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How does Antarctic Bottom Water Cross the Southern Ocean?
No full textAntarctic Bottom Water (AABW), which fills the global ocean abyss, is derived from dense water that forms in several distinct Antarctic shelf regions. Previous modeling studies have reached conflicting conclusions regarding export pathways of AABW across the Southern Ocean and the degree to which AABW originating from distinct source regions are blended during their export. This study addresses these questions using passive tracer deployments in a 61-year global high-resolution (0.1°) ocean/sea-ice simulation. Two distinct export “conduits” are identified: Weddell Sea- and Prydz Bay-sourced AABW are blended together and exported mainly to the Atlantic and Indian Oceans, while Ross Sea- and Adelie Land-sourced AABW are exported mainly to the Pacific Ocean. Northward transport of each tracer occurs almost exclusively (>90%) within a single conduit. These findings imply that regional changes in AABW production may impact the three-dimensional structure of the global overturning circulation
The ALPINE-ALMA [CII] survey: The population of [CII]-undetected galaxies and their role in the L_[CII]-SFR relation
No full textThe [CII] 158 μm emission line represents one of the most profitable tools for the investigation of the high-redshift galaxies in the early Universe so far. Being one of the brightest cooling lines in the rest-frame far-infrared regime of star-forming galaxies, it has been successfully exploited as a tracer of the star-formation rate (SFR) in local sources. The picture is more complex at higher redshifts, where its usability in this context is still under investigation. Recent results from the ALMA Large Program to INvestigate [CII] at Early times (ALPINE) survey suggest that there is no (or weak) evolution of the L[CII]-SFR relation up to z ∼ 6, but their reliability is hampered by the presence of a large population of [CII] nondetected galaxies. In this work, we characterize the population of [CII] nondetections in ALPINE. By stacking their ALMA spectra, we obtained a signal detected at ∼5.1σ, resulting in a [CII] luminosity of log(L_[CII]/L_⊙)∼7.8. When combining this value with those from the [CII] detections, we found a L_[CII]-SFR relation with a slope b = 1.14 ± 0.11, which is in agreement within the uncertainties both with the linear relation found in the local Universe and with the previous findings from ALPINE at z ∼ 5. This suggests that the [CII] line can be considered a good tracer of star formation up to the distant Universe. Finally, we show that the galaxies of our sample that deviate from the observed L_[CII]-SFR relation most could suffer from a less precise redshift estimation, perhaps artificially reducing their [CII] luminosity. In this respect, we claim that there is no evidence in favor of a deficit of [CII] content in high-z galaxies, in contrast with earlier studies
Gravitational Microlensing Rates in Milky Way Globular Clusters
No full textMany recent observational and theoretical studies suggest that globular clusters (GCs) host compact object populations large enough to play dominant roles in their overall dynamical evolution. Yet direct detection, particularly of black holes and neutron stars, remains rare and limited to special cases, such as when these objects reside in close binaries with bright companions. Here we examine the potential of microlensing detections to further constrain these dark populations. Based on state-of-the-art GC models from the CMC Cluster Catalog, we estimate the microlensing event rates for black holes, neutron stars, white dwarfs (WDs), and, for comparison, also for M dwarfs in Milky Way GCs, as well as the effects of different initial conditions on these rates. Among compact objects, we find that WDs dominate the microlensing rates, simply because they largely dominate by numbers. We show that microlensing detections are in general more likely in GCs with higher initial densities, especially in clusters that undergo core collapse. We also estimate microlensing rates in the specific cases of M22 and 47 Tuc using our best-fitting models for these GCs. Because their positions on the sky lie near the rich stellar backgrounds of the Galactic bulge and the Small Magellanic Cloud, respectively, these clusters are among the Galactic GCs best suited for dedicated microlensing surveys. The upcoming 10 yr survey with the Rubin Observatory may be ideal for detecting lensing events in GCs
Face neurons encode nonsemantic features
No full textThe primate inferior temporal cortex contains neurons that respond more strongly to faces than to other objects. Termed “face neurons,” these neurons are thought to be selective for faces as a semantic category. However, face neurons also partly respond to clocks, fruits, and single eyes, raising the question of whether face neurons are better described as selective for visual features related to faces but dissociable from them. We used a recently described algorithm, XDream, to evolve stimuli that strongly activated face neurons. XDream leverages a generative neural network that is not limited to realistic objects. Human participants assessed images evolved for face neurons and for nonface neurons and natural images depicting faces, cars, fruits, etc. Evolved images were consistently judged to be distinct from real faces. Images evolved for face neurons were rated as slightly more similar to faces than images evolved for nonface neurons. There was a correlation among natural images between face neuron activity and subjective “faceness” ratings, but this relationship did not hold for face neuron–evolved images, which triggered high activity but were rated low in faceness. Our results suggest that so-called face neurons are better described as tuned to visual features rather than semantic categories
From Specification to Implementation: Assume-Guarantee Contracts for Synthetic Biology
No full textWe provide a new perspective on using formal methods to model specifications and synthesize implementations for the design of biological circuits. In synthetic biology, design objectives are rarely described formally. We present an assume-guarantee contract framework to describe biological circuit design objectives as formal specifications. In our approach, these formal specifications are implemented by circuits modeled by ordinary differential equations, yielding a design framework that can be used to design complex synthetic biological circuits at scale. We describe our approach using the design of a biological AND gate as a motivating, running example
The Search for a Counterpart to NuSTAR J053449+2126.0
No full text(ATel #15171) have recently reported the discovery of an X-ray source, NuSTAR J053449+2126.0, during a calibration observation which took place on 2020 April 25. We scan the Zwicky Transient Facility alerts and archival photometry to determine the nature of the source. Palomar Gattini-IR is searched as well. We identify no obvious counterpart candidate. Follow-up X-ray and optical studies are needed to determine the true counterpart
Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success From Video
No full textBackground: Deep neural networks (DNNs) have not been proven to detect blood loss (BL) or predict surgeon performance from video.
Objective: To train a DNN using video from cadaveric training exercises of surgeons controlling simulated internal carotid hemorrhage to predict clinically relevant outcomes.
Methods: Video was input as a series of images; deep learning networks were developed, which predicted BL and task success from images alone (automated model) and images plus human-labeled instrument annotations (semiautomated model). These models were compared against 2 reference models, which used average BL across all trials as its prediction (control 1) and a linear regression with time to hemostasis (a metric with known association with BL) as input (control 2). The root-mean-square error (RMSE) and correlation coefficients were used to compare the models; lower RMSE indicates superior performance.
Results: One hundred forty-three trials were used (123 for training and 20 for testing). Deep learning models outperformed controls (control 1: RMSE 489 mL, control 2: RMSE 431 mL, R2 = 0.35) at BL prediction. The automated model predicted BL with an RMSE of 358 mL (R2 = 0.4) and correctly classified outcome in 85% of trials. The RMSE and classification performance of the semiautomated model improved to 260 mL and 90%, respectively.
Conclusion: BL and task outcome classification are important components of an automated assessment of surgical performance. DNNs can predict BL and outcome of hemorrhage control from video alone; their performance is improved with surgical instrument presence data. The generalizability of DNNs trained on hemorrhage control tasks should be investigated
Thermodynamics of electrolyte solutions near charged surfaces: Constant surface charge vs constant surface potential
No full textElectric double layers are ubiquitous in science and engineering and are of current interest, owing to their applications in the stabilization of colloidal suspensions and as supercapacitors. While the structure and properties of electric double layers in electrolyte solutions near a charged surface are well characterized, there are subtleties in calculating thermodynamic properties from the free energy of a system with charged surfaces. These subtleties arise from the difference in the free energy between systems with constant surface charge and constant surface potential. In this work, we present a systematic, pedagogical framework to properly account for the different specifications on charged bodies in electrolyte solutions. Our approach is fully variational—that is, all free energies, boundary conditions, relevant electrostatic equations, and thermodynamic quantities are systematically derived using variational principles of thermodynamics. We illustrate our approach by considering a simple electrolyte solution between two charged surfaces using the Poisson–Boltzmann theory. Our results highlight the importance of using the proper thermodynamic potential and provide a general framework for calculating thermodynamic properties of electrolyte solutions near charged surfaces. Specifically, we present the calculation of the pressure and the surface tension between two charged surfaces for different boundary conditions, including mixed boundary conditions
Global GOSAT, OCO-2, and OCO-3 solar-induced chlorophyll fluorescence datasets
No full textThe retrieval of solar-induced chlorophyll fluorescence (SIF) from space is a relatively new advance in Earth observation science, having only become feasible within the last decade. Interest in SIF data has grown exponentially, and the retrieval of SIF and the provision of SIF data products has become an important and formal component of spaceborne Earth observation missions. Here, we describe the global Level 2 SIF Lite data products for the Greenhouse Gases Observing Satellite (GOSAT), the Orbiting
Carbon Observatory-2 (OCO-2), and Orbiting Carbon Observatory-3 (OCO-3) platforms, which are provided for each platform in daily netCDF files (Frankenberg, 2022, https://doi.org/10.22002/D1.8771; OCO-2 Science Team et al., 2020, https://doi.org/10.5067/XO2LBBNPO010; OCO-3 Science Team et al., 2020, https://doi.org/10.5067/NOD1DPPBCXSO). We also outline the methods used to retrieve SIF and estimate uncertainty, describe all the data fields, and provide users with the background information necessary for the proper use
and interpretation of the data, such as considerations of retrieval noise, sun sensor geometry, the indirect relationship between SIF and photosynthesis, and differences among the three platforms and their respective data products. OCO-2 and OCO-3 have the highest spatial resolution of spaceborne SIF retrievals to date, and the target and snapshot area mode observation modes of OCO-2 and OCO-3 are unique. These modes
provide hundreds to thousands of SIF retrievals at biologically diverse global target sites during a single overpass, and provide an opportunity to better inform our understanding of canopy-scale vegetation SIF emission across biomes
Tailoring Term Truncations for Electronic Structure Calculations Using a Linear Combination of Unitaries
No full textA highly anticipated use of quantum computers is the simulation of complex quantum systems including molecules and other many-body systems. One promising method involves directly applying a linear combination of unitaries (LCU) to approximate a Taylor series by truncating after some order. Here we present an adaptation of that method, optimized for Hamiltonians with terms of widely varying magnitude, as is commonly the case in electronic structure calculations. We show that it is more efficient to apply LCU using a truncation that retains larger magnitude terms as determined by an iterative procedure. We obtain bounds on the simulation error for this generalized truncated Taylor method, and for a range of molecular simulations, we report these bounds as well as exact numerical results. We find that our adaptive method can typically improve the simulation accuracy by an order of magnitude, for a given circuit depth