Absorber Foam Characterization for Predicting Overall Anechoic Chamber Performance

A new rectangular anechoic chamber (20’L x 10’W x 9’7”H) has been established at California Polytechnic State University (Cal Poly) through donations and financial support from industry and Cal Poly departments and programs. The chamber was designed and constructed by three graduate students as part of their thesis studies to explore and further their understanding of chamber design and antenna measurements. The chamber project has included RF absorber characterization, overall chamber performance assessment, and software development for the coordination of a positioner with a vector network analyzer. This paper presents absorber characterization as a function of incidence angle and orientation to enable an overall chamber performance analysis. Test data at low incidence angles (\u3c 30o) are compared to manufacturer performance curves at normal incidence. The mean response of the measured data indicates a correlation with manufacturer curves. Through ray tracing analysis, the ripple encountered in the test data is used to identify two effective reflection planes indicative of the foam geometry. The measured data are subsequently used to predict overall anechoic chamber performance to within 1dB for a majority of the actual scan data. Details of this analysis and comparisons to actual chamber performance are presented in a companion paper

Determination of the surface charge density of a mercury electrode by extrusion: a new method for correction of the faradaic component

The accurate determination of the surface charge density at the mercury | solution interface by the method of extrusion of mercury drops is impaired by the faradaic current caused by traces of electroactive species. This paper describes a new design of a hanging mercury drop electrode with accurate control of the extruded electrode area, to within 0.1%, together with a new and reliable procedure for correction of the faradaic current. The procedure is based on first obtaining the correction parameters in the presence of increasing amounts of electroactive species and then using these parameters for correction of the faradaic component so as to obtain the surface charge density of the electrode. Implementation of the method with a microcomputer controlled system provides automatic acquisition of corrected electrode charge density values as a function of the electrode potential. The results obtained with this new method are in excellent agreement with those obtained by other methods, as illustrated for aqueous sodium fluoride solution.http://www.sciencedirect.com/science/article/B6TGB-3WS6M1X-4/1/959396100ce50f29fe3e81cc9a42242

The SLUGGS Survey: Calcium Triplet-based Spectroscopic Metallicities for Over 900 Globular Clusters

Although the colour distribution of globular clusters in massive galaxies is well known to be bimodal, the spectroscopic metallicity distribution has been measured in only a few galaxies. After redefining the calcium triplet index-metallicity relation, we use our relation to derive the metallicity of 903 globular clusters in 11 early-type galaxies. This is the largest sample of spectroscopic globular cluster metallicities yet assembled. We compare these metallicities with those derived from Lick indices finding good agreement. In 6 of the 8 galaxies with sufficient numbers of high quality spectra we find bimodality in the spectroscopic metallicity distribution. Our results imply that most massive early-type galaxies have bimodal metallicity, as well as colour, distributions. This bimodality suggests that most massive galaxies early-type galaxies experienced two periods of star formation.Comment: 23 pages, 13 figures. Accepted for publication in MNRAS. For more information about the SLUGGS Survey please see http://sluggs.swin.edu.a

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Prediction of enteric methane production, yield and intensity in dairy cattle using an intercontinental database

Enteric methane (CH4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive and impractical at large scales; therefore, models are commonly used to predict CH4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 production (g/d per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH4 prediction accuracy. The intercontinental database covered Europe (EU), the US (US), Chile (CL), Australia (AU), and New Zealand (NZ). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6, 14.4, and 19.8% for intercontinental, EU, and US regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH4 emission conversion factors for specific regions are required to improve CH4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary NDF concentration, improve the prediction. For enteric CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation

The effect of mission duration on LISA science objectives

The science objectives of the LISA mission have been defined under the implicit assumption of a 4-years continuous data stream. Based on the performance of LISA Pathfinder, it is now expected that LISA will have a duty cycle of ≈0.75 , which would reduce the effective span of usable data to 3 years. This paper reports the results of a study by the LISA Science Group, which was charged with assessing the additional science return of increasing the mission lifetime. We explore various observational scenarios to assess the impact of mission duration on the main science objectives of the mission. We find that the science investigations most affected by mission duration concern the search for seed black holes at cosmic dawn, as well as the study of stellar-origin black holes and of their formation channels via multi-band and multi-messenger observations. We conclude that an extension to 6 years of mission operations is recommended.publishedVersio

Advances in studying brain morphology: the benefits of open-access data

Until recently, neuroimaging data for a research study needed to be collected within one’s own lab. However, when studying inter-individual differences in brain structure, a large sample of participants is necessary. Given the financial costs involved in collecting neuroimaging data from hundreds or thousands of participants, large-scale studies of brain morphology could previously only be conducted by well-funded laboratories with access to MRI facilities and to large samples of participants. With the advent of broad open-access data-sharing initiatives, this has recently changed–here the primary goal of the study is to collect large datasets to be shared, rather than sharing of the data as an afterthought. This paradigm shift is evident as increase in the pace of discovery, leading to a rapid rate of advances in our characterization of brain structure. The utility of open-access brain morphology data is numerous, ranging from observing novel patterns of agerelated differences in subcortical structures to the development of more robust cortical parcellation atlases, with these advances being translatable to improved methods for characterizing clinical disorders (see Figure 1 for an illustration). Moreover, structural MRIs are generally more robust than functional MRIs, relative to potential artifacts and in being not task-dependent, resulting in large potential yields. While the benefits of open-access data have been discussed more broadly within the field of cognitive neuroscience elsewhere (Van Horn and Gazzaniga, 2013; Poldrack and Gorgolewski, 2014; Van Horn and Toga, 2014; Vogelstein et al., 2016; Voytek, 2016; Gilmore et al., 2017), as well as in other fields (Choudhury et al., 2014; Ascoli et al., 2017; Davies et al., 2017), this opinion paper is focused specifically on the implications of open data to brain morphology research

Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota.

SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19