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Convective inhibition with an ocean
No full textAims. In this work we generalize the notion of convective inhibition to apply it to cases where there is an infinite reservoir of condensible species (i.e., an ocean). We propose a new model for the internal structure and thermal evolution of super-Earths with hydrogen envelopes.
Methods. We derive the criterion for convective inhibition in a generalized phase mixture from first principles thermodynamics. We then investigate the global ocean case using a water-hydrogen system, for which we have data, as an example. After illustrating the relevant thermodynamics, we extend our arguments to apply to a system of hydrogen and silicate vapor. We then employ a simple atmospheric model to apply our findings to super-Earths and to make predictions about their internal structures and thermal evolution.
Results. For hydrogen envelope masses roughly in the range 10⁻³−10⁻¹ M_⊕, convective contact between the envelope and core may shut down because of the compositional gradient that arises from silicate partial vaporization. For envelope hydrogen masses that cause the associated basal pressure to exceed the critical pressure of pure silicate (on the order of a couple kilobars), the base of that envelope and the top of the core lie on the critical line of the two-phase hydrogen-silicate phase diagram. The corresponding temperature is much higher than convective models would suggest. The core is then “supercritical” in the sense that the temperature exceeds the critical temperature for pure silicate. The core then cools inefficiently, with intrinsic heat fluxes potentially comparable to the Earth’s internal heat flux today.
Conclusions. This low heat flux may allow the core to remain in a high entropy supercritical state for billions of years, but the details of this depend on the nature of the two-component phase diagram at high pressure, something that is currently unknown. A supercritical core thermodynamically permits the dissolution of large quantities of hydrogen into the core
Discriminative Few Shot Learning of Facial Dynamics in Interview Videos for Autism Trait Classification
No full textAutism is a prevalent neurodevelopmental disorder characterized by impairments in social and communicative behaviors. The possible connections between autism and facial expression recognition have been studied in the literature recently. However, most works are based on facial images or short videos. Few works aim at Autism Diagnostic Observation Schedule (ADOS) videos due to their complexity (e.g., interaction between interviewer and interviewee) and length (e.g., usually last for hours). In this paper, we attempt to fill this gap by developing a novel discriminative few shot learning method to analyze hour-long video data and exploring the fusion of facial dynamics for the trait classification of ASD. Leveraging well-established computer vision tools from spatio-temporal feature extraction and marginal fisher analysis to few-shot learning and scene-level fusion, we have constructed a three-category system to classify an individual into Autism, Autism Spectrum, and Non-Spectrum. For the first time, we have shown that certain interview scenes carry more discriminative information for ASD trait classification than others. Experimental results are reported to demonstrate the potential of the proposed automatic ASD trait classification system (reaching 91.72% accuracy on Caltech ADOS video dataset) and the benefits of few-shot learning and scene-level fusion strategy by extensive ablation studies
Indolactam Dipeptides as Nanomolar Gli Inhibitors
No full textThe Gli transcription factors within the Hedgehog (Hh) signaling pathway play essential roles in human development. However, the reactivation of Gli proteins in adult tissue is tumorigenic and drives the progression of several cancers, including the majority of basal cell carcinomas. Here we describe a novel set of indolactam dipeptides that target protein kinase C (PKC), exploiting the unique capacity of PKC isozymes to act as regulators of Gli. We devised an efficient synthetic route for the indolactam-based natural product (−)-pendolmycin and a series of analogues, and we evaluated these analogues in mechanistically distinct Gli reporter assays. The lead compound from these studies, N-hexylindolactam V, exhibits superior Gli suppression relative to clinical inhibitors and blocks the growth of Gli-dependent basal cell carcinoma cells. More broadly, our structure–activity studies provide inroads for the development of novel Gli antagonists and new avenues for combating Gli-driven cancers
Discovery of 34 Low-mass Comoving Systems Using NOIRLab Source Catalog DR2
No full textWe present the discovery of 34 comoving systems containing an ultracool dwarf found by means of the NOIRLab Source Catalog (NSC) DR2. NSC’s angular resolution of ∼ 1″ allows for the detection of small separation binaries with significant proper motions. We used the catalog’s accurate proper motion measurements to identify the companions by cross-matching a previously compiled list of brown dwarf candidates with NSC DR2. The comoving pairs consist of either a very low-mass star and an ultracool companion, or a white dwarf and an ultracool companion. The estimated spectral types of the primaries are in the K and M dwarf regimes, those of the secondaries in the M, L, and T dwarf regimes. We calculated angular separations between ∼2″ and ∼ 56″, parallactic distances between ∼43 and ∼261 pc, and projected physical separations between ∼169 and ∼8487 au. The lowest measured total proper motion is 97 mas yr⁻¹, with the highest 314 mas yr⁻¹. Tangential velocities range from ∼23 to ∼187 km s⁻¹. We also determined comoving probabilities, estimated mass ratios, and calculated binding energies for each system. We found no indication of possible binarity for any component of the 34 systems in the published literature. The discovered systems can contribute to the further study of the formation and evolution of low-mass systems as well as to the characterization of cool substellar objects
Anaerobic single particle cryoEM of nitrogenase
No full textThe enzyme nitrogenase catalyzes the reduction of dinitrogen to ammonia during biological nitrogen fixation through a mechanism involving the ATP dependent interaction of two component proteins adopting multiple conformational states. To date, high resolution structural information has been provided by X-ray crystallography, which restricts the states that can be accessed to those that can be crystallized. Cryo-electron microscopy (cryoEM) presents a new opportunity for structural characterization of nitrogenase solution structures, and may yield new information on the mechanism of nitrogenase by revealing structures of transient or heterogeneous states. In this study, we present single particle cryoEM structures of the MoFe-nitrogenase endogenously isolated from Azotobacter vinelandii. To maintain the fully reduced cluster states of this oxygen sensitive protein, we prepared samples within an anaerobic chamber and employed specialized conditions to minimize partial disordering of the α-subunit at the air-water interface during freezing. Under these conditions, cryoEM structures of the as-isolated MoFe-protein and stabilized MoFe-protein-Fe-protein ADP-AlF4-complex were generally found to closely resemble their corresponding X-ray crystallographic structures. The cryoEM structures did reveal disordering in regions of the MoFe-protein α-subunit reminiscent of that observed previously for the ΔnifB MoFe-protein lacking the FeMo-cofactor, suggesting that this disorder may reflect functionally relevant dynamics, as well as the possibility of asymmetric binding of the Fe-protein to the MoFe-protein in solution. The methods presented here pave the way toward the capture and interrogation of turnover-relevant nitrogenase states by cryoEM
Boron concentrations and isotopic compositions in methane-derived authigenic carbonates: Constraints and limitations in reconstructing formation conditions
No full textThe boron content and isotopic composition (δ¹¹B), of marine carbonates have the potential to constrain CO₂ chemistry during carbonate growth conditions. However, obtaining and interpreting boron compositions from authigenic carbonates in geological archives present several challenges that may substantially limit their application. In particular, contamination from non-carbonate phases during sample preparation must be carefully avoided, and a variety of controls on boron composition during authigenic growth conditions must be evaluated. To advance understanding of the use and limitations of boron in authigenic carbonates, we present data and modelling results on methane-derived authigenic carbonate (MDAC), a by-product of microbially mediated anaerobic oxidation of methane, taken from three cold seep sites along the Norwegian margin. We present a novel sequential leaching method to isolate the boron signals from the micritic (Mg-calcite) and cavity-filling (aragonitic) MDAC cements in these complex multi-phase samples. This method successfully minimizes contamination from non-carbonate phases. To investigate the factors that could potentially contribute to the observed boron signals, we construct a numerical model to simulate the evolution of MDAC δ¹¹B and B/Ca ratios over its growth history. We show that diagenetic fluid composition, depths of precipitation, the physical properties of sediments (such as porosity), and mineral surface kinetics all contribute to the observed boron compositions in the different carbonate cements. While broad constraints may be placed on fluid composition, the multiple competing controls on boron in these diagenetic settings limit the ability to place unique solutions on fluid CO₂ chemistry using boron in these authigenic carbonates
A fast rapidly convergent method for approximation of convolutions with applications to wave scattering and some other problems
No full textIn this article, we discuss an O(N log N) rapidly convergent algorithm for the numerical approximation of the convolution integral with weakly singular kernels and compactly supported densities with possible jump discontinuities. To achieve the reduced computational complexity, we utilize the Fast Fourier Transform (FFT) on a uniform grid of size N for approximating the convolution. To facilitate this and maintain the accuracy, we primarily rely on a periodic Fourier extension of the density with a suitably large period depending on the support of the density. While the method's convergence rate improves with increasing smoothness of the periodic extension and, in fact, approximations exhibit super-algebraic convergence when the extension is infinitely differentiable, it converges only linearly when the density has jump discontinuities. In this context, we present two different procedures to enhance the convergence speed. Firstly, we utilize a certain Fourier smoothing technique to accelerate the convergence to achieve the quadratic rate in the overall approximation. Finally, to make the method truly high order, we augment the basic scheme by including a “thin” boundary grid and employing a specialized high-order boundary integrator. We validate its performance in terms of accuracy as well as computational efficiency through a variety of numerical experiments. In particular, to demonstrate the method's utility, we apply the integration scheme for the numerical solution of certain partial differential equations. Moreover, we also apply the quadrature to obtain a fast and high-order Nyström solver for the solution of the Lippmann-Schwinger integral equation
Trans-epithelial fluid flow and mechanics of epithelial morphogenesis
No full textActive fluid transport across epithelial monolayers is emerging as a major driving force of tissue morphogenesis in a variety of healthy and diseased systems, as well as during embryonic development. Cells use directional transport of ions and osmotic gradients to drive fluid flow across the cell surface, in the process also building up fluid pressure. The basic physics of this process is described by the osmotic engine model, which also underlies actin-independent cell migration. Recently, the trans-epithelial fluid flux and the hydraulic pressure gradient have been explicitly measured for a variety of cellular and tissue model systems across various species. For the kidney, it was shown that tubular epithelial cells behave as active mechanical fluid pumps: the trans-epithelial fluid flux depends on the hydraulic pressure difference across the epithelial layer. When a stall pressure is reached, the fluid flux vanishes. Hydraulic forces generated from active fluid pumping are important in tissue morphogenesis and homeostasis, and could also underlie multiple morphogenic events seen in other developmental contexts. In this review, we highlight findings that examined the role of trans-epithelial fluid flux and hydraulic pressure gradient in driving tissue-scale morphogenesis. We also review organ pathophysiology due to impaired fluid pumping and the loss of hydraulic pressure sensing at the cellular scale. Finally, we draw an analogy between cellular fluidic pumps and a connected network of water pumps in a city. The dynamics of fluid transport in an active and adaptive network is determined globally at the systemic level, and transport in such a network is best when each pump is operating at its optimal efficiency
LQG modeling and GA control of structures subjected to earthquakes
No full textThis paper addresses the stochastic control problem of robots within the framework of parameter uncertainty and uncertain noise covariance. First of all, an open circle deterministic trajectory optimization issue is explained without knowing the unequivocal type of the dynamical framework. Then, a Linear Quadratic Gaussian (LQG) controller is intended for the ostensible trajectory-dependent linearized framework, to such an extent that robust hereditary NN robotic controller made out of the Kalman filter and the fuzzy controller is blended to ensure the asymptotic stability of the non-continuous controlled frameworks. Applicability and performance of the proposed algorithm shown through simulation results in the complex systems which are demonstrate the feasible to improve the performance by the proposed approach
Imagination and the prosocial personality: Mapping the effect of episodic simulation on helping across prosocial traits
No full textPrior work suggests that imagining helping others increases prosocial intentions and behavior toward those individuals. But is this true for everyone, or only for those who tend toward—or away from—helping more generally? The current study (N = 283) used an imagined helping paradigm and a battery of behavioral and self-report measures of trait prosociality to determine whether the prosocial benefits of imagination depend upon an individual's general tendency to help others. Replicating prior work, we found links between imagination and prosociality and support for a three-factor model of prosociality comprising altruistically, norm-motivated, and self-reported prosocial behaviors. Centrally, the effects of imagination on prosociality were slightly larger for less altruistic individuals but independent of norm-motivated and self-reported prosociality. These results suggest leveraging people's abilities for episodic simulation as a promising strategy for increasing prosociality in general, and perhaps particularly for those least likely to help otherwise