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We observed slected mutual occultations of Jupiter's satellites in 1990-1991 and we used the occultation profiles to constrain the areal distribution of selected spectrally active compounds on Io's surface.
Mutualism in a Reduced Gravity Environment (MuRGE) is a ground research study to determine the feasibility of assessing fungi-plant (Piriformospora indica-Arabidopsis thaliana) interactions in microgravity. Seeds from the plant Arabiddospsis thaliana (At) will be grown in the presence of Piriformospora indica (Pi) an endophytic Sebacinacae family fungus. Pi is capable of colonizing the roots of a wide variety of plant species, including non-mycorrhizal hosts like At, and promoting plant growth similarly to AMF (arbusuclar mychorrizal fungi) unlike most AMF, Pi is not an obligate plant symbiont and can be grown in the absence of a host. In the presence of a suitable plant host, Pi can attach to and colonize root tips. Interaction visualization is accomplished with strong autofluorescence in the roots, followed by root colonization via fungal hyphae, and chlamydospore production. Increased root growth can be observed even before root colonization is detectable. In addition, Pi chlamydospores generated from axenic culture in microgravity will be used to inoculate roots of At grown in 1g to determine the effect of microgravity upon the inherent virulence or beneficial effects. Based on recent reports of increased virulence of S. typhimurium, P. aeruginosa, and S. Pneumoniae in reduced gravity, differences in microbial pathogenic responses and host plant systemic acquired resistance are expected. The focus of this project within MuRGE involved the development P. indica culture media evaluation and microscopy protocol development. High, clean spore harvest yields for the detection of fungi-plant interactions microscopically was the immediate goal of this experiment.
MuRGE (Mutualism in a Reduced Gravity Environment) is a NASA flight-research experiment to investigate the microgravity effects associated with cell-cell communication and beneficial microbe-host interactions using a plant-fungal model system. This investigation will use a clinostat, an instrument that slowly rotates the plants to negate the effects of gravitational pull on plant growth (gravitropism) and development, to simulate microgravity. I will be using the endophytic fungus Piriformospora indica (Pi) and the model plant species Arabidopsis thaliana (At). P. indica has been shown to colonize roots of various plant species, including A. thaliana, and to increase plant growth and resistance to stress. The fungus has the ability to grow from spores or in axenic cultures without the presence of a host. P. indica spores and P. indica extract will be used to inoculate Arabidopsis seeds germinated on a clinostat in order to determine if simulated microgravity affects the interaction between the fungus and its plant host.
MuRGE (Mutualism in a Reduced Gravity Environment) is a NASA flight-research experiment to investigate the microgravity effects associated with cell-cell communication and beneficial microbe-host interactions using a plant-fungal model system. This investigation will use a clinostat, an instrument that slowly rotates the plants to negate the effects of gravitational pull on plant growth (gravitropism) and development, to simulate microgravity. I will be using the endophytic fungus Piriformospora indica (Pi) and the model plant species Arabidopsis thaliana (At). P. indica has been shown to colonize roots of various plant species, including A. thaliana, and to increase plant growth and resistance to stress. The fungus has the ability to grow from spores or in axenic cultures without the presence of a host. P. indica spores and P. indica extract will be used to inoculate Arabidopsis seeds germinated on a clinostat in order to determine if simulated microgravity affects the interaction between the fungus and its plant host.
An expression for the mutual coherence function (MCF) of an electromagnetic beam wave propagating through atmospheric turbulence is derived within the confines of the Rytov approximation. It is shown that both the first and second Rytov approximations are required. The Rytov MCF is then compared to that which issues from the parabolic equation method of strong fluctuation theory. The agreement is found to be quite good in the weak fluctuation case. However, an instability is observed for the special case of beam wave intensities. The source of the instabilities is identified to be the characteristic way beam wave amplitudes are treated within the Rytov method.
We present a technique for automatically extracting temporal mutual exclusion invariants from PDDL2.2 planning instances. We first identify a set of invariant candidates by inspecting the domain and then check these candidates against properties that assure invariance. If these properties are violated, we show that it is sometimes possible to refine a candidate by adding additional propositions and turn it into a real invariant. Our technique builds on other approaches to invariant synthesis presented in the literature, but departs from their limited focus on instantaneous discrete actions by addressing temporal and numeric domains. To deal with time, we formulate invariance conditions that account for both the entire structure of the operators (including the conditions, rather than just the effects) and the possible interactions between operators. As a result, we construct a technique that is not only capable of identifying invariants for temporal domains, but is also able to find a broader set of invariants for non-temporal domains than the previous techniques.
A new Hubble Space Telescope observation of the 7:4 resonant transneptunian binary system (385446) Manwe has shown that, of two previously reported solutions for the orbit of its satellite Thorondor, the prograde one is correct. The orbit has a period of 110.18 +/- 0.02 days, semimajor axis of 6670 +/- 40 km, and an eccentricity of 0.563 +/- 0.007. It will be viewable edge-on from the inner Solar System during 2015- 2017, presenting opportunities to observe mutual occultation and eclipse events. However, the number of observable events will be small, owing to the long orbital period and expected small sizes of the bodies relative to their separation. This paper presents predictions for events observable from Earth-based telescopes and discusses the associated uncertainties and challenges.
We consider the problem of designing a sensor network to most efficiently locate the source of a seismic event. The left panel of Figure 1 shows 982 possible sensor locations in a region of interest. The objective is to infer the unknown location of an earthquake, indicated by the gold dot for illustration purposes. Assume that three sensors have already been placed for data collection. Travel times of the P-wave from the source to the three sensors are observed and used to infer the unknown source location via a Bayesian statistical model described subsequently. The right panel of Figure 1 shows samples from the resulting posterior distribution for source location along with a posterior estimate of this location.
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Bifacial solar cells hold the potential to achieve a higher power output per unit area than conventional monofacial devices without significantly increasing manufacturing costs. However, efficient bifacial designs are challenging to implement in inorganic thin-film solar cells because of their short carrier lifetimes and high rear surface recombination. The emergence of perovskite photovoltaic (PV) technology creates a golden opportunity to realize efficient bifacial thin-film solar cells, owing to their outstanding optoelectronic properties and unique features of device physics. More importantly, transparent conducting oxide electrodes can prevent electrode corrosion by halide ions, mitigating one major instability issue of the perovskite devices. Here, the theory of bifacial PV devices is summarized and the advantages of bifacial perovskite solar cells, such as high power output, enhanced device durability, and low economic and environmental costs, are reviewed. The limitations and challenges for bifacial perovskite solar cells are also discussed. Lastly, the awareness of bifacial solar cells as a feasible commercialization pathway of perovskite PV for mainstream solar power generation and building-integrated PV is advocated and future research directions are suggested.
Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.
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Amorphous materials distinguish themselves from crystalline materials by lacking long-range order while retaining structural order at the local scale (2–5 Å). However, the complexity in topological and chemical order prevents current characterization tools from fully unveiling the structure in disordered materials. Consequently, the nature of medium-range order in amorphous materials has remained elusive. The Zachariasen and crystal competing models have been proposed to describe disordered phases and have both been verified through synthesis and characterization. The main difference between them is thought to be whether the amorphous phase shows medium-range order. Here we demonstrate a form of organized inorganic matter that is amorphous in two dimensions, while exhibiting long-range order and a high degree of crystallinity in the third. The structure consists of periodically stacked 2-dimensional amorphous Nb-W-O monolayers without long-range in-plane order. The unique periodic and therefore crystalline stacking along one principal axis enables direct imaging and revealed that the amorphous Nb-W-O monolayers formed in agreement with the Zachariasen model for 2 dimensions. Our findings show that the gap between crystalline and amorphous materials does not only depend on medium-range order but can also apply to principal dimensions within the same solid.
Despite the pivotal role of jasmonic acid in the outcome of plant-microorganism interactions, JA-signaling components in roots of perennial trees like western balsam poplar (Populus trichocarpa) are poorly characterized. Here we decipher the poplar-root JA-perception complex centered on PtJAZ6, a co-repressor of JA-signaling targeted by the effector protein MiSSP7 from the ectomycorrhizal basidiomycete Laccaria bicolor during symbiotic development. Through protein–protein interaction studies in yeast we determined the poplar root proteins interacting with PtJAZ6. Moreover, we assessed via yeast triple-hybrid how the mutualistic effector MiSSP7 reshapes the association between PtJAZ6 and its partner proteins. In the absence of the symbiotic effector, PtJAZ6 interacts with the transcription factors PtMYC2s and PtJAM1.1. In addition, PtJAZ6 interacts with it-self and with other Populus JAZ proteins. Finally, MiSSP7 strengthens the binding of PtJAZ6 to PtMYC2.1 and antagonizes PtJAZ6 homo-/heterodimerization. We conclude that a symbiotic effector secreted by a mutualistic fungus may promote the symbiotic interaction through altered dynamics of a JA-signaling-associated protein–protein interaction network, maintaining the repression of PtMYC2.1-regulated genes.
Abstract The hypergraph community detection problem seeks to identify groups of related vertices in hypergraph data. We propose an information-theoretic hypergraph community detection algorithm which compresses the observed data in terms of community labels and community-edge intersections. This algorithm can also be viewed as maximum-likelihood inference in a degree-corrected microcanonical stochastic blockmodel. We perform the compression/inference step via simulated annealing. Unlike several recent algorithms based on canonical models, our microcanonical algorithm does not require inference of statistical parameters such as vertex degrees or pairwise group connection rates. Through synthetic experiments, we find that our algorithm succeeds down to recently-conjectured thresholds for sparse random hypergraphs. We also find competitive performance in cluster recovery tasks on several hypergraph data sets.