cssi/SciSciGPT-SciSciNet huggingface dataset:
Changes in Ni-NiO Equilibrium Due to LaFeO3 and the Effect on Dry Reforming of CH4

Abstract The interactions between Ni and LaFeO3 were studied on catalysts prepared by Atomic Layer Deposition (ALD) of 0.5-nm films of LaFeO3 on MgAl2O4. Scanning Transmission Electron Microscopy showed that the films covered the support uniformly, even after 5 redox cycles at 1073 K, and X-Ray Diffraction showed that the films had the perovskite structure. Equilibrium between Ni and NiO was studied using coulometric-titration and flow-titration measurements on 5-wt% Ni catalysts, with and without LaFeO3. While equilibrium constants for Ni/MgAl2O4 were similar to that expected for bulk Ni, equilibrium P O 2 were shifted to significantly lower values in the presence of LaFeO3. In studies of Methane Dry Reforming, the shift in equilibrium resulted in catalyst deactivation due to Ni oxidation at low CO:CO2 ratios, even though Ni/LaFeO3/MgAl2O4 otherwise showed a high reaction rate and excellent tolerance against coking.
Rhapsody: predicting the pathogenicity of human missense variants.

Motivation The biological effects of human missense variants have been studied experimentally for decades but predicting their effects in clinical molecular diagnostics remains challenging. Available computational tools are usually based on the analysis of sequence conservation and structural properties of the mutant protein. We recently introduced a new machine learning method that demonstrated for the first time the significance of protein dynamics in determining the pathogenicity of missense variants. Results Here, we present a new interface (Rhapsody) that enables fully automated assessment of pathogenicity, incorporating both sequence coevolution data and structure- and dynamics-based features. Benchmarked against a dataset of about 20 000 annotated variants, the methodology is shown to outperform well-established and/or advanced prediction tools. We illustrate the utility of Rhapsody by in silico saturation mutagenesis studies of human H-Ras, phosphatase and tensin homolog and thiopurine S-methyltransferase. Availability and implementation The new tool is available both as an online webserver at http://rhapsody.csb.pitt.edu and as an open-source Python package (GitHub repository: https://github.com/prody/rhapsody; PyPI package installation: pip install prody-rhapsody). Links to additional resources, tutorials and package documentation are provided in the 'Python package' section of the website. Supplementary information Supplementary data are available at Bioinformatics online.
All Things Homunculus

The “Homunculus” nebula around Eta Carinae is one of our most valuable tools for understanding the extreme nature of episodic pre-supernova mass loss in the most massive stars, perhaps even more valuable than the historical light curve of η Car. As a young nebula that is still in free expansion, it bears the imprint of its ejection physics, making it a prototype for understanding the bipolar mass loss that is so common in astrophysics. The high mass and kinetic energy of the nebula provide a sobering example of the extreme nature of stellar eruptions in massive stars near the Eddington limit. The historical ejection event was observed, and current parameters are easily measured due to its impressive flux at all wavelengths, so the Homunculus is also a unique laboratory for studying rapid dust formation and molecular chemistry, unusual ISM abundances, and spectroscopy of dense gas. Since it is relatively nearby and bright and is expanding rapidly, its 3-D geometry, kinematics, and detailed structure can be measured accurately, providing unusually good quantitative contraints on the physics that created these structures. In this chapter I review the considerable recent history of observational and theoretical study of the Homunculus nebula, and I provide an up-to-date summary of our current understanding, as well as areas that need work.
Limits of sums for binomial and Eulerian numbers and their associated distributions

We provide a probabilistic approach using renewal theory to derive some novel identities involving Eulerian numbers and uniform B-splines. The renewal perspective leads to a unified treatment for the normalized binomial coefficients and the normalized Eulerian numbers when studying their limits of sums, as well as their associated distributions - the binomial distributions (Bernstein polynomials) and the Irwin-Hall distributions (uniform B-splines). We further extend the probabilistic perspective to h-Bernstein polynomials (Polya-Eggenberger distributions) through conditional renewal processes, and derive new limits of various ways of summing for the two special numbers and associated distributions. The proposed probabilistic unification dramatically simplifies the proofs of some identities, which are far from obvious (such as for h-Bernstein polynomials) or do not otherwise even appear promising (such as for Eulerian numbers).
Fundamental Limits of Covert Packet Insertion

Covert communication conceals the existence of the transmission from a watchful adversary. We consider the fundamental limits for covert communications via packet insertion over packet channels whose packet timings are governed by a renewal process of rate $\lambda $ . Authorized transmitter Jack sends packets to authorized receiver Steve, and covert transmitter Alice wishes to transmit packets to covert receiver Bob without being detected by watchful adversaries Willie 1 and Willie 2. Willies cannot authenticate the source of the packets or collaborate. Hence, each Willie looks for statistical anomalies in the packet stream from Jack to Steve to attempt detection of unauthorized packet insertion. First, we consider a special case where the packet timings are governed by a Poisson process and we show that Alice can covertly insert $\mathcal {O}(\sqrt {\lambda T})$ packets for Bob in a time interval of length $T$ ; conversely, if Alice inserts $\omega (\sqrt {\lambda T})$ packets, she will be detected by Willie 1 or Willie 2 with high probability. Then, we extend our results to general renewal channels and show that in a stream of $N$ packets transmitted by Jack, Alice can covertly insert $\mathcal {O}(\sqrt {N})$ packets; if she inserts $\omega (\sqrt {N})$ packets, she will be detected by Willie 1 or Willie 2, with high probability.
Urban Agglomerations and Employment Transitions in Ethiopia

Agglomeration boosts economic growth. A vast literature has empirically assessed the effects of agglomeration by estimating the city population elasticity on wages. This conventional approach is not necessarily suitable for analyzing urbanization at the early stage in developing countries, where a majority of urban workers engage in self-employment and/or informal jobs. Focusing on one of the poorest and largest among those countries, this paper sheds light on an aspect of urbanization and agglomeration: the transition in the mode of labor from self-employment/informal jobs to wage employment/formal jobs. Applying the instrumental variable approach to national labor force survey data sets, the analysis underscores several labor market transitions across space in urban Ethiopia. First, the town population size and the share of workers with wage employment are strongly correlated. The probability of engaging in wage work increases by 4.5 percentage points with a log increase in population size. Second, this relationship is particularly strong among disadvantaged workers, such as the female, young, and/or less educated population. Finally, the study documents higher labor force participation and lower underemployment in larger towns.
Unpredictable Planning Under Partial Observability

We study the problem of synthesizing a controller that maximizes the entropy of a partially observable Markov decision process (POMDP) subject to a constraint on the expected total reward. Such a controller minimizes the predictability of a decision-maker’s trajectories while guaranteeing the completion of a task expressed by a reward function. First, we prove that a decision-maker with perfect observations can randomize its paths at least as well as a decision-maker with partial observations. Then, focusing on finite-state controllers, we recast the entropy maximization problem as a so-called parameter synthesis problem for a parametric Markov chain (pMC). We show that the maximum entropy of a POMDP is lower bounded by the maximum entropy of this pMC. Finally, we present an algorithm, based on a nonlinear optimization problem, to synthesize an FSC that locally maximizes the entropy of a POMDP over FSCs with the same number of memory states. In numerical examples, we demonstrate the proposed algorithm on motion planning scenarios.
Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

Bird plumage exhibits a diversity of colors that serve functional roles ranging from signaling to camouflage and thermoregulation. However, birds must maintain a balance between evolving colorful signals to attract mates, minimizing conspicuousness to predators, and optimizing adaptation to climate conditions. Examining plumage color macroevolution provides a framework for understanding this dynamic interplay over phylogenetic scales. Plumage evolution due to a single overarching process, such as selection, may generate the same macroevolutionary pattern of color variation across all body regions. In contrast, independent processes may partition plumage and produce region-specific patterns. To test these alternative scenarios, we collected color data from museum specimens of an ornate clade of birds, the Australasian lorikeets, using visible-light and UV-light photography, and comparative methods. We predicted that the diversification of homologous feather regions, i.e., patches, known to be involved in sexual signaling (e.g., face) would be less constrained than patches on the back and wings, where new color states may come at the cost of crypsis. Because environmental adaptation may drive evolution towards or away from color states, we tested whether climate more strongly covaried with plumage regions under greater or weaker macroevolutionary constraint. We found that alternative macroevolutionary models and varying rates best describe color evolution, a pattern consistent with our prediction that different plumage regions evolved in response to independent processes. Modeling plumage regions independently, in functional groups, and all together showed that patches with similar macroevolutionary models clustered together into distinct regions (e.g., head, wing, belly), which suggests that plumage does not evolve as a single trait in this group. Wing patches, which were conserved on a macroevolutionary scale, covaried with climate more strongly than plumage regions (e.g., head), which diversified in a burst. Overall, our results support the hypothesis that the extraordinary color diversity in the lorikeets was generated by a mosaic of evolutionary processes acting on plumage region subsets. Partitioning of plumage regions in different parts of the body provides a mechanism that allows birds to evolve bright colors for signaling and remain hidden from predators or adapt to local climatic conditions.
Seismic Inversion and the Data Normalization for Optimal Transport

Full waveform inversion (FWI) has recently become a favorite technique for the inverse problem of finding properties in the earth from measurements of vibrations of seismic waves on the surface. Mathematically, FWI is PDE constrained optimization where model parameters in a wave equation are adjusted such that the misfit between the computed and the measured dataset is minimized. In a sequence of papers, we have shown that the quadratic Wasserstein distance from optimal transport is to prefer as misfit functional over the standard $L^2$ norm. Datasets need however first to be normalized since seismic signals do not satisfy the requirements of optimal transport. There has been a puzzling contradiction in the results. Normalization methods that satisfy theorems pointing to ideal properties for FWI have not performed well in practical computations, and other scaling methods that do not satisfy these theorems have performed much better in practice. In this paper, we will shed light on this issue and resolve this contradiction.
Electron temperature of the solar wind

Solar wind provides an example of a weakly collisional plasma expanding from a thermal source in the presence of spatially diverging magnetic-field lines. Observations show that in the inner heliosphere, the electron temperature declines with the distance approximately as T e ( r ) ∼ r − 0.3 … r − 0.7 , which is significantly slower than the adiabatic expansion law ∼ r − 4 / 3 . Motivated by such observations, we propose a kinetic theory that addresses the nonadiabatic evolution of a nearly collisionless plasma expanding from a central thermal source. We concentrate on the dynamics of energetic electrons propagating along a radially diverging magnetic-flux tube. Due to conservation of their magnetic moments, the electrons form a beam collimated along the magnetic-field lines. Due to weak energy exchange with the background plasma, the beam population slowly loses its energy and heats the background plasma. We propose that no matter how weak the collisions are, at large enough distances from the source a universal regime of expansion is established where the electron temperature declines as T e ( r ) ∝ r − 2 / 5 . This is close to the observed scaling of the electron temperature in the inner heliosphere. Our first-principle kinetic derivation may thus provide an explanation for the slower-than-adiabatic temperature decline in the solar wind. More broadly, it may be useful for describing magnetized collisionless winds from G-type stars.
Quasi-isometric embeddings of non-uniform lattices

Let $G$ and $G'$ be simple Lie groups of equal real rank and real rank at least $2$. Let $\Gamma <G$ and $\Lambda < G'$ be non-uniform lattices. We prove a theorem that often implies that any quasi-isometric embedding of $\Gamma$ into $\Lambda$ is at bounded distance from a homomorphism. For example, any quasi-isometric embedding of $SL(n,\mathbb Z)$ into $SL(n, \mathbb Z[i])$ is at bounded distance from a homomorphism. We also include a discussion of some cases when this result is not true for what turn out to be purely algebraic reasons.
Effects of ocean climate on spatiotemporal variation in sea urchin settlement and recruitment

Abstract Sea urchins are voracious herbivores that influence the ecological structure and function of nearshore ecosystems throughout the world. Like many species that produce planktonic larvae, their recruitment is thought to be particularly sensitive to climatic fluctuations in temperature that directly or indirectly affect adult reproduction and larval transport and survival. Yet how climate alters sea urchin populations in space and time by modifying larval recruitment and year-class strength on the time-scales that regulate populations remains understudied. Using a, spatially replicated weekly-biweekly dataset spanning 27 years and 1100 km of coastline, we characterized seasonal, interannual, and spatial patterns of larval settlement of the purple sea urchin (Strongylocentrotus purpuratus). We show that large spatial differences in temporal patterns of larval settlement were associated with different responses to fluctuations in ocean temperature and climate. Importantly, we found a strong correlation between larval settlement and regional year class strength suggesting that such temporal and spatial variation in settlement plays an important role in controlling population dynamics. These results provide strong evidence over extensive temporal and spatial domains that climatic fluctuations shape broad-scale patterns of larval settlement and subsequent population structure of an important marine herbivore known to control the productivity, community state and provisioning services of marine ecosystems.
Compressed Sensing Using Binary Matrices of Nearly Optimal Dimensions

In this paper, we study the problem of compressed sensing using binary measurement matrices and $\ell _1$ -norm minimization (basis pursuit) as the recovery algorithm. We derive new upper and lower bounds on the number of measurements to achieve robust sparse recovery with binary matrices. We establish sufficient conditions for a column-regular binary matrix to satisfy the robust null space property (RNSP) and show that the associated sufficient conditions for robust sparse recovery obtained using the RNSP are better by a factor of $(3 \sqrt{3})/2 \approx 2.6$ compared to the sufficient conditions obtained using the restricted isometry property (RIP). Next we derive universal lower bounds on the number of measurements that any binary matrix needs to have in order to satisfy the weaker sufficient condition based on the RNSP and show that bipartite graphs of girth six are optimal. Then we display two classes of binary matrices, namely parity check matrices of array codes and Euler squares, which have girth six and are nearly optimal in the sense of almost satisfying the lower bound. In principle, randomly generated Gaussian measurement matrices are “order-optimal.” So we compare the phase transition behavior of the basis pursuit formulation using binary array codes and Gaussian matrices and show that (i) there is essentially no difference between the phase transition boundaries in the two cases and (ii) the CPU time of basis pursuit with binary matrices is hundreds of times faster than with Gaussian matrices and the storage requirements are less. Therefore it is suggested that binary matrices are a viable alternative to Gaussian matrices for compressed sensing using basis pursuit.
Borrowing Without Debt? Understanding the U.S. International Investment Position

Sustained large U.S. current account deficits have led some economists and policymakers to worry that future current account adjustment could occur through a sudden and disruptive depreciation of the dollar and a sharp drop in U.S. consumption. Two factors that, to date, have cast doubt on such concerns are the stability of U.S. net external liabilities and the minimal net income payments made by the United States on these liabilities. We show that the stability of the external position reflects sizable capital gains stemming from strong foreign equity markets and a weaker dollar—conditions that could be reversed in the future. We also show that while minimal U.S. net income payments reflect a much higher measured rate of return on U.S. foreign direct investment (FDI) assets than on U.S. FDI liabilities, ongoing borrowing is likely to overwhelm this favorable rate of return, pushing the U.S. net income balance more deeply into deficit.
An Empirical Investigation of the Welfare Effects of Banning Wholesale Price Discrimination

Economic theory does not provide sharp predictions on the welfare effects of banning wholesale price discrimination: if downstream costs differences exist then discrimination shifts production inefficiently, towards high cost retailers, so a ban increases welfare; if differences in price elasticity of demand across retailers exist, discrimination may increase welfare if more market is covered, so a ban reduces welfare. Using retail prices and quantities of coffee brands sold by German retailers, I estimate a model of demand and supply and separate cost and demand differences. Simulating a ban on wholesale price discrimination has positive welfare effects in this market, and less if downstream cost differences shrink, or with less competition.
Prostate-Specific Antigen as a Serum Marker for Adenocarcinoma of the Prostate

To compare the clinical usefulness of the serum markers prostate-specific antigen (PSA) and prostatic acid phosphatase (PAP), we measured them by radioimmunoassay in 2200 serum samples from 699 patients, 378 of whom had prostatic cancer. PSA was elevated in 122 of 127 patients with newly diagnosed, untreated prostatic cancer, including 7 of 12 patients with unsuspected early disease and all of 115 with more advanced disease. The PSA level increased with advancing clinical stage and was proportional to the estimated volume of the tumor. The PAP concentration was elevated in only 57 of the patients with cancer and correlated less closely with tumor volume. PSA was increased in 86 percent and PAP in 14 percent of the patients with benign prostatic hyperplasia. After radical prostatectomy for cancer, PSA routinely fell to undetectable levels, with a half-life of 2.2 days. If initially elevated, PAP fell to normal levels within 24 hours but always remained detectable. In six patients followed postoperatively by means of repeated measurements, PSA--but not PAP--appeared to be useful in detecting residual and early recurrence of tumor and in monitoring responses to radiation therapy. Prostate massage increased the levels of both PSA and PAP approximately 1.5 to 2 times. Needle biopsy and transurethral resection increased both considerably. We conclude that PSA is more sensitive than PAP in the detection of prostatic cancer and will probably be more useful in monitoring responses and recurrence after therapy. However, since both PSA and PAP may be elevated in benign prostatic hyperplasia, neither marker is specific.
Optimal Spatial Policies, Geography, and Sorting

We study optimal spatial policies in quantitative trade and geography frameworks with spillovers and sorting of heterogeneous workers. We rst characterize ecient spatial transfers and the labor subsidies that would implement them. Then, we quantify the aggregate and distributional eects of implementing these policies in the U.S. economy. Under homogeneous workers and constant-elasticity spillovers, a constant labor subsidy over space restores efficiency regardless of micro heterogeneity in fundamentals and trade costs. In that case, the quantification suggests that the observed spatial transfers in the U.S. are close to ecient. Spillovers across heterogeneous workers create an additional rationale for place-specific subsidies to attain optimal sorting. Under heterogeneous workers, the quantication suggests that optimal spatial policies may require stronger redistribution towards low-wage cities than in the data, reduce wage inequality in larger cities, weaken spatial sorting by skill, and lead to signicant welfare gains. Spillovers across dierent types of workers are a key driving force behind these results.
Coordination and Cooperation in Local, Random and Small World Networks: Experimental Evidence

A laboratory experiment studies coordination and cooperation in games played in different networks local, random and small-world. Coordination on the payoff-dominant equilibrium was faster in small-world networks than in local and random networks. However, in a prisoners dilemma game, cooperation was the hardest to achieve in small-world networks. Two graph-theoretic characteristics clustering coefficient and characteristic path length accounted for differences in individual behavior, possibly explaining why equilibrium convergence is most rapid in small-world networks.
Chapter 4 – The Heart

In this chapter, we begin to discuss flow through the macrocirculation by describing the organ that drives blood flow, the heart. The structure of cardiac muscle cells and how action potentials develop and are transmitted through these cells are discussed. Differences between the cardiac muscle cell action potential and the skeletal muscle action potential are discussed. The cardiac conduction system, which is a specialized system to rapidly and efficiently transmit electrical signals through the heart, is described. The electrocardiogram, pressure waveform, and heart motion are related to blood flow through the heart. We also highlight how the heart valves function and discuss methods to calculate the tension within the heart valve leaflets. Some of the salient disease conditions that affect the heart are compared.
Chapter 9 – Advanced Geothermal Energy Conversion Systems

No two geothermal resources are exactly alike and thus energy conversion systems must be chosen and often adapted to suit a particular resource. Some geothermal resources demand more sophisticated energy conversion systems, and this chapter reviews some of the advanced systems for geothermal power generation. Hybrid single-flash and double-flash systems are often used to increase the output of a system when expanding the generating capacity becomes possible. Hybrid flash-binary designs also exist, either through adding a binary cycle to an existing single-flash plant or by integrating the two from scratch in the initial design. The concept of a total-flow system arises from a desire to avoid the irreversibilities associated with the flashing processes needed for either a single- or double-flash plant. Other advanced designs look to combine geothermal energy with other energy sources such as fossil and solar energy, or combine both power generation and direct heat usage in a single plant. In addition, systems for dealing with hypersaline brines are also just starting to be exploited.
Estimating diffusion coefficients of shale oil, gas, and condensate with nano-confinement effect

Abstract Molecular diffusion plays an important role in oil and gas migration in tight shale formations. However, there are insufficient reference data in the literature to specify the diffusion coefficients within porous media. This study aims at calculating diffusion coefficients of shale gas, shale condensate, and shale oil at reservoir conditions with CO2 injection for EOR/EGR. The large nano-confinement effects including large gas-oil capillary pressure and critical property shifts could alter the phase behaviors. This paper estimates the diffusivities of shale fluids in nanometer-scale shale rock from two perspectives: 1) examining the shift of diffusivity caused by nanopore confinement effects from phase change (phase composition and fluid property) perspective, and 2) calculating the effective diffusion coefficient in porous media by incorporating rock intrinsic properties (porosity and tortuosity factor). The tortuosity is obtained by using tortuosity-porosity relations as well as the measured tortuosity of shale from 3D imaging techniques. The results indicated that nano-confinement effects could affect the diffusion coefficient through altering the phase properties, such as phase compositions and densities. Compared to bulk phase diffusivity, the effective diffusion coefficient in porous shale rock is reduced by 102 to 104 times as porosity decreases from 0.1 to 0.03.
Optimum Threshold Minimizes Noise in Timing of Intracellular Events

Summary How the noisy expression of regulatory proteins affects timing of intracellular events is an intriguing fundamental problem that influences diverse cellular processes. Here we use the bacteriophage λ to study event timing in individual cells where cell lysis is the result of expression and accumulation of a single protein (holin) in the Escherichia coli cell membrane up to a critical threshold level. Site-directed mutagenesis of the holin gene generated phage variants that vary in their lysis times from 30 to 190 min. Observation of the lysis times of single cells reveals an intriguing finding—the noise in lysis timing first decreases with increasing lysis time to reach a minimum and then sharply increases at longer lysis times. A mathematical model with stochastic expression of holin together with dilution from cell growth was sufficient to explain the non-monotonic noise profile and identify holin accumulation thresholds that generate precision in lysis timing.
Cross-media Structured Common Space for Multimedia Event Extraction.

We introduce a new task, MultiMedia Event Extraction, which aims to extract events and their arguments from multimedia documents. We develop the first benchmark and collect a dataset of 245 multimedia news articles with extensively annotated events and arguments. We propose a novel method, Weakly Aligned Structured Embedding (WASE), that encodes structured representations of semantic information from textual and visual data into a common embedding space. The structures are aligned across modalities by employing a weakly supervised training strategy, which enables exploiting available resources without explicit cross-media annotation. Compared to uni-modal state-of-the-art methods, our approach achieves 4.0% and 9.8% absolute F-score gains on text event argument role labeling and visual event extraction. Compared to state-of-the-art multimedia unstructured representations, we achieve 8.3% and 5.0% absolute F-score gains on multimedia event extraction and argument role labeling, respectively. By utilizing images, we extract 21.4% more event mentions than traditional text-only methods.
Systematic review and meta-analysis of sex-specific COVID-19 clinical outcomes

To successfully mitigate the extraordinary devastation caused by the Coronavirus disease 2019 (COVID-19) pandemic, it is crucial to identify important risk factors for this disease. One such neglected health determinant is the sex of the patient. This is an essential clinical characteristic, as it can factor into a patient's clinical management and preventative measures. Some clinical studies have shown disparities in the proportion between males and females that have more severe clinical outcomes or, subsequently, die from this disease. However, this association has not been unequivocally established. Thus, the purpose of this investigation was to examine the association between male sex and COVID-19 severity. We systematically reviewed the literature, identified studies that matched predetermined selection criteria, and performed a meta-analysis to evaluate the proportion of males among four disease severity categories. Appropriate assessment strategies were implemented to assess and minimize potential biases. The results of this meta-analysis indicated that males constituted a significantly higher proportion of those who had adverse clinical outcomes and died from COVID-19. As the coronavirus spread from the East to the West, male sex remained a consistent risk factor. Our results support the establishment of the male sex as an important risk factor for this disease. Early identification and appropriate medical care for males with lab-confirmed COVID-19 may substantially change the course of clinical prognosis, resulting in greater numbers of lives saved.
$R^3$: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledge

We propose an unsupervised approach for sarcasm generation based on a non-sarcastic input sentence. Our method employs a retrieve-and-edit framework to instantiate two major characteristics of sarcasm: reversal of valence and semantic incongruity with the context, which could include shared commonsense or world knowledge between the speaker and the listener. While prior works on sarcasm generation predominantly focus on context incongruity, we show that combining valence reversal and semantic incongruity based on the commonsense knowledge generates sarcasm of higher quality. Human evaluation shows that our system generates sarcasm better than humans 34% of the time, and better than a reinforced hybrid baseline 90% of the time.
Soil microbial communities associated with giant sequoia: How does the world's largest tree affect some of the world's smallest organisms?

Giant sequoia (Sequoiadendron giganteum) is an iconic conifer that lives in relict populations on the western slopes of the California Sierra Nevada. In these settings, it is unusual among the dominant trees in that it associates with arbuscular mycorrhizal fungi rather than ectomycorrhizal fungi. However, it is unclear whether differences in microbial associations extend more broadly to nonmycorrhizal components of the soil microbial community. To address this question, we used next-generation amplicon sequencing to characterize bacterial/archaeal and fungal microbiomes in bulk soil (0-5 cm) beneath giant sequoia and co-occurring sugar pine (Pinus lambertiana) individuals. We did this across two groves with distinct parent material in Yosemite National Park, USA. We found tree-associated differences were apparent despite a strong grove effect. Bacterial/archaeal richness was greater beneath giant sequoia than sugar pine, with a core community double the size. The tree species also harbored compositionally distinct fungal communities. This pattern depended on grove but was associated with a consistently elevated relative abundance of Hygrocybe species beneath giant sequoia. Compositional differences between host trees correlated with soil pH and soil moisture. We conclude that the effects of giant sequoia extend beyond mycorrhizal mutualists to include the broader community and that some but not all host tree differences are grove-dependent.
SCOUT: Self-Aware Discriminant Counterfactual Explanations

The problem of counterfactual visual explanations is considered. A new family of discriminant explanations is introduced. These produce heatmaps that attribute high scores to image regions informative of a classifier prediction but not of a counter class. They connect attributive explanations, which are based on a single heat map, to counterfactual explanations, which account for both predicted class and counter class. The latter are shown to be computable by combination of two discriminant explanations, with reversed class pairs. It is argued that self-awareness, namely the ability to produce classification confidence scores, is important for the computation of discriminant explanations, which seek to identify regions where it is easy to discriminate between prediction and counter class. This suggests the computation of discriminant explanations by the combination of three attribution maps. The resulting counterfactual explanations are optimization free and thus much faster than previous methods. To address the difficulty of their evaluation, a proxy task and set of quantitative metrics are also proposed. Experiments under this protocol show that the proposed counterfactual explanations outperform the state of the art while achieving speeds much faster, for popular networks. In a human-learning machine teaching experiment, they are also shown to improve mean student accuracy from chance level to 95%.
Characterization of on-orbit GPS transmit antenna patterns for space users

The GPS Antenna Characterization Experiment (GPS ACE) has made extensive observations of GPS L1 signals received at geosynchronous (GEO) altitude, with the objective of developing comprehensive models of the signal levels and signal performance in the GPS transmit antenna side lobes. The experiment was originally motivated by the fact that data on the characteristics and performance of the GPS signals available in GEO and other high Earth orbits was limited. The lack of knowledge of the power and accuracy of the side lobe signals on-orbit added risk to missions seeking to employ the side lobes to meet navigation requirements or improve performance. The GPS ACE Project lled that knowledge gap through a collaboration between The Aerospace Corporation and NASA Goddard Space Fight Center to collect and analyze observations from GPS side lobe transmissions to a satellite at GEO using a highly-sensitive GPS receiver installed at the ground station. The GPS ACE architecture has been in place collecting observations of the GPS constellation with extreme sensitivity for several years. This sensitivity combined with around-the-clock, all-in-view processing enabled full azimuthal coverage of the GPS transmit gain patterns over time to angles beyond 90 degrees o -boresight. Results discussed in this paper include the reconstructed transmit gain patterns, with comparisons to available pre-fight gain measurements from the GPS vehicle contractors. For GPS blocks with extensive ground measurements, the GPS ACE results show remarkable agreement with ground based measurements. For blocks without extensive ground measurements, the GPS ACE results provide the only existing assessments of the full transmit gain patterns. The paper also includes results of pseudorange deviation analysis to assess systematic errors associated with GPS side lobe signals.
The Berenstein–Kirillov group and cactus groups

Berenstein and Kirillov have studied the action of Bender-Knuth moves on semistandard tableaux. Losev has studied a cactus group action in Kazhdan-Lusztig theory; in type $A$ this action can also be identified in the work of Henriques and Kamnitzer. We establish the relationship between the two actions. We show that the Berenstein-Kirillov group is a quotient of the cactus group. We use this to derive previously unknown relations in the Berenstein-Kirillov group. We also determine precise implications between subsets of relations in the two groups, which yields a presentation for cactus groups in terms of Bender-Knuth generators.
Concentration phenomena to a higher order Liouville equation

We study blow-up and quantization phenomena for a sequence of solutions $$(u_k)$$ to the prescribed Q-curvature problem $$\begin{aligned} (-\Delta )^nu_k= Q_ke^{2nu_k}\quad \text {in }\Omega \subset {\mathbb {R}}^{2n},\quad \int _{\Omega }e^{2nu_k}dx\le C, \end{aligned}$$ under natural assumptions on $$Q_k$$ . It is well-known that, up to a subsequence, either $$(u_k)$$ is bounded in a suitable norm, or there exists $$\beta _k\rightarrow \infty $$ such that $$ u_k=\beta _k(\varphi +o(1))$$ in $$\Omega \setminus (S_1\cup S_\varphi )$$ for some non-trivial non-positive n-harmonic function $$\varphi $$ and for a finite set $$S_1$$ , where $$S_\varphi $$ is the zero set of $$\varphi $$ . We prove quantization of the total curvature $$\int _{{\tilde{\Omega }}}Q_ke^{2nu_k}dx$$ on the region $${\tilde{\Omega }}\Subset (\Omega \setminus S_\varphi )$$ .
Index of minimal spheres and isoperimetric eigenvalue inequalities

In the present paper we use twistor theory in order to solve two problems related to harmonic maps from surfaces to Euclidean spheres $${\mathbb {S}}^n$$ . First, we propose a new approach to isoperimetric eigenvalue inequalities based on energy index. Using this approach we show that for any positive k, the k-th non-zero eigenvalue of the Laplacian on the real projective plane endowed with a metric of unit area, is maximized on the sequence of metrics converging to a union of $$(k-1)$$ identical copies of round sphere and a single round projective plane. This extends the results of Li and Yau (Invent Math 69(2):269–291, 1982) for $$k=1$$ ; Nadirashvili and Penskoi (Geom Funct Anal 28(5):1368–1393, 2018) for $$k=2$$ ; and confirms the conjecture made in (KNPP). Second, we improve the known lower bounds for the area index of minimal two-dimensional spheres and minimal projective planes in $${\mathbb {S}}^n$$ . In the course of the proof we establish a twistor correspondence for Jacobi fields, which could be of independent interest for the study of moduli spaces of harmonic maps.
Our Present Misfortune: Games and the Post-bureaucratic Colonization of Contingency

Anthropology is turning toward a new engagement with a central question of Weber: how do people come to understand the distribution of fortune in the world? Our discipline’s recent examination of the uses of the past prompts us to ask how stances toward the future are both the product of cultural logics and the target of institutional interests. In this article, I trace the engagement with contingency in anthropology and social thought, and then compare the nonchalant stance toward the future found in Greek society with the different disposition of individual gaming mastery in the digital domain, such as in Second Life, but also in the longest-running Greek state-sponsored game: Pro-Po. These examples illustrate how games are increasingly the sites for institutional efforts both to appropriate creativity and to generate distinctive subjectivities.
Exceptional Points of Degeneracy Directly Induced by Space–Time Modulation of a Single Transmission Line

We demonstrate how exceptional points of degeneracy (EPDs) are induced in a single transmission line (TL) directly by applying periodic space–time modulation to the per-unit-length distributed capacitance. In such space–time modulated (STM) TL, two eigenmodes coalesce into a single degenerate one, in their eigenvalues (wavenumbers), and eigenvectors (voltage–current states) when the system approaches the EPD condition. The EPD condition is achieved by tuning a parameter in the space–time modulation, such as spatial or temporal modulation frequency, or the modulation depth. We unequivocally demonstrate the occurrence of the EPD by showing that the bifurcation of the wavenumber around the EPD is described by the Puiseux fractional power series expansion. We show that the first-order expansion is sufficient to approximate well the dispersion diagram, and how this “exceptional” sensitivity of the STM-TL's wavenumber to tiny changes of any TL or modulation parameter enables a possible application as a highly sensitive TL sensor when operating at an EPD.
Exploiting Machine Learning to Efficiently Predict Multidimensional Optical Spectra in Complex Environments.

The excited-state dynamics of chromophores in complex environments determine a range of vital biological and energy capture processes. Time-resolved, multidimensional optical spectroscopies provide...
Mindfulness Improves Brain–Computer Interface Performance by Increasing Control Over Neural Activity in the Alpha Band

Brain-computer interfaces (BCIs) are promising tools for assisting patients with paralysis, but suffer from long training times and variable user proficiency. Mind-body awareness training (MBAT) can improve BCI learning, but how it does so remains unknown. Here, we show that MBAT allows participants to learn to volitionally increase alpha band neural activity during BCI tasks that incorporate intentional rest. We trained individuals in mindfulness-based stress reduction (MBSR; a standardized MBAT intervention) and compared performance and brain activity before and after training between randomly assigned trained and untrained control groups. The MBAT group showed reliably faster learning of BCI than the control group throughout training. Alpha-band activity in electroencephalogram signals, recorded in the volitional resting state during task performance, showed a parallel increase over sessions, and predicted final BCI performance. The level of alpha-band activity during the intentional resting state correlated reliably with individuals' mindfulness practice as well as performance on a breath counting task. Collectively, these results show that MBAT modifies a specific neural signal used by BCI. MBAT, by increasing patients' control over their brain activity during rest, may increase the effectiveness of BCI in the large population who could benefit from alternatives to direct motor control.
Malicious Experts Versus the Multiplicative Weights Algorithm in Online Prediction

We consider a prediction problem with two experts and a forecaster. We assume that one of the experts is honest and makes correct prediction with probability $\mu $ at each round. The other one is malicious, who knows true outcomes at each round and makes predictions in order to maximize the loss of the forecaster. Assuming the forecaster adopts the classical multiplicative weights algorithm, we find an upper bound (5) for the value function of the malicious expert, and also a lower bound (19) . Our results imply that the multiplicative weights algorithm cannot resist the corruption of malicious experts. We also show that an adaptive multiplicative weights algorithm is asymptotically optimal for the forecaster, and hence more resistant to the corruption of malicious experts.
Going Solo: The Law and Ethics of Childbirth During the COVID-19 Pandemic

The COVID-19 pandemic has had devastating effects on women’s reproductive lives. Women’s access to both abortion and contraceptive care has been restricted in many states across the U.S. Yet, the coronavirus has put a strain on another aspect of women’s reproductive rights: childbirth. In New York, for example, several hospitals instituted bans on all visitors in order to protect obstetric health care providers, as well as patients and newborn babies, from the risks posed by the virus. The policies were met with anger and confusion among expectant parents. An executive order issued in response to such criticism, overruling these policies, was described by some health professionals as unethical and ill-informed. Against this background this Essay maps the ethical and legal issues raised by childbirth visitation bans. It argues that the benefits of such visitation bans should be weighed against the implications they may have on laboring women’s emotional and physical well-being, considering the challenges they already face during facility-based childbirth. It then considers several national and international legal frameworks through which women’s birthing rights may be affirmed, also pointing out where they fall short. Lastly, this Essay makes recommendations for how such rights may be better addressed by different legal actors, including scholars, courts, and legislators.
Visual-Thermal Landmarks and Inertial Fusion for Navigation in Degraded Visual Environments

During the past decade, aerial robots have seen an unprecedented expansion in their utility as they take on more tasks which had typically been reserved for humans. With an ever widening domain of aerial robotic applications, including many mission critical tasks such as disaster response operations, search and rescue missions and infrastructure inspections taking place in GPS-denied environments, the need for reliable autonomous operation of aerial robots has become crucial. To accomplish their tasks, aerial robots operating in GPS-denied areas rely on a multitude of sensors to localize and navigate. Visible spectrum camera systems correspond to the most commonly used sensing modality due to their low cost and weight rendering them suitable for small aerial robots in indoor or broadly GPS-denied settings. However, in environments that are visually-degraded such as in conditions of poor illumination, low texture, or presence of obscurants including fog, smoke and dust, the reliability of visible light cameras deteriorates significantly. Nevertheless, maintaining reliable robot navigation in such conditions is essential if the robot is to perform many of the critical applications listed above. In contrast to visible light cameras, thermal cameras offer visibility in the infrared spectrum and can be used in a complementary manner with visible spectrum cameras for robot localization and navigation tasks, without paying the significant weight and power penalty typically associated with carrying other sensors such as 3D LiDARs or a RADAR. Exploiting this fact, in this work we present a multi-sensor fusion algorithm for reliable odometry estimation in GPS-denied and degraded visual environments. The proposed method utilizes information from both the visible and thermal spectra for landmark selection and prioritizes feature extraction from informative image regions based on a metric over spatial entropy. Furthermore, inertial sensing cues are integrated to improve the robustness of the odometry estimation process. The proposed method works in real-time, fully on-board an aerial robot. To verify our solution, a set of challenging experiments were conducted inside a) an obscurant-filed machine shop-like industrial environment, as well as b) a dark subterranean mine in the presence of heavy airborne dust.