Transition Metal Chemistry of Oxime Containing Ligands: Part III-Complexes of Fe(II), Co(II) & Ni(II) with Pyridine-2-aldoxime & 6-Methylpyridine-2-aldoxime

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Fixing the BMS Frame of Numerical Relativity Waveforms

Understanding the Bondi-Metzner-Sachs (BMS) frame of the gravitational waves produced by numerical relativity is crucial for ensuring that analyses on such waveforms are performed properly. It is also important that models are built from waveforms in the same BMS frame. Up until now, however, the BMS frame of numerical waveforms has not been thoroughly examined, largely because the necessary tools have not existed. In this paper, we show how to analyze and map to a suitable BMS frame for numerical waveforms calculated with the Spectral Einstein Code (SpEC). However, the methods and tools that we present are general and can be applied to any numerical waveforms. We present an extensive study of 13 binary black hole systems that broadly span parameter space. From these simulations, we extract the strain and also the Weyl scalars using both SpECTRE's Cauchy-characteristic extraction module and also the standard extrapolation procedure with a displacement memory correction applied during post-processing. First, we show that the current center-of-mass correction used to map these waveforms to the center-of-mass frame is not as effective as previously thought. Consequently, we also develop an improved correction that utilizes asymptotic Poincar\'e charges instead of a Newtonian center-of-mass trajectory. Next, we map our waveforms to the post-Newtonian (PN) BMS frame using a PN strain waveform. This helps us find the unique BMS transformation that minimizes the $L^{2}$ norm of the difference between the numerical and PN strain waveforms during the early inspiral phase. We find that once the waveforms are mapped to the PN BMS frame, they can be hybridized with a PN strain waveform much more effectively than if one used any of the previous alignment schemes, which only utilize the Poincar\'e transformations

Multipole moments on the common horizon in a binary-black-hole simulation

We construct the covariantly defined multipole moments on the common horizon of an equal-mass, non-spinning, quasicircular binary-black-hole system. We see a strong correlation between these multipole moments and the gravitational waveform. We find that the multipole moments are well described by the fundamental quasinormal modes at sufficiently late times. For each multipole moment, at least two fundamental modes of different $\ell$ are detectable in the best model. These models provide faithful estimates of the true mass and spin of the remnant black hole. We also show that by including overtones, the $\ell=m=2$ mass multipole moment admits an excellent quasinormal-mode description at all times after the merger. This demonstrates the perhaps surprising power of perturbation theory near the merger

Identification of QTLs associated with oil content and mapping FAD2 genes and their relative contribution to oil quality in peanut (Arachis hypogaeaL.)

Background Peanut is one of the major source for human consumption worldwide and its seed contain approximately 50% oil. Improvement of oil content and quality traits (high oleic and low linoleic acid) in peanut could be accelerated by exploiting linked markers through molecular breeding. The objective of this study was to identify QTLs associated with oil content, and estimate relative contribution of FAD2 genes (ahFAD2A and ahFAD2B) to oil quality traits in two recombinant inbred line (RIL) populations. Results Improved genetic linkage maps were developed for S-population (SunOleic 97R × NC94022) with 206 (1780.6 cM) and T-population (Tifrunner × GT-C20) with 378 (2487.4 cM) marker loci. A total of 6 and 9 QTLs controlling oil content were identified in the S- and T-population, respectively. The contribution of each QTL towards oil content variation ranged from 3.07 to 10.23% in the S-population and from 3.93 to 14.07% in the T-population. The mapping positions for ahFAD2A (A sub-genome) and ahFAD2B (B sub-genome) genes were assigned on a09 and b09 linkage groups. The ahFAD2B gene (26.54%, 25.59% and 41.02% PVE) had higher phenotypic effect on oleic acid (C18:1), linoleic acid (C18:2), and oleic/linoleic acid ratio (O/L ratio) than ahFAD2A gene (8.08%, 6.86% and 3.78% PVE). The FAD2 genes had no effect on oil content. This study identified a total of 78 main-effect QTLs (M-QTLs) with up to 42.33% phenotypic variation (PVE) and 10 epistatic QTLs (E-QTLs) up to 3.31% PVE for oil content and quality traits. Conclusions A total of 78 main-effect QTLs (M-QTLs) and 10 E-QTLs have been detected for oil content and oil quality traits. One major QTL (more than 10% PVE) was identified in both the populations for oil content with source alleles from NC94022 and GT-C20 parental genotypes. FAD2 genes showed high effect for oleic acid (C18:1), linoleic acid (C18:2), and O/L ratio while no effect on total oil content. The information on phenotypic effect of FAD2 genes for oleic acid, linoleic acid and O/L ratio, and oil content will be applied in breeding selection

Adding Gravitational Memory to Waveform Catalogs using BMS Balance Laws

Accurate models of gravitational waves from merging binary black holes are crucial for detectors to measure events and extract new science. One important feature that is currently missing from the Simulating eXtreme Spacetimes (SXS) Collaboration's catalog of waveforms for merging black holes, and other waveform catalogs, is the gravitational memory effect: a persistent, physical change to spacetime that is induced by the passage of transient radiation. We find, however, that by exploiting the Bondi-Metzner-Sachs (BMS) balance laws, which come from the extended BMS transformations, we can correct the strain waveforms in the SXS catalog to include the missing displacement memory. Our results show that these corrected waveforms satisfy the BMS balance laws to a much higher degree of accuracy. Furthermore, we find that these corrected strain waveforms coincide especially well with the waveforms obtained from Cauchy-characteristic extraction (CCE) that already exhibit memory effects. These corrected strain waveforms also evade the transient junk effects that are currently present in CCE waveforms. Lastly, we make our code for computing these contributions to the BMS balance laws and memory publicly available as a part of the python package $\texttt{sxs}$, thus enabling anyone to evaluate the expected memory effects and violation of the BMS balance laws

The Association Between Self-Reported Symptoms of Recent Airway Infection and CRP Values in a General Population: The Tromsø Study: Tromsø 6

C-reactive protein (CRP) is a much used biomarker for respiratory tract infection; however, the influence of airway infection on the CRP level in the general population has not been well described. The study aimed to evaluate the impact of recent symptoms of airway infection on the CRP level and how the predictive power of other known CRP predictors is influenced by taking respiratory symptoms into account. A total of 6,325 participants, aged 38–87 years, in the Tromsø Study, a repeated population-based survey, were examined with questionnaires, measurements of height and weight, spirometry, and high-sensitivity CRP analyses. The mean CRP value was 2.86 mg/L, and the geometric mean was 1.51 mg/L. Geometric means above 2.0 mg/L were found in the subgroups with the following characteristics: self-reported COPD, diabetes, recent symptoms of airway infection, forced expiratory volume in 1 s (FEV1) <80% predicted, body mass index (BMI) ≥30, and subjects treated with inhaled or oral corticosteroids. Among the subjects who reported recent airway infection, 10.5% had a CRP value of ≥10 mg/L, compared to 3.3% among the remaining participants. By multivariate analysis, BMI was the strongest independent predictor of the CRP level, followed by recent airway infection, FEV1% predicted, age, and current smoking. The study clearly demonstrates that a report of recent symptoms of airway infection strongly predicts the CRP level in the population. Such symptoms were shared rather equally between subgroups with increased CRP level, and the risk of being an important confounder in epidemiological studies is probably low. In the clinical setting, care should be taken when using the CRP level as a guide for medical prevention of chronic diseases

High Precision Ringdown Modeling: Multimode Fits and BMS Frames

Quasi-normal mode (QNM) modeling is an invaluable tool for studying strong gravity, characterizing remnant black holes, and testing general relativity. To date, most studies have focused on the dominant $(2, 2)$ mode, and have fit to standard strain waveforms from numerical relativity. But, as gravitational wave observatories become more sensitive, they can resolve higher-order modes. Multimode fits will be critically important, and in turn require a more thorough treatment of the asymptotic frame at $\mathscr{I}^+$. The first main result of this work is a method for systematically fitting a QNM model containing many modes to a numerical waveform produced using Cauchy-characteristic extraction, which is known to exhibit memory effects. We choose the modes to model based on their power contribution to the residual between numerical and model waveforms. We show that the all-angles mismatch improves by a factor of $\sim 10^5$ when using multimode fitting as opposed to only fitting $(2, \pm2, n)$ modes. Our second main result addresses a critical point that has been overlooked in the literature: the importance of matching the Bondi-van der Burg-Metzner-Sachs (BMS) frame of the simulated gravitational wave to that of the QNM model. We show that by mapping the numerical relativity waveforms to the super rest frame, there is an improvement of $\sim 10^5$ in the all-angles strain mismatch, compared to using the strain whose BMS frame is not fixed. We illustrate the effectiveness of these modeling enhancements by applying them to families of waveforms produced by numerical relativity, and comparing our results to previous studies

Long-range potential fluctuations and 1/f noise in hydrogenated amorphous silicon

We present a microscopic theory of the low-frequency voltage noise (known as "1/f" noise) in micrometer-thick films of hydrogenated amorphous silicon. This theory traces the noise back to the long-range fluctuations of the Coulomb potential produced by deep defects, thereby predicting the absolute noise intensity as a function of the distribution of defect activation energies. The predictions of this theory are in very good agreement with our own experiments in terms of both the absolute intensity and the temperature dependence of the noise spectra.Comment: 8 pages, 3 figures, several new parts and one new figure are added, but no conceptual revision

Associations Between High-Density Lipoprotein Particles and Ischemic Events by Vascular Domain, Sex, and Ethnicity A Pooled Cohort Analysis

Background: High-density lipoprotein (HDL) cholesterol concentration (HDL-C) is an established atheroprotective marker, in particular for coronary artery disease; however, HDL particle concentration (HDL-P) may better predict risk. The associations of HDL-C and HDL-P with ischemic stroke and myocardial infarction (MI) among women and Blacks have not been well studied. We hypothesized that HDL-P would consistently be associated with MI and stroke among women and Blacks compared with HDL-C. Methods: We analyzed individual-level participant data in a pooled cohort of 4 large population studies without baseline atherosclerotic cardiovascular disease: DHS (Dallas Heart Study; n=2535), ARIC (Atherosclerosis Risk in Communities; n=1595), MESA (Multi-Ethnic Study of Atherosclerosis; n=6632), and PREVEND (Prevention of Renal and Vascular Endstage Disease; n=5022). HDL markers were analyzed in adjusted Cox proportional hazard models for MI and ischemic stroke. Results: In the overall population (n=15 784), HDL-P was inversely associated with the combined outcome of MI and ischemic stroke, adjusted for cardiometabolic risk factors (hazard ratio [HR] for quartile 4 [Q4] versus quartile 1 [Q1], 0.64 [95% CI, 0.52-0.78]), as was HDL-C (HR for Q4 versus Q1, 0.76 [95% CI, 0.61-0.94]). Adjustment for HDL-C did not attenuate the inverse relationship between HDL-P and atherosclerotic cardiovascular disease, whereas adjustment for HDL-P attenuated all associations between HDL-C and events. HDL-P was inversely associated with the individual end points of MI and ischemic stroke in the overall population, including in women. HDL-P was inversely associated with MI among White participants but not among Black participants (HR for Q4 versus Q1 for Whites, 0.49 [95% CI, 0.35-0.69]; for Blacks, 1.22 [95% CI, 0.76-1.98];P-interaction=0.001). Similarly, HDL-C was inversely associated with MI among White participants (HR for Q4 versus Q1, 0.53 [95% CI, 0.36-0.78]) but had a weak direct association with MI among Black participants (HR for Q4 versus Q1, 1.75 [95% CI, 1.08-2.83];P-interactio

Prospecting environmental mycobacteria: combined molecular approaches reveal unprecedented diversity

Background: Environmental mycobacteria (EM) include species commonly found in various terrestrial and aquatic environments, encompassing animal and human pathogens in addition to saprophytes. Approximately 150 EM species can be separated into fast and slow growers based on sequence and copy number differences of their 16S rRNA genes. Cultivation methods are not appropriate for diversity studies; few studies have investigated EM diversity in soil despite their importance as potential reservoirs of pathogens and their hypothesized role in masking or blocking M. bovis BCG vaccine. Methods: We report here the development, optimization and validation of molecular assays targeting the 16S rRNA gene to assess diversity and prevalence of fast and slow growing EM in representative soils from semi tropical and temperate areas. New primer sets were designed also to target uniquely slow growing mycobacteria and used with PCR-DGGE, tag-encoded Titanium amplicon pyrosequencing and quantitative PCR. Results: PCR-DGGE and pyrosequencing provided a consensus of EM diversity; for example, a high abundance of pyrosequencing reads and DGGE bands corresponded to M. moriokaense, M. colombiense and M. riyadhense. As expected pyrosequencing provided more comprehensive information; additional prevalent species included M. chlorophenolicum, M. neglectum, M. gordonae, M. aemonae. Prevalence of the total Mycobacterium genus in the soil samples ranged from 2.3×107 to 2.7×108 gene targets g−1; slow growers prevalence from 2.9×105 to 1.2×107 cells g−1. Conclusions: This combined molecular approach enabled an unprecedented qualitative and quantitative assessment of EM across soil samples. Good concordance was found between methods and the bioinformatics analysis was validated by random resampling. Sequences from most pathogenic groups associated with slow growth were identified in extenso in all soils tested with a specific assay, allowing to unmask them from the Mycobacterium whole genus, in which, as minority members, they would have remained undetected