Smoothly-Rising Star Formation Histories During the Reionization Epoch

Cosmological hydrodynamic simulations robustly predict that high-redshift galaxy star formation histories (SFHs) are smoothly-rising and vary with mass only by a scale factor. We use our latest simulations to test whether this scenario can account for recent observations at z>=6 from WFC3/IR, NICMOS, and IRAC. Our simulations broadly reproduce the observed ultraviolet (UV) luminosity functions and stellar mass densities and their evolution at z=6-8, all of which are nontrivial tests of the mean SFH. In agreement with observations, simulated galaxies possess blue UV continua owing to young ages (50-150 Myr), low metallicities (0.1-0.5 Zsun), and low dust columns (E(B-V) <= 0.05). Observations imply a near-unity slope in the stellar mass--star formation rate relation at all z=6-8, confirming the prediction that SFH shapes are invariant. Current surveys detect the majority of galaxies with stellar masses exceeding 10^9 Msun and few galaxies less massive than 10^{8.5} Msun, implying that they probe no more than the brightest 30% of the complete star formation and stellar mass densities at z>=6. Finally, we demonstrate that there is no conflict between smoothly-rising SFHs and recent clustering observations. This is because momentum-driven outflows suppress star formation in low-mass halos, leading to overall occupancies of 0.2-0.4 even though the star formation duty cycle is one. This leads to many interesting predictions at z>=4, among them that (1) optically-selected and UV-selected samples largely overlap; (2) few galaxies exhibit significantly suppressed specific star formation rates; and (3) occupancy is constant or increasing with decreasing luminosity. These predictions are in tentative agreement with current observations, but further analysis of existing and upcoming data sets is required in order to test them more thoroughly. (abridged)Comment: 25 pages, 14 figures, accepted to MNRA

Optimal N Application Rates on Switchgrass for Producers and a Biorefinery

13-C-AJFF-UTenn-005This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: Robertson, K.A.; English, B.C.; Clark, C.D.; Thompson, J.M.; Jensen, K.L.; Menard, R.J.; Labb\ue9, N. Optimal N Application Rates on Switchgrass for Producers and a Biorefinery. Energies 2021, 14, 7912. https://doi.org/10.3390/en14237912This study analyzes the effects of N fertilizer application rates on profitability of growing switchgrass and using the feedstock in a pyrolysis biorefinery facility to create a source of sustainable aviation fuel (SAF) supply in Tennessee. Switchgrass (Panicum virgatum L.) is a perennial bunchgrass native to North America with traits suitable for biofuel and co-product production. Previous chemical analysis has shown that ash content in switchgrass is related to the amount of nitrogen applied to the field, while at the biorefinery level, the percentage ash content reduces the biorefinery fuel output. To obtain optimal nitrogen (N) application rates for the switchgrass producers and the biorefinery, a two-part analysis is employed. First, a partial budgeting profitability analysis is conducted for this cropping enterprise at the farm-gate level without considering downstream implications of biomass quality, i.e., ash content. Second, the effects of higher ash content as a percentage of the feedstock on biorefinery output are analyzed. Results show farm-gate profit is maximized when N fertilizer is applied at 111 kg/ha, while as a result of increased production levels and decreased percentage ash content, biorefinery profit is maximized when N is applied at 157 kg/ha. Lower ash could lead to premium prices paid to switchgrass producers if higher quality feedstock were to be demanded as part of an integrated biofuel industry

A Predictive Model of the Oxygen and Heme Regulatory Network in Yeast

Deciphering gene regulatory mechanisms through the analysis of high-throughput expression data is a challenging computational problem. Previous computational studies have used large expression datasets in order to resolve fine patterns of coexpression, producing clusters or modules of potentially coregulated genes. These methods typically examine promoter sequence information, such as DNA motifs or transcription factor occupancy data, in a separate step after clustering. We needed an alternative and more integrative approach to study the oxygen regulatory network in Saccharomyces cerevisiae using a small dataset of perturbation experiments. Mechanisms of oxygen sensing and regulation underlie many physiological and pathological processes, and only a handful of oxygen regulators have been identified in previous studies. We used a new machine learning algorithm called MEDUSA to uncover detailed information about the oxygen regulatory network using genome-wide expression changes in response to perturbations in the levels of oxygen, heme, Hap1, and Co2+. MEDUSA integrates mRNA expression, promoter sequence, and ChIP-chip occupancy data to learn a model that accurately predicts the differential expression of target genes in held-out data. We used a novel margin-based score to extract significant condition-specific regulators and assemble a global map of the oxygen sensing and regulatory network. This network includes both known oxygen and heme regulators, such as Hap1, Mga2, Hap4, and Upc2, as well as many new candidate regulators. MEDUSA also identified many DNA motifs that are consistent with previous experimentally identified transcription factor binding sites. Because MEDUSA's regulatory program associates regulators to target genes through their promoter sequences, we directly tested the predicted regulators for OLE1, a gene specifically induced under hypoxia, by experimental analysis of the activity of its promoter. In each case, deletion of the candidate regulator resulted in the predicted effect on promoter activity, confirming that several novel regulators identified by MEDUSA are indeed involved in oxygen regulation. MEDUSA can reveal important information from a small dataset and generate testable hypotheses for further experimental analysis. Supplemental data are included

Importance of Rhodococcus strains in a bacterial consortium degrading a mixture of hydrocarbons, gasoline, and diesel oil additives revealed by metatranscriptomic analysis

A bacterial consortium (Mix3) composed of microorganisms originating from different environments (soils and wastewater) was obtained after enrichment in the presence of a mixture of 16 hydrocarbons, gasoline, and diesel oil additives. After addition of the mixture, the development of the microbial composition of Mix3 was monitored at three different times (35, 113, and 222 days) using fingerprinting method and dominant bacterial species were identified. In parallel, 14 bacteria were isolated after 113 days and identified. Degradation capacities for Mix3 and the isolated bacterial strains were characterized and compared. At day 113, we induced the expression of catabolic genes in Mix3 by adding the substrate mixture to resting cells and the metatranscriptome was analyzed. After addition of the substrate mixture, the relative abundance of Actinobacteria increased at day 222 while a shift between Rhodococcus and Mycobacterium was observed after 113 days. Mix3 was able to degrade 13 compounds completely, with partial degradation of isooctane and 2-ethylhexyl nitrate, but tert-butyl alcohol was not degraded. Rhodococcus wratislaviensis strain IFP 2016 isolated from Mix3 showed almost the same degradation capacities as Mix3: these results were not observed with the other isolated strains. Transcriptomic results revealed that Actinobacteria and in particular, Rhodococcus species, were major contributors in terms of total and catabolic gene transcripts while other species were involved in cyclohexane degradation. Not all the microorganisms identified at day 113 were active except R. wratislaviensis IFP 2016 that appeared to be a major player in the degradation activity observed in Mix3.Peer reviewed: YesNRC publication: Ye

Characterization of diamond-like carbon by Raman spectroscopy, XPS and optical constants

Crystalline diamond coatings and, increasingly, diamond-like amorphous carbon (DLC) films are used for tribological and protective layers for their hardness and chemical inertness. They are also under investigation for their electron emitting properties, with possible applications in field emission displays. In this study, hydrogen-free DLC films were deposited by laser ablation using a KrF excimer laser and fluences between 0.5 and 2 J/cm2. Information about the disorder and short range order in the films was gained via Raman spectra. As the ratio of graphitic and diamond bonds (sp2 and sp3) is often hidden in these measurements, other analytical methods have to be included. XPS spectra exhibit for certain films the presence of sp3 bonds or graphitic growth. For a better determination of the sp3-content, a correlation with optical properties in the near IR to near UV region was established. These values depended strongly on the substrate temperature and the laser fluence. DLC formation with large sp3 contents could be demonstrated without substrate heating. Vickers hardness values and measurements on the electron emissivity of the films are strongly correlated to the sp3 content and the preparation method of the films.NRC publication: Ye

Ordering and Self-Organization in Nanocrystalline Silicon

The spontaneous formation of organized nanocrystals in semiconductors has been observed during heteroepitaxial growth and chemical synthesis. The ability to fabricate size-controlled silicon nanocrystals encapsulated by insulating SiO2 would be of significant interest to the microelectronics industry. But reproducible manufacture of such crystals is hampered by the amorphous nature of SiO2 and the differing thermal expansion coefficients of the two materials. Previous attempts to fabricate Si nanocrystals failed to achieve control over their shape and crystallographic orientation, the latter property being important in systems such as Si quantum dots. Here we report the self-organization of Si nanocrystals larger than 80 \uc5 into brick-shaped crystallites oriented along the left fence111right fence crystallographic direction. The nanocrystals are formed by the solid-phase crystallization of nanometre-thick layers of amorphous Si confined between SiO2 layers. The shape and orientation of the crystallites results in relatively narrow photoluminescence, whereas isotropic particles produce qualitatively different, broad light emission. Our results should aid the development of maskless, reproducible Si nanofabrication techniques.NRC publication: Ye