Physical Characterization of Warm Spitzer-observed Near-Earth Objects

Near-infrared spectroscopy of Near-Earth Objects (NEOs) connects diagnostic spectral features to specific surface mineralogies. The combination of spectroscopy with albedos and diameters derived from thermal infrared observations can increase the scientific return beyond that of the individual datasets. To that end, we have completed a spectroscopic observing campaign to complement the ExploreNEOs Warm Spitzer program that obtained albedos and diameters of nearly 600 NEOs (Trilling et al. 2010). Here we present the results of observations using the low-resolution prism mode (~0.7-2.5 microns) of the SpeX instrument on the NASA Infrared Telescope Facility (IRTF). We also include near-infrared observations of ExploreNEOs targets from the MIT-UH-IRTF Joint Campaign for Spectral Reconnaissance. Our dataset includes near-infrared spectra of 187 ExploreNEOs targets (125 observations of 92 objects from our survey and 213 observations of 154 objects from the MIT survey). We identify a taxonomic class for each spectrum and use band parameter analysis to investigate the mineralogies for the S-, Q-, and V-complex objects. Our analysis suggests that for spectra that contain near-infrared data but lack the visible wavelength region, the Bus-DeMeo system misidentifies some S-types as Q-types. We find no correlation between spectral band parameters and ExploreNEOs albedos and diameters. We find slightly negative Band Area Ratio (BAR) correlations with phase angle for Eros and Ivar, but a positive BAR correlation with phase angle for Ganymed. We find evidence for spectral phase reddening for Eros, Ganymed, and Ivar. We identify the likely ordinary chondrite type analog for a subset of our sample. Our resulting proportions of H, L, and LL ordinary chondrites differ from those calculated for meteorite falls and in previous studies of ordinary chondrite-like NEOs.Comment: 6 Tables, 9 Figure

Metabolic engineering of \u3ci\u3eEscherichia coli\u3c/i\u3e for the \u3ci\u3ede novo\u3c/i\u3e stereospecific biosynthesis of 1,2-propanediol through lactic acid

1,2-propanediol (1,2-PDO) is an industrial chemical with a broad range of applications, such as the production of alkyd and unsaturated polyester resins. It is currently produced as a racemic mixture from nonrenewable petroleum-based feedstocks. We have reported a novel artificial pathway for the biosynthesis of 1,2-PDO via lactic acid isomers as the intermediates. The pathway circumvents the cytotoxicity issue caused by methylglyoxal intermediate in the naturally existing pathway. Successful E. coli bioconversion of lactic acid to 1,2-PDO was shown in previous report. Here, we demonstrated the engineering of E. coli host strains for the de novo biosynthesis of 1,2-PDO through this pathway. Under fermenter-controlled conditions, the R-1,2-PDO was produced at 17.3 g/L with a molar yield of 42.2% from glucose, while the S-isomer was produced at 9.3 g/L with a molar yield of 23.2%. The optical purities of the two isomers were 97.5% ee (R) and 99.3% ee (S), respectively. To the best of our knowledge, these are the highest titers of 1,2-PDO biosynthesized by either natural producer or engineered microbial strains that are published in peer-reviewed journals

High-quality genome-scale metabolic modelling of \u3ci\u3ePseudomonas putida\u3c/i\u3e highlights its broad metabolic capabilities

Genome-scale reconstructions of metabolism are computational species-specific knowledge bases able to compute systemic metabolic properties. We present a comprehensive and validated reconstruction of the biotechnologically relevant bacterium Pseudomonas putida KT2440 that greatly expands computable predictions of its metabolic states. The reconstruction represents a significant reactome expansion over available reconstructed bacterial metabolic networks. Specifically, iJN1462 (i) incorporates several hundred additional genes and associated reactions resulting in new predictive capabilities, including new nutrients supporting growth; (ii) was validated by in vivo growth screens that included previously untested carbon (48) and nitrogen (41) sources; (iii) yielded gene essentiality predictions showing large accuracy when compared with a knock-out library and Bar-seq data; and (iv) allowed mapping of its network to 82 P. putida sequenced strains revealing functional core that reflect the large metabolic versatility of this species, including aromatic compounds derived from lignin. Thus, this study provides a thoroughly updated metabolic reconstruction and new computable phenotypes for P. putida, which can be leveraged as a first step toward understanding the pan metabolic capabilities of Pseudomonas

Vision-Based Close Formation Flight of Unmanned Aerial Vehicles (UAVs)

Since cost of unmanned aircraft vehicles have decreased recently due to technological advancement, there has been a growing interest in developing and implementing systems for close formation missions. Our research objective is to investigate and implement low-cost vision-based tracking algorithms for such a flight formation. For the first technical objective (TO), we are developing an algorithm for vision-based tracking using a Raspberry-Pi hardware. For the second TO, we assembled a quadcopter to be equipped with a camera module and a calibrated flight control computer. In addition, the research team has performed flight testing to obtain video data of a flying marked quadcopter as a reference for developing the tracking algorithm. The final TO is to test-fly two quadcopters in close formation using vision-based tracking algorithm. Ultimately, this research will provide a reliable platform to further investigate formation flight capabilities, and to extrapolate the technology to a wide range of applications

Fire history reconstruction in grassland ecosystems: amount of charcoal reflects local area burned

Citation: Leys, B., Brewer, S. C., McConaghy, S., Mueller, J., & McLauchlan, K. K. (2015). Fire history reconstruction in grassland ecosystems: amount of charcoal reflects local area burned. Environmental Research Letters, 10(11), 114009. https://doi.org/10.1088/1748-9326/10/11/114009Fire is one of the most prevalent disturbances in the Earth system, and its past characteristics can be reconstructed using charcoal particles preserved in depositional environments. Although researchers know that fires produce charcoal particles, interpretation of the quantity or composition of charcoal particles in terms of fire source remains poorly understood. In this study, we used a unique four-year dataset of charcoal deposited in traps from a native tallgrass prairie in mid-North America to test which environmental factors were linked to charcoal measurements on three spatial scales. We investigated small and large charcoal particles commonly used as a proxy of fire activity at different spatial scales, and charcoal morphotypes representing different types of fuel. We found that small (125–250 μ m) and large (250 μ m–1 mm) particles of charcoal are well-correlated (Spearman correlation = 0.88) and likely reflect the same spatial scale of fire activity in a system with both herbaceous and woody fuels. There was no significant relationship between charcoal pieces and fire parameters <500 m from the traps. Moreover, local area burned (<5 km distance radius from traps) explained the total charcoal amount, and regional burning (200 km radius distance from traps) explained the ratio of non arboreal to total charcoal (NA/ T ratio). Charcoal variables, including total charcoal count and NA/ T ratio, did not correlate with other fire parameters, vegetation cover, landscape, or climate variables. Thus, in long-term studies that involve fire history reconstructions, total charcoal particles, even of a small size (125–250 μ m), could be an indicator of local area burned. Further studies may determine relationships among amount of charcoal recorded, fire intensity, vegetation cover, and climatic parameters

A quick guide for student-driven community genome annotation

High quality gene models are necessary to expand the molecular and genetic tools available for a target organism, but these are available for only a handful of model organisms that have undergone extensive curation and experimental validation over the course of many years. The majority of gene models present in biological databases today have been identified in draft genome assemblies using automated annotation pipelines that are frequently based on orthologs from distantly related model organisms. Manual curation is time consuming and often requires substantial expertise, but is instrumental in improving gene model structure and identification. Manual annotation may seem to be a daunting and cost-prohibitive task for small research communities but involving undergraduates in community genome annotation consortiums can be mutually beneficial for both education and improved genomic resources. We outline a workflow for efficient manual annotation driven by a team of primarily undergraduate annotators. This model can be scaled to large teams and includes quality control processes through incremental evaluation. Moreover, it gives students an opportunity to increase their understanding of genome biology and to participate in scientific research in collaboration with peers and senior researchers at multiple institutions

How Best to Hunt a Mammoth - Toward Automated Knowledge Extraction From Graphical Research Models

In the Information Systems (IS) discipline, central contributions of research projects are often represented in graphical research models, clearly illustrating constructs and their relationships. Although thousands of such representations exist, methods for extracting this source of knowledge are still in an early stage. We present a method for (1) extracting graphical research models from articles, (2) generating synthetic training data for (3) performing object detection with a neural network, and (4) a graph reconstruction algorithm to (5) storing results into a designated research model format. We trained YOLOv7 on 20,000 generated diagrams and evaluated its performance on 100 manually reconstructed diagrams from the Senior Scholars\u27 Basket. The results for extracting graphical research models show a F1-score of 0.82 for nodes, 0.72 for links, and an accuracy of 0.72 for labels, indicating the applicability for supporting the population of knowledge repositories contributing to knowledge synthesi

Infrared Lightcurves of Near Earth Objects

We present lightcurves and derive periods and amplitudes for a subset of 38 near earth objects (NEOs) observed at 4.5 microns with the IRAC camera on the the Spitzer Space Telescope, many of them having no previously reported rotation periods. This subset was chosen from about 1800 IRAC NEO observations as having obvious periodicity and significant amplitude. For objects where the period observed did not sample the full rotational period, we derived lower limits to these parameters based on sinusoidal fits. Lightcurve durations ranged from 42 to 544 minutes, with derived periods from 16 to 400 minutes. We discuss the effects of lightcurve variations on the thermal modeling used to derive diameters and albedos from Spitzer photometry. We find that both diameters and albedos derived from the lightcurve maxima and minima agree with our previously published results, even for extreme objects, showing the conservative nature of the thermal model uncertainties. We also evaluate the NEO rotation rates, sizes, and their cohesive strengths.Comment: 16 pages, 4 figures, 3 tables, to appear in the Astrophysical Journal Supplement Serie

The Discovery of Cometary Activity in Near-Earth Asteroid (3552) Don Quixote

The near-Earth object (NEO) population, which mainly consists of fragments from collisions between asteroids in the main asteroid belt, is thought to include contributions from short-period comets as well. One of the most promising NEO candidates for a cometary origin is near-Earth asteroid (3552) Don Quixote, which has never been reported to show activity. Here we present the discovery of cometary activity in Don Quixote based on thermal-infrared observations made with the Spitzer Space Telescope in its 3.6 and 4.5 {\mu}m bands. Our observations clearly show the presence of a coma and a tail in the 4.5 {\mu}m but not in the 3.6 {\mu}m band, which is consistent with molecular band emission from CO2. Thermal modeling of the combined photometric data on Don Quixote reveals a diameter of 18.4 (-0.4/+0.3) km and an albedo of 0.03 (-0.01/+0.02), which confirms Don Quixote to be the third-largest known NEO. We derive an upper limit on the dust production rate of 1.9 kg s^-1 and derive a CO2 gas production rate of (1.1+-0.1)10^26 molecules s^-1. Spitzer IRS spectroscopic observations indicate the presence of fine-grained silicates, perhaps pyroxene rich, on the surface of Don Quixote. Our discovery suggests that CO2 can be present in near-Earth space over a long time. The presence of CO2 might also explain that Don Quixote's cometary nature remained hidden for nearly three decades.Comment: 40 pages, 8 figures, accepted by Ap