups. A number of analytical problems beset GRT designs. The major problem emerges from the likely positive intraclass correlation among observations of individuals within a group. This paper provides an overview of the analytical method for GRT data and applies this method to a randomized cancer prevention trial, where multiple binary primary endpoints were obtained. We develop an index of extra variability to investigate group-specific effects on response. The purpose of the index is to understand the influence of individual groups on evaluating the intervention effect, especially, when a GRT study involves a small number of groups. The multiple endpoints from the GRT design are analyzed using a generalized linear mixed model and the stepdown Bonferroni method of Holm

Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple "big-leaf" approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1°. While the photosynthetic capacity parameter (Vc;max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity

Theoretical study of the insulating oxides and nitrides: SiO2, GeO2, Al2O3, Si3N4, and Ge3N4

An extensive theoretical study is performed for wide bandgap crystalline oxides and nitrides, namely, SiO_{2}, GeO_{2}, Al_{2}O_{3}, Si_{3}N_{4}, and Ge_{3}N_{4}. Their important polymorphs are considered which are for SiO_{2}: $\alpha$-quartz, $\alpha$- and $\beta$-cristobalite and stishovite, for GeO_{2}: $\alpha$-quartz, and rutile, for Al_{2}O_{3}: $\alpha$-phase, for Si_{3}N_{4} and Ge_{3}N_{4}: $\alpha$- and $\beta$-phases. This work constitutes a comprehensive account of both electronic structure and the elastic properties of these important insulating oxides and nitrides obtained with high accuracy based on density functional theory within the local density approximation. Two different norm-conserving \textit{ab initio} pseudopotentials have been tested which agree in all respects with the only exception arising for the elastic properties of rutile GeO_{2}. The agreement with experimental values, when available, are seen to be highly satisfactory. The uniformity and the well convergence of this approach enables an unbiased assessment of important physical parameters within each material and among different insulating oxide and nitrides. The computed static electric susceptibilities are observed to display a strong correlation with their mass densities. There is a marked discrepancy between the considered oxides and nitrides with the latter having sudden increase of density of states away from the respective band edges. This is expected to give rise to excessive carrier scattering which can practically preclude bulk impact ionization process in Si_{3}N_{4} and Ge_{3}N_{4}.Comment: Published version, 10 pages, 8 figure

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

Transcriptomics reveal an integrative role for maternal thyroid hormones during zebrafish embryogenesis

Thyroid hormones (THs) are essential for embryonic brain development but the genetic mechanisms involved in the action of maternal THs (MTHs) are still largely unknown. As the basis for understanding the underlying genetic mechanisms of MTHs regulation we used an established zebrafish monocarboxylic acid transporter 8 (MCT8) knock-down model and characterised the transcriptome in 25hpf zebrafish embryos. Subsequent mapping of differentially expressed genes using Reactome pathway analysis together with in situ expression analysis and immunohistochemistry revealed the genetic networks and cells under MTHs regulation during zebrafish embryogenesis. We found 4,343 differentially expressed genes and the Reactome pathway analysis revealed that TH is involved in 1681 of these pathways. MTHs regulated the expression of core developmental pathways, such as NOTCH and WNT in a cell specific context. The cellular distribution of neural MTH-target genes demonstrated their cell specific action on neural stem cells and differentiated neuron classes. Taken together our data show that MTHs have a role in zebrafish neurogenesis and suggest they may be involved in cross talk between key pathways in neural development. Given that the observed MCT8 zebrafish knockdown phenotype resembles the symptoms in human patients with Allan-Herndon-Dudley syndrome our data open a window into understanding the genetics of this human congenital condition.Portuguese Fundacao para Ciencia e Tecnologia (FCT) [PTDC/EXPL/MARBIO/0430/2013]; CCMAR FCT Plurianual financing [UID/Multi/04326/2013]; FCT [SFRH/BD/111226/2015, SFRH/BD/108842/2015, SFRH/BPD/89889/2012]; FCT-IF Starting Grant [IF/01274/2014]info:eu-repo/semantics/publishedVersio