Luminosity and surface brightness distribution of K-band galaxies from the UKIDSS Large Area Survey

We present luminosity and surface brightness distributions of 40,111 galaxies with K-band photometry from the United Kingdom Infrared Telescope (UKIRT) Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS), Data Release 3 and optical photometry from Data Release 5 of the Sloan Digital Sky Survey (SDSS). Various features and limitations of the new UKIDSS data are examined, such as a problem affecting Petrosian magnitudes of extended sources. Selection limits in K- and r-band magnitude, K-band surface brightness and K-band radius are included explicitly in the 1/Vmax estimate of the space density and luminosity function. The bivariate brightness distribution in K-band absolute magnitude and surface brightness is presented and found to display a clear luminosity--surface brightness correlation that flattens at high luminosity and broadens at low luminosity, consistent with similar analyses at optical wavelengths. Best fitting Schechter function parameters for the K-band luminosity function are found to be M*-5 log h=-23.19 +/- 0.04, alpha=-0.81 +/- 0.04 and phi*=(0.0166 +/- 0.0008)h^3 Mpc^{-3}, although the Schechter function provides a poor fit to the data at high and low luminosity, while the luminosity density in the K band is found to be j = (6.305 +/- 0.067) x 10^8 L_sun h Mpc^{-3}. However, we caution that there are various known sources of incompleteness and uncertainty in our results. Using mass-to-light ratios determined from the optical colours we estimate the stellar mass function, finding good agreement with previous results. Possible improvements are discussed that could be implemented when extending this analysis to the full LAS.Comment: 17 pages, 24 figures, matches MNRAS accepted versio

Increased Productivity of a Cover Crop Mixture Is Not Associated with Enhanced Agroecosystem Services

Cover crops provide a variety of important agroecological services within cropping systems. Typically these crops are grown as monocultures or simple graminoid-legume bicultures; however, ecological theory and empirical evidence suggest that agroecosystem services could be enhanced by growing cover crops in species-rich mixtures. We examined cover crop productivity, weed suppression, stability, and carryover effects to a subsequent cash crop in an experiment involving a five-species annual cover crop mixture and the component species grown as monocultures in SE New Hampshire, USA in 2011 and 2012. The mean land equivalent ratio (LER) for the mixture exceeded 1.0 in both years, indicating that the mixture over-yielded relative to the monocultures. Despite the apparent over-yielding in the mixture, we observed no enhancement in weed suppression, biomass stability, or productivity of a subsequent oat (Avena sativa L.) cash crop when compared to the best monoculture component crop. These data are some of the first to include application of the LER to an analysis of a cover crop mixture and contribute to the growing literature on the agroecological effects of cover crop diversity in cropping systems

Cultivar diversity as a means of ecologically intensifying dry matter production in a perennial forage stand

The relationship between genotypic diversity and productivity has not been adequately explored in perennial forage production systems despite strong theoretical and empirical evidence supporting diversity\u27s role in ecosystem functioning in other managed and unmanaged systems. We conducted a two-year field experiment with six cultivars of an agriculturally important forage grass, Lolium perenne L. (perennial ryegrass). Dry matter production of L. perenne and the weed community that emerged from the soil seed bank were measured each year in treatments that ranged from cultivar monocultures to three- and six-way cultivar mixtures, all sown at a constant seeding rate. Mean L. perenne dry matter production increased with increasing cultivar diversity and was highest in mixtures that contained cultivars representing the greatest additive trait range (calculated on rankings of three traits: winter hardiness, heading date, and tolerance to grazing). Mixtures had greater yields than those predicted by the mean of their component monoculture yields, but there was evidence that highly productive cultivars may have dampened over-yielding in mixtures. Weed abundance was correlated with L. perenne dry matter, but not L. perenne cultivar diversity. These results suggest that multi-cultivar mixtures may have utility as an approach to ecologically intensifying perennial forage production. Additional research will be necessary to determine the mechanisms responsible for the over-yielding observed in this study and the generality of these findings

Radio frequency dataset collection system development for location and device fingerprinting

Radio-frequency (RF) fingerprinting is a process that uses the minute inconsistencies among manufactured radio transmitters to identify wireless devices. Coupled with location fingerprinting, which is a machine learning technique to locate devices based on their radio signals, it can uniquely identify and locate both trusted and rogue wireless devices transmitting over the air. This can have wide-ranging applications for the Internet of Things, security, and networking fields. To contribute to this effort, this research first builds a software-defined radio (SDR) testbed to collect an RF dataset over LTE and WiFi channels. The developed testbed consists of both hardware which are receivers with multiple antennas and software which performs signal preprocessing. Several features that can be used for RF device fingerprinting and location fingerprinting, including received signal strength indicator and channel state information, are also extracted from the signals. With the developed dataset, several data-driven machine learning algorithms have been implemented and tested for fingerprinting performance evaluation. Overall, experimental results show promising performance with a radio fingerprinting accuracy above 90\% and device localization within 1.10 meters

Hydrodynamic controls on alluvial ridge construction and avulsion likelihood in meandering river floodplains

This is the author accepted manuscript. The final version is available from Geological Society of America via the DOI in this record.Existing models of alluvial stratigraphy often neglect the hydrodynamic controls on channel belt and floodplain sedimentation, and predict avulsion using topographic metrics, such as channel belt super-elevation (the ratio of alluvial ridge height to channel depth). This study provides a first demonstration of the potential for simulating long-term river floodplain evolution (over >500 floods) using a process-based hydrodynamic model. Simulations considered alluvial ridge construction during the period leading up to an avulsion, and assess the controls on avulsion likelihood. Results illustrate that the balance between within-channel and overbank sedimentation exerts a key control on both super-elevation ratios and on the conveyance of water and sediment to the floodplain. Rapid overbank sedimentation creates high alluvial ridges with deep channels, leading to lower apparent super-elevation ratios, and implying a reduced likelihood of avulsion. However, channel deepening also drives a reduction in channel belt–floodplain connectivity, so that conveyance of water to the distal floodplain is concentrated in a declining number of channel breaches, which may favor avulsion. These results suggest that, while super-elevation ratios in excess of a threshold value may be a necessary condition for a meandering river avulsion, the likelihood of avulsion may not be greatest where the super-elevation ratio is maximized. Instead, optimal conditions for avulsion may depend on channel-floodplain hydrodynamic connectivity, determined by the balance between coarse (channel bed–forming) and fine (floodplain-constructing) sediment delivery. These results highlight a need to rethink the representation of avulsion in existing models of alluvial architecture.This work was funded by UK Natural Environment Research Council grants NE/H009108/1 and NE/H007288/1

Association of plasma uric acid with ischaemic heart disease and blood pressure: mendelian randomisation analysis of two large cohorts

Objectives: To assess the associations between both uric acid levels and hyperuricaemia, with ischaemic heart disease and blood pressure, and to explore the potentially confounding role of body mass index. Design: Mendelian randomisation analysis, using variation at specific genes (SLC2A9 (rs7442295) as an instrument for uric acid; and FTO (rs9939609), MC4R (rs17782313), and TMEM18 (rs6548238) for body mass index). Setting: Two large, prospective cohort studies in Denmark. Participants: We measured levels of uric acid and related covariables in 58 072 participants from the Copenhagen General Population Study and 10 602 from the Copenhagen City Heart Study, comprising 4890 and 2282 cases of ischaemic heart disease, respectively. Main outcome: Blood pressure and prospectively assessed ischaemic heart disease. Results: Estimates confirmed known observational associations between plasma uric acid and hyperuricaemia with risk of ischaemic heart disease and diastolic and systolic blood pressure. However, when using genotypic instruments for uric acid and hyperuricaemia, we saw no evidence for causal associations between uric acid, ischaemic heart disease, and blood pressure. We used genetic instruments to investigate body mass index as a potentially confounding factor in observational associations, and saw a causal effect on uric acid levels. Every four unit increase of body mass index saw a rise in uric acid of 0.03 mmol/L (95% confidence interval 0.02 to 0.04), and an increase in risk of hyperuricaemia of 7.5% (3.9% to 11.1%). Conclusion: By contrast with observational findings, there is no strong evidence for causal associations between uric acid and ischaemic heart disease or blood pressure. However, evidence supports a causal effect between body mass index and uric acid level and hyperuricaemia. This finding strongly suggests body mass index as a confounder in observational associations, and suggests a role for elevated body mass index or obesity in the development of uric acid related conditions

Nuclear and Metabolic Quantification for Enhanced Ductal Carcinoma In Situ Risk Stratification

Ductal carcinoma in situ (DCIS) is currently considered an early and localized form of ductal breast cancer stemming from the epithelial ductal cells. These lesions are largely heterogenous, categorized by their morphologies, amount of necrosis, and stromal changes. Even though 10-year mortality rate for DCIS is 1-2.6% while that of early invasive breast cancer is 7-10%. Yet, current recommended treatment for DCIS is breast-conserving surgery and radiation or mastectomy – the same treatment regimen recommended for early invasive breast cancer. This assumes that all DCIS will progress to invasive breast cancer if left untreated. However, mounting evidence indicates that a significant number of DCIS would remain indolence and never progress to invasive cancer. Current risk stratification is based on grade and hormone receptor (estrogen and progesterone) status. While the underlying mechanisms for DCIS to invasive cancer progression are not well understood, an improvement in the quantification of cellular morphology, the extracellular matrix and the metabolism modification of the tumor microenvironment could provide a more accurate and objective prognostication and treatment recommendations. DCIS is currently graded manually by a surgical pathologist using a representative number of areas on the slide. This risks grading bias between different pathologists. By using an automated software to measure quantifiable attributes such as nuclear density, size, and degree of variation of all areas of DCIS on the slide, we can have a more uniform and objective scoring system that would have minimal bias and variation. In addition, we will quantify heterogeneity of collagen arrangement, collagen fiber profile in the stroma as well as the metabolic modifications in the tumor microenvironment of “low risk” vs “high risk” DCIS to determine factors that could provide us with a better prognostication system.https://digitalcommons.unmc.edu/surp2022/1032/thumbnail.jp

Fixed Versus Random Sampling Designs in Small South Dakota Glacial Lakes

Choice of sampling design is fundamental when planning surveys to monitor fisheries resources. However, little is known about the impact that different sampling designs may have on commonly collected fish population metrics used to index relative abundance, size structure, and diversity in small (\u3c200 ha) glacial lakes. To address this issue, we sampled three small glacial lakes in eastern South Dakota with modified fyke nets and gill nets at fixed sites used by South Dakota Game, Fish and Parks and a complement of nets at randomized sites. Catch per unit effort (CPUE), proportional size distribution (PSD), and PSD-preferred (PSD-P) were compared between fixed and random designs for each species and gear by lake while Bray-Curtis distances were calculated between sample designs for each gear type in each lake. Precision of CPUE estimates for routinely indexed species were calculated for both gears used by each sampling design. No consistent bias in calculated population metrics was detected between sampling designs for any species collected with either gear type in the three lakes. Sampling precision of CPUE estimates were low for both gears and study designs; though randomized sites tended to yield lower precision. Power analyses indicated that current levels of sampling effort are insufficient to detect differences in CPUE or PSD/PSD-P between fixed and random sampling designs. In addition to being small, study lakes had relatively homogenous habitat allowing for effective sampling resulting in similar values of CPUE and PSD/PSD-P for both fixed and random study designs, and high assemblage overlap. We conclude that fixed sampling sites provide adequate representation of fish communities in small glacial lakes and are sufficient for monitoring temporal changes in these small, but numerous, systems