We present a computationally tractable implementation of spectro-perfectionism, a method which minimizes error imparted by spectral extraction. We develop our method in conjunction with a full raw reduction pipeline for the MINiature Exoplanet Radial Velocity Array (MINERVA), capable of performing both optimal extraction and spectro-perfectionism. Although spectro-perfectionism remains computationally expensive, our implementation can extract a MINERVA exposure in approximately 30 minutes. We describe our localized extraction procedure and our approach to point-spread function (PSF) fitting. We compare the performance of both extraction methods on a set of 119 exposures on HD 122064, an RV standard star. Both the optimal extraction and spectro-perfectionism pipelines achieve nearly identical RV precision under a six-exposure chronological binning. We discuss the importance of reliable calibration data for PSF fitting and the potential of spectro-perfectionism for future precise radial velocity exoplanet studies.

We present the discovery of KELT-24 b, a massive hot Jupiter orbiting a bright (V = 8.3 mag, K = 7.2 mag) young F-star with a period of 5.6 days. The host star, KELT-24 (HD 93148), has a T-eff = 6509(-49)(+50) K, a mass of M-* = 1.460(-0.059)(+0.055) M-circle dot, a radius of R-* = 1.506 +/- 0.022 R-circle dot, and an age of 0.78(-0.42)(+0.61) Gyr. Its planetary companion (KELT-24 b) has a radius of R-P = 1.272 +/- 0.021 R-J and a mass of M-P = 5.18(-0.22)(+0.21) M-J, and from Doppler tomographic observations, we find that the planet's orbit is well-aligned to its host star's projected spin axis (lambda = 2.6(-3.6)(+5.1)). The young age estimated for KELT-24 suggests that it only recently started to evolve from the zero-age main sequence. KELT-24 is the brightest star known to host a transiting giant planet with a period between 5 and 10 days. Although the circularization timescale is much longer than the age of the system, we do not detect a large eccentricity or significant misalignment that is expected from dynamical migration. The brightness of its host star and its moderate surface gravity make KELT-24b an intriguing target for detailed atmospheric characterization through spectroscopic emission measurements since it would bridge the current literature results that have primarily focused on lower mass hot Jupiters and a few brown dwarfs.

We leverage state-of-the-art machine learning methods and a decade's worth of archival data from Canada-France-Hawaii Telescope (CFHT) to predict observatory image quality (IQ) from environmental conditions and observatory operating parameters. Specifically, we develop accurate and interpretable models of the complex dependence between data features and observed IQ for CFHT's wide-field camera, MegaCam. Our contributions are several-fold. First, we collect, collate, and reprocess several disparate data sets gathered by CFHT scientists. Second, we predict probability distribution functions of IQ and achieve a mean absolute error of similar to 0.07 arcsec for the predicted medians. Third, we explore the data-driven actuation of the 12 dome 'vents' installed in 2013-14 to accelerate the flushing of hot air from the dome. We leverage epistemic and aleatoric uncertainties in conjunction with probabilistic generative modelling to identify candidate vent adjustments that are in-distribution (ID); for the optimal configuration for each ID sample, we predict the reduction in required observing time to achieve a fixed signal-to-noise ratio. On average, the reduction is similar to 12 per cent. Finally, we rank input features by their Shapley values to identify the most predictive variables for each observation. Our long-term goal is to construct reliable and real-time models that can forecast optimal observatory operating parameters to optimize IQ. We can then feed such forecasts into scheduling protocols and predictive maintenance routines. We anticipate that such approaches will become standard in automating observatory operations and maintenance by the time CFHT's successor, the Maunakea Spectroscopic Explorer, is installed in the next decade.

Water is one of the key limiting factors for the survival and growth of plant species in arid and semi-arid steppe regions. Different plant functional groups (PFGs) based on life-forms differ in their strategies to cope with limited water availability. The foliar carbon isotope discrimination (Delta) value provides an integrated measurement of internal plant physiological and external environmental properties affecting photosynthetic gas exchange over the time interval when the carbon was fixed. In this study, we surveyed the composition and Delta values of various life-forms (shrubs, sub-shrubs, perennial grasses, perennial forbs and annuals) in eight different plant communities along a soil moisture gradient in the Xilin River Basin, Inner Mongolia, China. Our results showed that: (1) life-forms occurred variously in eight steppe communities with different soil moisture status; (2) in wetter habitats, forbs were more abundant and accounted for the majority of aboveground biomass, whereas grasses became more important in drier habitats. Shrubs and sub-shrubs increased with decreasing soil water availability and their relative biomass rapidly increased in degraded steppe and sand dune communities. (3) The numerical order of the mean Delta values of life-forms is as follows: perennial grasses (15.86 parts per thousand) < shrubs (16.10 parts per thousand) < perennial forbs (16.45 parts per thousand) = annuals (16.41 parts per thousand) < sub-shrubs (17.55 parts per thousand), reflecting their differences in water use efficiencies. The significant differences in the Delta values among these life-forms suggested that life-form-based PFGs not only represent a morphological classification of these plants, but could also represent a functional group integrating different physiological processes such as water use strategies, which may partially explain the differences in PFG composition and competitive ability of co-existing species along environmental gradients in the Xilin River Basin.

Brassinosteroid and gibberellin promote many similar developmental responses in plants; however, their relationship remains unclear. Here we show that BR and GA act interdependently through a direct interaction between the BR-activated BZR1 and GA-inactivated DELLA transcription regulators. GA promotion of cell elongation required BR signalling, where as BR or active BZR1 suppressed the GA-defcient dwarf phenotype. DELLAs directly interacted with BZR1 and inhibited BZR1-DNA binding both in vitro and in vivo. Genome-wide analysis defined a BZR1-dependent GA-regulated transcriptome, which is enriched with light-regulated genes and genes involved in cell wall synthesis and photosynthesis/chloroplast function. GA promotion of hypocotyl elongation requires both BZR1 and the phytochrome-interacting factors (PIFs), as well as their common downstream targets encoding the PRE-family helix-loop-helix factors. The results demonstrate that GA releases DELLA-mediated inhibition of BZR1, and that the DELLA-BZR1-PIF4 interaction defines a core transcription module that mediates coordinated growth regulation by GA, BR and light signals.

Aluminum (Al) toxicity in plants is one of the primary constraints in crop production. Al-3, the most toxic form of Al, is released into soil under acidic conditions and causes extensive damage to plants, especially in the roots. In rice, Al tolerance requires the ASR5 gene, but the molecular function of ASR5 has remained unknown. Here, we perform genome-wide analyses to identify ASR5-dependent Al-responsive genes in rice. Based on ASR5_RNAi silencing in plants, a global transcriptome analysis identified a total of 961 genes that were responsive to Al treatment in wild-type rice roots. Of these genes, 909 did not respond to Al in the ASR5_RNAi plants, indicating a central role for ASR5 in Al-responsive gene expression. Under normal conditions, without Al treatment, the ASR5_RNAi plants expressed 1.756 genes differentially compared to the wild-type plants, and 446 of these genes responded to Al treatment in the wild-type plants. Chromatin immunoprecipitation followed by deep sequencing identified 104 putative target genes that were directly regulated by ASR5 binding to their promoters, including the STAR1 gene, which encodes an ABC transporter required for Al tolerance. Motif analysis of the binding peak sequences revealed the binding motif for ASR5, which was confirmed via in vitro DNA-binding assays using the STAR1 promoter. These results demonstrate that ASR5 acts as a key transcription factor that is essential for Al-responsive gene expression and Al tolerance in rice.

Guided by a simple strategy in search of new superconducting materials, we predict that high-temperature superconductivity can be realized in classes of high-density materials having strong sp(3) chemical bonding and high lattice symmetry. We examine in detail sodalite carbon frameworks doped with simple metals such as Li, Na, and Al. Though such materials share some common features with doped diamond, their doping level is not limited, and the density of states at the Fermi level in them can be as high as that in the renowned MgB2. Together with other factors, this boosts the superconducting temperature (T-c) in the materials investigated to higher levels compared to doped diamond. For example, the T-c of sodalitelike NaC6 is predicted to be above 100 K. This phase and a series of other sodalite-based superconductors are predicted to be metastable phases but are dynamically stable. Owing to the rigid carbon framework of these and related dense carbon materials, these doped sodalite-based structures could be recoverable as potentially useful superconductors.

Static pressure is an alternative method to chemical pressure for tuning the crystal structure, bonds, and physical properties of materials, and is a significant technique for the synthesis of novel materials and fundamental research. In this letter, we report the crystallization and phase transformation of p-xylene under high pressure. Our optical micrographic observations and the appearance of lattice modes in the Raman and infrared (IR) spectra indicated that p-xylene crystallizes at similar to 0.1 GPa. The X-ray diffraction (XRD) pattern at 0.84 GPa suggests that the crystallized p-xylene had a monoclinic phase with the Cc(9) space group. The sharp shrinkage of the lattice at similar to 13 GPa and the solid state of the decompressed sample we observed suggests a new crystalline phase of p-xylene. The in situ XRD showed that the new crystalline phase was still a monoclinic structure but with a different space group of C2(5), indicating that a phase transition occurred during further compression. The mass spectrometry experiment confirmed phase transition polymerization, with mainly trimer and tetramer polymers. Our findings suggest an easy and efficient method for crystallizing and polymerizing p-xylene under high pressure.

Zebrafish Liver-enriched gene 1a (Leg1a) and Leg1b are liver-produced serum proteins encoded by two adjacently linked homologous genes leg1a and leg1b, respectively. We previously showed that maternal-zygotic (MZ) leg1a null mutant developed a small liver at 3.5 days post-fertilization (dpf) during winter-time or under UV-treatment and displayed an abnormal stature at its adulthood. It is puzzling why Leg1b, which shares 89.3% identity with Leg1a and co-expressed with Leg1a, cannot fully compensate for the loss-of-function of Leg1a in the leg1a(zju1) MZ mutant. Here we report that Leg1a and Leg1b share eight cysteine residues but differ in amino acid residue 358, which is a serine in Leg1a but cysteine (C-358) in Leg1b. We find that Leg1b forms an intermolecular disulfide bond through C-358. Mutating C-358 to Methionine (M-358) does not affect Leg1b secretion whereas mutating other conserved cysteine residues do. We propose that the intermolecular disulfide bond in Leg1b might establish a rigid structure that makes it functionally different from Leg1a under certain oxidative conditions. (c) 2021 Published by Elsevier Inc.