cssi/SciSciGPT-SciSciNet huggingface dataset:
Chapter 16 – Controlled Drugs

This chapter deals with the main legislation covering the production, possession and use of Controlled Drugs (CDs). The different ways of classifying CDs for various purposes are discussed. The requirements for writing prescriptions are set out. Details are given of the safe custody requirements for stocks of drugs.
Trade adjustment policies and income distribution in three archetype developing economies

This paper explores quantitatively the macroeconomic and distributional impacts on non-oil producing, semi-industrial developing countries of external shocks originating in the world economy —in particular, rising costs of imports and shrinking export markets. The empirical analysis is done with a computable general equilibrium (CGE) model. The effects of the same external shock are modelled for three different archetype economies: a primary exporter, a manufacturing exporter, and a closed economy. Three different policy-adjustment regimes are considered: devaluation, premium rationing of imports (import licenses), and premium rationing in an environment with a fixed real wage for unskilled labor. By making simple assumptions about the way socioeconomic groups operate to influence decision-making, the paper also examines how the struggle between the gainers and losers is likely to affect the policy regime to be chosen.
Chapter 7 – Data Communications

Publisher Summary Data communications is the transmission of data between computer systems. At present, the trend is toward networks of computers that share information. Recent government rulings have tended to increase competition in the data communications industry. Because a computer transmits digital data and telephone lines transmit analog data, modems must be used to convert data between these different formats. The data communications controller receives signals from transmission lines, converts them into computerized form, and passes them onto the central computer system, thus relieving the central computer system of these chores. Simplex lines allow transmission in only one direction; half-duplex lines allow two-way transmission but in only one direction at a time; and full-duplex lines allow transmission in both directions simultaneously. Leased lines are dedicated to the user who is charged for the undivided attention of the line. Switched lines are available through the regular telephone switching system. Each terminal might be connected to the computer by a different set of communication lines each time the user dials the number of the computer system.
ALGEBRAIC ALGORITHMS FOR MATCHING AND MATROID PROBLEMS

We present new algebraic approaches for two well-known combinatorial problems: nonbipartite matching and matroid intersection. Our work yields new randomized algorithms that exceed or match the efficiency of existing algorithms. For nonbipartite matching, we obtain a simple, purely algebraic algorithm with running time O(n ω ) where n is the number of vertices and ω is the matrix multiplication exponent. This resolves the central open problem of Mucha and Sankowski (2004). For matroid intersection, our algorithm has running time O(nr ω-1 ) for matroids with n elements and rank r that satisfy some natural conditions.
Dual-frequency 2D IR photon echo of a hydrogen bond

Dual-frequency 2D IR heterodyned photon echo experiments with independently tunable mid-IR pulses are presented. Two-dimensional IR spectra acquired using three pulses in a sequence of 3, 3 and 6 μm allow observation of NH and CO stretching mode interactions. Intermolecular hydrogen bonding between NH and CO groups is characterized via observation of interaction of the NH and CO vibrational modes. Structural and dynamical parameters determined include the cross anharmonicity, angular constraints, and a correlation factor for the frequency distributions.
Model Uncertainty and Liquidity

Abstract Extreme market outcomes are often followed by a lack of liquidity and a lack of trade. This market collapse seems particularly acute for markets where traders rely heavily on a specific empirical model such as in derivative markets like the market for mortgage backed securities or credit derivatives. Moreover, the observed behavior of traders and institutions that places a large emphasis on “worst-case scenarios” through the use of “stress testing” and “Value-at-Risk” seems different than Savage expected utility would suggest. In this paper, we capture model-uncertainty using an Epstein and Wang [Epstein, L.G., Wang, T., 1994. Intertemporal asset pricing under Knightian uncertainty. Econometrica 62, 283–322] uncertainty-averse utility function with an ambiguous underlying asset-returns distribution. To explore the connection of uncertainty with liquidity, we specify a simple market where a monopolist financial intermediary makes a market for a propriety derivative security. The market-maker chooses bid and ask prices for the derivative, then, conditional on trade in this market, chooses an optimal portfolio and consumption. We explore how uncertainty can increase the bid–ask spread and, hence, reduces liquidity. Our infinite-horizon example produces short, dramatic decreases in liquidity even though the underlying environment is stationary. We show how these liquidity crises are closely linked to the uncertainty aversion effect on the optimal portfolio. Effectively, the uncertainty aversion can, at times, limit the ability of the market-maker to hedge a position and thus reduces the desirability of trade, and hence, liquidity.
Acyl-lipid desaturases and Vipp1 cooperate in cyanobacteria to produce novel omega-3 PUFA-containing glycolipids.

Dietary omega-3 (n-3), long chain (LC-, ≥ 20 carbons), polyunsaturated fatty acids (PUFAs) derived largely from marine animal sources protect against inflammatory processes and enhance brain development and function. With the depletion of natural stocks of marine animal sources and an increasing demand for n-3 LC-PUFAs, alternative, sustainable supplies are urgently needed. As a result, n-3 18-carbon and LC-PUFAs are being generated from plant or algal sources, either by engineering new biosynthetic pathways or by augmenting existing systems. We utilized an engineered plasmid encoding two cyanobacterial acyl-lipid desaturases (DesB and DesD, encoding Δ15 and Δ6 desaturases, respectively) and “vesicle-inducing protein in plastids” (Vipp1) to induce production of stearidonic acid (SDA, 18:4 n-3) at high levels in three strains of cyanobacteria (10, 17 and 27% of total lipids in Anabaena sp. PCC7120, Synechococcus sp. PCC7002, and Leptolyngbya sp. strain BL0902, respectively). Lipidomic analysis revealed that in addition to SDA, the rare anti-inflammatory n-3 LC-PUFA eicosatetraenoic acid (ETA, 20:4 n-3) was synthesized in these engineered strains, and ~ 99% of SDA and ETA was complexed to bioavailable monogalactosyldiacylglycerol (MGDG) and digalactosyldiacylglycerol (DGDG) species. Importantly, novel molecular species containing alpha-linolenic acid (ALA), SDA and/or ETA in both acyl positions of MGDG and DGDG were observed in the engineered Leptolyngbya and Synechococcus strains, suggesting that these could provide a rich source of anti-inflammatory molecules. Overall, this technology utilizes solar energy, consumes carbon dioxide, and produces large amounts of nutritionally important n-3 PUFAs and LC-PUFAs. Importantly, it can generate previously undescribed, highly bioavailable, anti-inflammatory galactosyl lipids. This technology could therefore be transformative in protecting ocean fisheries and augmenting the nutritional quality of human and animal food products.
Processing South Asian languages written in the Latin script: the Dakshina dataset

This paper describes the Dakshina dataset, a new resource consisting of text in both the Latin and native scripts for 12 South Asian languages. The dataset includes, for each language: 1) native script Wikipedia text; 2) a romanization lexicon; and 3) full sentence parallel data in both a native script of the language and the basic Latin alphabet. We document the methods used for preparation and selection of the Wikipedia text in each language; collection of attested romanizations for sampled lexicons; and manual romanization of held-out sentences from the native script collections. We additionally provide baseline results on several tasks made possible by the dataset, including single word transliteration, full sentence transliteration, and language modeling of native script and romanized text.
The impact of fiscal consolidations on growth in sub-Saharan Africa

This paper examines the output effects of changes in public expenditure and revenue in sub-Saharan African countries during 1990–2016. Fiscal multipliers in sub-Saharan Africa are somewhat smaller than those estimated in the literature for advanced and emerging economies. The effect of changes in fiscal policy on output depends on the composition: Cutting public investment has a larger effect on output than cutting public consumption or raising revenue. Episodes of fiscal consolidation have short- and medium-term output effects, but here, too, composition matters: Fiscal consolidations based on reducing public investment have the largest effect on output, while fiscal consolidations based on revenue mobilization are less harmful. These findings suggest that the negative impact on growth can be mitigated through the design of fiscal adjustment.
Moduli of Polarized Calabi—Yau Pairs

We prove that the irreducible components of the moduli space of polarized Calabi–Yau pairs are projective.
Balancing Training for Multilingual Neural Machine Translation

When training multilingual machine translation (MT) models that can translate to/from multiple languages, we are faced with imbalanced training sets: some languages have much more training data than others. Standard practice is to up-sample less resourced languages to increase representation, and the degree of up-sampling has a large effect on the overall performance. In this paper, we propose a method that instead automatically learns how to weight training data through a data scorer that is optimized to maximize performance on all test languages. Experiments on two sets of languages under both one-to-many and many-to-one MT settings show our method not only consistently outperforms heuristic baselines in terms of average performance, but also offers flexible control over the performance of which languages are optimized.
A Complete Realization of the Orbits of Generalized Derivatives of Quasiregular Mappings

Quasiregular maps are differentiable almost everywhere and are analogous to holomorphic maps in the plane for higher real dimensions. Introduced by Gutlyanskii et al. (Ann Acad Sci Fenn 25:101–130, 2000), the infinitesimal space is a generalization of the notion of derivatives for quasiregular maps. Evaluation of all elements in the infinitesimal space at a particular point is called the orbit space. We prove that any compact connected subset of $$\mathbb {R}^n\setminus \{0\}$$ can be realized as an orbit space of a quasiconformal map. To that end, we construct analogues of logarithmic spiral maps and interpolation between radial stretch maps in higher dimensions. For the construction of such maps, we need to implement a new tool called the Zorich transform, which is a direct analogue of the logarithmic transform. The Zorich transform could have further applications in quasiregular dynamics.
Scalable surrogate deconvolution for identification of partially-observable systems and brain modeling

OBJECTIVE For many biophysical systems, direct measurement of all state-variables, in - vivo is not feasible. Thus, a key challenge in biological modeling and signal processing is to reconstruct the activity and structure of interesting biological systems from indirect measurements. These measurements are often generated by approximately linear time-invariant dynamical interactions with the hidden system and may therefore be described as a convolution of hidden state-variables with an unknown kernel. APPROACH In the current work, we present an approach termed surrogate deconvolution, to directly identify such coupled systems (i.e. parameterize models). Surrogate deconvolution reframes certain non linear partially-observable identification problems, which are common in neuroscience/biology, as analytical objectives that are compatible with almost any user-chosen optimization procedure. MAIN RESULTS We show that the proposed technique is highly scalable, low in computational complexity, and performs competitively with the current gold-standard in partially-observable system estimation: the joint Kalman Filters (Unscented and Extended). We show the benefits of surrogate deconvolution for model identification when applied to simulations of the Local Field Potential and blood oxygen level dependent (BOLD) signal. Lastly, we demonstrate the empirical stability of Hemodynamic Response Function (HRF) kernel estimates for Mesoscale Individualized NeuroDynamic (MINDy) models of individual human brains. The recovered HRF parameters demonstrate reliable individual variation as well as a stereotyped spatial distribution, on average. SIGNIFICANCE These results demonstrate that surrogate deconvolution promises to enhance brain-modeling approaches by simultaneously and rapidly fitting large-scale models of brain networks and the physiological processes which generate neuroscientific measurements (e.g. hemodynamics for BOLD fMRI).
A Bayesian analysis of nuclear deformation properties with Skyrme energy functionals

In spite of numerous scientific and practical applications, there is still no comprehensive theoretical description of the nuclear fission process based solely on protons, neutrons and their interactions. The most advanced simulations of fission are currently carried out within nuclear density functional theory (DFT). In spite of being fully quantum-mechanical and rooted in the theory of nuclear forces, DFT still depends on a dozen or so parameters characterizing the energy functional. Calibrating these parameters on experimental data results in uncertainties that must be quantified for applications. This task is very challenging because of the high computational cost of DFT calculations for fission. In this paper, we use Gaussian processes to build emulators of DFT models in order to quantify and propagate statistical uncertainties of theoretical predictions for a range of nuclear deformations relevant to describing the fission process.
Online Matching with Stochastic Rewards: Optimal Competitive Ratio via Path Based Formulation

The problem of online matching with stochastic rewards is a generalization of the online bipartite matching problem where each edge has a probability of success. When a match is made it succeeds with the probability of the corresponding edge. Introducing this model, Mehta and Panigrahi (FOCS 2012) focused on the special case of identical edge probabilities. Comparing against a deterministic offline LP, they showed that the Ranking algorithm of Karp et al. (STOC 1990) is 0.534 competitive and proposed a new online algorithm with an improved guarantee of 0.567 for vanishingly small probabilities. For the case of vanishingly small but heterogeneous probabilities Mehta et al. (SODA 2015), gave a 0.534 competitive algorithm against the same LP benchmark. For the more general vertex-weighted version of the problem, to the best of our knowledge, no results being 1/2 were previously known even for identical probabilities. We focus on the vertex-weighted version and give two improvements. First, we show that a natural generalization of the Perturbed-Greedy algorithm of Aggarwal et al. (SODA 2011), is (1-1/e) competitive when probabilities decompose as a product of two factors, one corresponding to each vertex of the edge. This is the best achievable guarantee as it includes the case of identical probabilities and in particular, the classical online bipartite matching problem. Second, we give a deterministic 0.596 competitive algorithm for the previously well studied case of case of fully heterogeneous but vanishingly small edge probabilities. A key contribution of our approach is the use of novel path-based formulations and a generalization of the primal-dual scheme of Devanur et al. (SODA 2013). These allow us to compare against the natural benchmark of clairvoyant (offline) algorithms that know the sequence of arrivals and the edge probabilities in advance, but not the outcomes of potential matches. These ideas may be of independent interest in other online settings with post-allocation stochasticity.
Crosscap numbers of alternating knots via unknotting splices

Ito–Takimura recently defined a splice-unknotting number u−(D) for knot diagrams. They proved that this number provides an upper bound for the crosscap number of any prime knot, asking whether equa...
Homotopy types of abstract elementary classes

Abstract We prove that for any homotopy type X, there is an abstract elementary class C , with joint embedding, almagamation and no maximal models such that the classifying space realizes the homotopy type X. We provide a few explicit examples.
A dynamic fountain model for lunar dust

Abstract There is much evidence to show that lunar “horizon glow” and “streamers” observed at the terminator are caused by sunlight scattered by dust grains originating from the surface. The dust grains and lunar surface are electrostatically charged by the Moon’s interaction with the local plasma environment and the photoemission of electrons due to solar UV and X-rays. This effect causes the like-charged surface and dust particles to repel each other, and creates a near-surface electric field. Previous models have explained micron-sized dust observed at ∼10 cm above the surface, by suggesting that charged grains “levitate” in the local electric field; however this cannot account for observations of 0.1 μm-scale grains at ∼100 km altitude. In order to explain the high-altitude dust observations, we propose a dynamic “fountain” model in which charged dust grains follow ballistic trajectories, subsequent to being accelerated upward through a narrow sheath region by the surface electric field. These dust grains could affect the optical quality of the lunar environment for astronomical observations and interfere with exploration activities.
Redundant Trojan horse and endothelial-circulatory mechanisms for host-mediated spread of Candida albicans yeast.

The host innate immune system has developed elegant processes for the detection and clearance of invasive fungal pathogens. These strategies may also aid in the spread of pathogens in vivo, although technical limitations have previously hindered our ability to view the host innate immune and endothelial cells to probe their roles in spreading disease. Here, we have leveraged zebrafish larvae as a model to view the interactions of these host processes with the fungal pathogen Candida albicans in vivo. We examined three potential host-mediated mechanisms of fungal spread: movement inside phagocytes in a “Trojan Horse” mechanism, inflammation-assisted spread, and endothelial barrier passage. Utilizing both chemical and genetic tools, we systematically tested the loss of neutrophils and macrophages and the loss of blood flow on yeast cell spread. Both neutrophils and macrophages respond to yeast-locked and wild type C. albicans in our model and time-lapse imaging revealed that macrophages can support yeast spread in a “Trojan Horse” mechanism. Surprisingly, loss of immune cells or inflammation does not alter dissemination dynamics. On the other hand, when blood flow is blocked, yeast can cross into blood vessels but they are limited in how far they travel. Blockade of both phagocytes and circulation reduces rates of dissemination and significantly limits the distance of fungal spread from the infection site. Together, this data suggests a redundant two-step process whereby (1) yeast cross the endothelium inside phagocytes or via direct uptake, and then (2) they utilize blood flow or phagocytes to travel to distant sites.
Interregional Demand for Workers and the Effects of Labor Income Taxation

We study the short-run impacts of labor income taxation in an aggregate economy of N>2 regions. The distinct regions demand workers. Each region is endowed with one unit of immobile capital. The aggregate economy also has one unit of labor that is mobile across the regions. All regions produce a final good with identical Cobb-Douglas production functions. The price of output is normalized to unity. We perform five tasks. First, we focus on the benchmark case in which no region taxes either capital or labor. We find the equilibrium wage, the allocation of workers across the regions, and the total income of labor and capital. Second, we study the impact of a tax τ on labor income in region 1 when the other N-1 regions do not tax labor income. We ascertain the after-tax return to labor in region 1, the equilibrium wage, and the allocation of labor across the regions. Third, we compute the total income of capital and labor and the tax revenue in region 1. Fourth, we discuss whether workers in region 1 are better off with a tax on labor income. Finally, we comment on the policy implications of our research.
Diffuse band extinction and polarization in core-mantle grains

Diffuse band shapes in both extinction and polarization are calculated for interstellar coremantle particles for varying size distributions of mantle thickness. It is shown that no matter whether the source of the bands is in the silicate cores or the accreted icy mantles the polarization shapes are highly asymmetric for all mantel thicknesses. The extinction band shapes are significantly less asymmetric although the effect is clearly present. The only apparent possibility for producing symmetric band shapes in the dust grains is in the very small bare particles in interstellar space which, if they are aligned and produce the λ 2200 band, must exhibit a strong polarization effect in this region.
Polymer escape through a three dimensional double-nanopore system

We study the escape dynamics of a double-stranded DNA (dsDNA) through an idealized double nanopore geometry subject to two equal and opposite forces (tug-of-war) using Brownian dynamics (BD) simulation. In addition to the geometrical restrictions imposed on the cocaptured dsDNA segment in between the pores, the presence of tug-of-war forces at each pore results in a variation of the local chain stiffness for the segment of the chain in between the pores, which increases the overall stiffness of the chain. We use the BD simulation results to understand how the intrinsic chain stiffness and the tug-of-war forces affect the escape dynamics by monitoring the local chain persistence length lp, the residence time of the individual monomers W(m) in the nanopores, and the chain length dependence of the escape time ⟨τ⟩ and its distribution. Finally, we generalize the scaling theory for the unbiased single nanopore translocation for a fully flexible chain for the escape of a semi-flexible chain through a double nanopore in the presence of tug-of-war forces. We establish that the stiffness dependent part of the escape time is approximately independent of the translocation mechanism so that ⟨τ⟩∼lp2/D+2, and therefore, the generalized escape time for a semi-flexible chain can be written as ⟨τ⟩=ANαlp2/D+2. We use the BD simulation results to compare the predictions of the scaling theory. Our numerical studies supplemented by scaling analysis provide fundamental insights to design new experiments where a dsDNA moves slowly through a series of graphene nanopores.
Experimental Demonstration of a Reconfigurable Coupled Oscillator Platform to Solve the Max-Cut Problem

In this work, we experimentally demonstrate an integrated circuit (IC) of 30 relaxation oscillators with reconfigurable capacitive coupling to solve the NP-Hard maximum cut (Max-Cut) problem. We show that under the influence of an external second-harmonic injection signal, the oscillator phases exhibit a bipartition that can be used to calculate a high-quality approximate Max-Cut solution. Leveraging the all-to-all reconfigurable coupling architecture, we experimentally evaluate the computational properties of the oscillators using randomly generated graph instances of varying size and edge density ( $\eta $ ). Furthermore, comparing the Max-Cut solutions with the optimal values, we show that the oscillators (after simple postprocessing) produce a Max-Cut that is within 99% of the optimal value in 28 of the 36 measured graphs; importantly, the oscillators are particularly effective in dense graphs with the Max-Cut being optimal in seven out of nine measured graphs with $\eta =0.8$ . Our work marks a step toward creating an efficient, room-temperature-compatible non-Boolean hardware-based solver for hard combinatorial optimization problems.
Flying batteries: In-flight battery switching to increase multirotor flight time

We present a novel approach to increase the flight time of a multirotor via mid-air docking and in-flight battery switching. A main quadcopter flying using a primary battery has a docking platform attached to it. A ‘flying battery’ – a small quadcopter carrying a secondary battery – is equipped with docking legs that can mate with the main quadcopter’s platform. Connectors between the legs and the platform establish electrical contact on docking, and enable power transfer from the secondary battery to the main quadcopter. A custom-designed circuit allows arbitrary switching between the primary battery and secondary battery. We demonstrate the concept in a flight experiment involving repeated docking, battery switching, and undocking. This is shown in the video attachment. The experiment increases the flight time of the main quadcopter by a factor of 4.7× compared to solo flight, and 2.2× a theoretical limit for that given multirotor. Importantly, this increase in flight time is not associated with a large increase in overall vehicle mass or size, leaving the main quadcopter in fundamentally the same safety class.
Motion2Vec: Semi-Supervised Representation Learning from Surgical Videos

Learning meaningful visual representations in an embedding space can facilitate generalization in downstream tasks such as action segmentation and imitation. In this paper, we learn a motion-centric representation of surgical video demonstrations by grouping them into action segments/subgoals/options in a semi-supervised manner. We present Motion2Vec, an algorithm that learns a deep embedding feature space from video observations by minimizing a metric learning loss in a Siamese network: images from the same action segment are pulled together while pushed away from randomly sampled images of other segments, while respecting the temporal ordering of the images. The embeddings are iteratively segmented with a recurrent neural network for a given parametrization of the embedding space after pre-training the Siamese network. We only use a small set of labeled video segments to semantically align the embedding space and assign pseudo-labels to the remaining unlabeled data by inference on the learned model parameters. We demonstrate the use of this representation to imitate surgical suturing kinematic motions from publicly available videos of the JIGSAWS dataset. Results give 85.5% segmentation accuracy on average suggesting performance improvement over several state-of-the-art baselines, while kinematic pose imitation gives 0.94 centimeter error in position per observation on the test set. Videos, code and data are available at: https://sites.google.com/view/motion2vec
Provably Efficient Third-Person Imitation from Offline Observation

Domain adaptation in imitation learning represents an essential step towards improving generalizability. However, even in the restricted setting of third-person imitation where transfer is between isomorphic Markov Decision Processes, there are no strong guarantees on the performance of transferred policies. We present problem-dependent, statistical learning guarantees for third-person imitation from observation in an offline setting, and a lower bound on performance in the online setting.
Student Self-Determination following Developmental Education Reform in Florida's Community Colleges

BackgroundThis multiple case study explores the self-determination needs of academically underprepared students. The context for our study was a sweeping redesign of developmental education (DE) in...
ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia

Algorithmic systems---from rule-based bots to machine learning classifiers---have a long history of supporting the essential work of content moderation and other curation work in peer production projects. From counter-vandalism to task routing, basic machine prediction has allowed open knowledge projects like Wikipedia to scale to the largest encyclopedia in the world, while maintaining quality and consistency. However, conversations about how quality control should work and what role algorithms should play have generally been led by the expert engineers who have the skills and resources to develop and modify these complex algorithmic systems. In this paper, we describe ORES: an algorithmic scoring service that supports real-time scoring of wiki edits using multiple independent classifiers trained on different datasets. ORES decouples several activities that have typically all been performed by engineers: choosing or curating training data, building models to serve predictions, auditing predictions, and developing interfaces or automated agents that act on those predictions. This meta-algorithmic system was designed to open up socio-technical conversations about algorithms in Wikipedia to a broader set of participants. In this paper, we discuss the theoretical mechanisms of social change ORES enables and detail case studies in participatory machine learning around ORES from the 5 years since its deployment.
How Taxing is Corruption on International Investors

This paper studies the effect of corruption on foreign direct investment. The sample covers bilateral investment from twelve source countries to 45 host countries. There are two central findings. First, a rise in either the tax rate on multinational firms or the corruption level in a host country reduces inward foreign direct investment (FDI). In a benchmark estimation, an increase in the corruption level from that of Singapore to that of Mexico would have the same negative effect on inward FDI as raising the tax rate by fifty percentage points. Second, American investors are averse to corruption in host countries, but not necessarily more so than average OECD investors, in spite of the U.S. Foreign Corrupt Practices Act of 1977.
RECURRENT AND LIFE-THREATENING PERIPARTUM CARDIOMYOPATHY: DIAGNOSIS, DELIVERY CONSIDERATIONS AND MANAGEMENT

Peripartum cardiomyopathy (PPCM) is an idiopathic reduction in LV systolic function (ejection fraction (EF) <45%) towards the end of pregnancy or in the months following delivery. Despite treatment, recurrence is frequent and can be fatal in subsequent pregnancies. A 38-year-old African American
Where are we now?: a large benchmark study of recent symbolic regression methods

In this paper we provide a broad benchmarking of recent genetic programming approaches to symbolic regression in the context of state of the art machine learning approaches. We use a set of nearly 100 regression benchmark problems culled from open source repositories across the web. We conduct a rigorous benchmarking of four recent symbolic regression approaches as well as nine machine learning approaches from scikit-learn. The results suggest that symbolic regression performs strongly compared to state-of-the-art gradient boosting algorithms, although in terms of running times is among the slowest of the available methodologies. We discuss the results in detail and point to future research directions that may allow symbolic regression to gain wider adoption in the machine learning community.
Looking for Intermediate-Mass Black Holes

A discussion of the entropy of the universe leads to the suggestion of very many intermediate-mass black holes between thirty and three hundred thousand solar masses in the halo. It is consistent with observations on wide binaries as well as microlensing and considerations of disk stability that such IMBHs constitute all cold dark matter.
New instanton effects in string theory

We describe a new class of instanton effects in string compactifications that preserve only = 1 supersymmetry in four dimensions. As is well-known, worldsheet or brane instantons in such a background can sometimes contribute to an effective superpotential for the moduli of the compactification. We generalize this phenomenon by showing that such instantons can also contribute to new multi-fermion and higher-derivative F-terms in the low-energy effective action. We consider in most detail the example of heterotic compactification on a Calabi-Yau threefold X with gauge bundle V, in which case we study worldsheet instanton effects that deform the complex structure of the moduli space associated to X and V. We also give new, slightly more economical derivations of some previous results about worldsheet instantons in Type IIA Calabi-Yau compactifications.
Pseudo-likelihood based logistic regression for estimating COVID-19 infection and case fatality rates by gender, race, and age in California

In emerging epidemics, early estimates of key epidemiological characteristics of the disease are critical for guiding public policy. In particular, identifying high-risk population subgroups aids policymakers and health officials in combating the epidemic. This has been challenging during the coronavirus disease 2019 (COVID-19) pandemic because governmental agencies typically release aggregate COVID-19 data as summary statistics of patient demographics. These data may identify disparities in COVID-19 outcomes between broad population subgroups, but do not provide comparisons between more granular population subgroups defined by combinations of multiple demographics. We introduce a method that helps to overcome the limitations of aggregated summary statistics and yields estimates of COVID-19 infection and case fatality rates - key quantities for guiding public policy related to the control and prevention of COVID-19 - for population subgroups across combinations of demographic characteristics. Our approach uses pseudo-likelihood based logistic regression to combine aggregate COVID-19 case and fatality data with population-level demographic survey data to estimate infection and case fatality rates for population subgroups across combinations of demographic characteristics. We illustrate our method on California COVID-19 data to estimate test-based infection and case fatality rates for population subgroups defined by gender, age, and race/ethnicity. Our analysis indicates that in California, males have higher test-based infection rates and test-based case fatality rates across age and race/ethnicity groups, with the gender gap widening with increasing age. Although elderly infected with COVID-19 are at an elevated risk of mortality, the test-based infection rates do not increase monotonically with age. The workforce population, especially, has a higher test-based infection rate than children, adolescents, and other elderly people in their 60-80. LatinX and African Americans have higher test-based infection rates than other race/ethnicity groups. The subgroups with the highest 5 test-based case fatality rates are all-male groups with race as African American, Asian, Multi-race, LatinX, and White, followed by African American females, indicating that African Americans are an especially vulnerable California subpopulation.
The Cluster of Galaxies Surrounding Cygnus A

We report optical imaging and spectroscopy of 41 galaxies in a 22' square region surrounding Cygnus A. The results show that there is an extensive rich cluster associated with Cyg A of Abell richness of at least 1 and possibly as high as 4. The velocity histogram has two peaks, one centered on Cyg A and a more significant peak redshifted by about 2060 km s-1 from the velocity of Cyg A. The dynamical centroid of the spatial distribution is also shifted somewhat to the northwest. However, statistical tests show only weak evidence that there are two distinct clusters. The entire system has a velocity dispersion of 1581 km s-1, which is slightly larger than other, well-studied examples of rich clusters.
Counterexamples, covering systems, and zero-one laws for inhomogeneous approximation

We develop the inhomogeneous counterpart to some key aspects of the story of the Duffin–Schaeffer Conjecture (1941). Specifically, we construct counterexamples to a number of candidates for a sans-...
The dehydration of water worlds via atmospheric losses

We present a three-species multi-fluid MHD model (H$^+$, H$_2$O$^+$ and e$^-$), endowed with the requisite atmospheric chemistry, that is capable of accurately quantifying the magnitude of water ion losses from exoplanets. We apply this model to a water world with Earth-like parameters orbiting a Sun-like star for three cases: (i) current normal solar wind conditions, (ii) ancient normal solar wind conditions, and (iii) one extreme "Carrington-type" space weather event. We demonstrate that the ion escape rate for (ii), with a value of 6.0$\times$10$^{26}$ s$^{-1}$, is about an order of magnitude higher than the corresponding value of 6.7$\times$10$^{25}$ s$^{-1}$ for (i). Studies of ion losses induced by space weather events, where the ion escape rates can reach $\sim$ 10$^{28}$ s$^{-1}$, are crucial for understanding how an active, early solar-type star (e.g., with frequent coronal mass ejections) could have accelerated the depletion of the exoplanet's atmosphere. We briefly explore the ramifications arising from the loss of water ions, especially for planets orbiting M-dwarfs where such effects are likely to be significant.
The Role of a Massive Central Singularity in Galactic Mergers on the Survival of the Core Fundamental Plane

In order for the core fundamental plane (CFP) to endure, small ellipticals must not survive mergers with giant ellipticals, despite the fact that the small secondary galaxy can be as much as a million times more dense than the primary. However, our previous set of experiments has shown that, for purely stellar galaxies, the secondary does in fact survive mergers with primaries up to 100 times more massive. In this paper, we demonstrate the effect that a massive central black hole has on mergers of CFP galaxies. Our results indicate that the addition of a massive central singularity inside the primary galaxy provides strong enough tidal forces to destroy dense CFP companions when the secondary's orbital decay is sufficiently elongated. The destruction of the secondary acts to preserve the original low central density profile of the primary in the giant merger remnant, which allows the remnant to remain on the CFP. On more circular orbits, however, the secondary is disrupted only near the end of the merger, and the degree to which the secondary particles disperse depends on the amount of orbital energy left in the merger. Hence, there are some mergers for which the CFP is not preserved in our experiments. We find that if the secondary is not dispersed, it forms a spinning stellar disk with a central density that forces the merger remnant off the CFP.
Stability of stationary-axisymmetric black holes in vacuum general relativity to axisymmetric electromagnetic perturbations

We consider arbitrary stationary and axisymmetric black holes in general relativity in dimensions (with ) that satisfy the vacuum Einstein equation and have a non-degenerate horizon. We prove that the canonical energy of axisymmetric electromagnetic perturbations is positive definite. This establishes that all vacuum black holes are stable to axisymmetric electromagnetic perturbations. Our results also hold for asymptotically de Sitter black holes that satisfy the vacuum Einstein equation with a positive cosmological constant. Our results also apply to extremal black holes provided that the initial perturbation vanishes in a neighborhood of the horizon.
Improving the LSST dithering pattern and cadence for dark energy studies

The Large Synoptic Survey Telescope (LSST) will explore the entire southern sky over 10 years starting in 2022 with unprecedented depth and time sampling in six filters, ugrizy. Artificial power on the scale of the 3.5 deg LSST field-of-view will contaminate measurements of baryonic acoustic oscillations (BAO), which fall at the same angular scale at redshift z ~ 1. Using the HEALPix framework, we demonstrate the impact of an “un- dithered” survey, in which 17% of each LSST field-of-view is overlapped by neighboring observations, generating a honeycomb pattern of strongly varying survey depth and significant artificial power on BAO angular scales. We find that adopting large dithers (i.e., telescope pointing o sets) of amplitude close to the LSST field-of-view radius reduces artificial structure in the galaxy distribution by a factor of ~10. We propose an observing strategy utilizing large dithers within the main survey and minimal dithers for the LSST Deep Drilling Fields. We show that applying various magnitude cutos can further increase survey uniformity. We find that a magnitude cut of r < 27:3 removes significant spurious power from the angular power spectrum with a minimal reduction in the total number of observed galaxies over the ten-year LSST run. We also determine the effectiveness of the observing strategy for Type Ia SNe and predict that the main survey will contribute ~100,000 Type Ia SNe. We propose a concentrated survey where LSST observes one-third of its main survey area each year, increasing the number of main survey Type Ia SNe by a factor of ~1.5, while still enabling the successful pursuit of other science drivers.
Erupting Dwarf Novae in the Large Magellanic Cloud

We report the first likely detections of erupting dwarf novae (DNe) in an external galaxy: the Large Magellanic Cloud. Six candidates were isolated from approximately a million stars observed every second night over 11 nights with the Cerro Tololo Inter-American Observatory 8K × 8K Mosaic2 CCD imager. Artificial dwarf nova and completeness tests suggest that we are seeing only the brightest of the LMC DNe, probably SS Cygni–like cataclysmic variables (CVs), but possibly SU UMa type cataclysmics undergoing superoutbursts. We derive crude but useful limits on the LMC DN surface density and on the number of DNe in the LMC. Many thousands of CVs in the Magellanic Clouds can be discovered and characterized with 8 m class telescopes.
The Strikingly Similar Relation between Satellite and Central Galaxies and Their Dark Matter Halos Since z=2

Satellite galaxies in rich clusters are subject to numerous physical processes that can significantly influence their evolution. However, the typical L* satellite galaxy resides in much lower mass galaxy groups, where the processes capable of altering their evolution are generally weaker and have had less time to operate. To investigate the extent to which satellite and central galaxy evolution differs, we separately model the stellar mass-halo mass (M *-Mh ) relation for these two populations over the redshift interval 0 < z < 1. This relation for central galaxies is constrained by the galaxy stellar mass function while the relation for satellite galaxies is constrained against recent measurements of the galaxy two-point correlation function (2PCF). Our approach does not rely on the abundance matching technique but instead adopts a flexible functional form for the relation between satellite galaxy stellar mass and subhalo mass, where subhalo mass is considered as the maximum mass that a subhalo has ever reached in its merger history, M peak. At z ~ 0 the satellites, on average, have ~10% larger stellar masses at fixed M peak compared to central galaxies of the same halo mass (although the two relations are consistent at 2σ-3σ for M peak 1013 M ☉). This is required in order to reproduce the observed stellar mass-dependent 2PCF and satellite fractions. At low masses our model slightly under-predicts the correlation function at ~1 Mpc scales. At z ~ 1 the satellite and central galaxy M *-Mh relations are consistent within the errors, and the model provides an excellent fit to the clustering data. At present, the errors on the clustering data at z ~ 2 are too large to constrain the satellite model. A simple model in which satellite and central galaxies share the same M *-Mh relation is able to reproduce the extant z ~ 2 clustering data. We speculate that the striking similarity between the satellite and central galaxy M *-Mh relations since z ~ 2 arises because the central galaxy relation evolves very weakly with time and because the stellar mass of the typical satellite galaxy has not changed significantly since it was accreted. The reason for this last point is not yet entirely clear, but it is likely related to the fact that the typical ~L* satellite galaxy resides in a poor group where transformation processes are weak and lifetimes are short.
Electromagnetism as Quantum Physics

One can interpret the Dirac equation either as giving the dynamics for a classical field or a quantum wave function. Here I examine whether Maxwell’s equations, which are standardly interpreted as giving the dynamics for the classical electromagnetic field, can alternatively be interpreted as giving the dynamics for the photon’s quantum wave function. I explain why this quantum interpretation would only be viable if the electromagnetic field were sufficiently weak, then motivate a particular approach to introducing a wave function for the photon (following Good in Phys Rev 105(6):1914–1919, 1957). This wave function ultimately turns out to be unsatisfactory because the probabilities derived from it do not always transform properly under Lorentz transformations. The fact that such a quantum interpretation of Maxwell’s equations is unsatisfactory suggests that the electromagnetic field is more fundamental than the photon.
A ONE-SIDED PRIME IDEAL PRINCIPLE FOR NONCOMMUTATIVE RINGS

Completely prime right ideals are introduced as a one-sided generalization of the concept of a prime ideal in a commutative ring. Some of their basic properties are investigated, pointing out both similarities and differences between these right ideals and their commutative counterparts. We prove the Completely Prime Ideal Principle, a theorem stating that right ideals that are maximal in a specific sense must be completely prime. We offer a number of applications of the Completely Prime Ideal Principle arising from many diverse concepts in rings and modules. These applications show how completely prime right ideals control the one-sided structure of a ring, and they recover earlier theorems stating that certain noncommutative rings are domains (namely, proper right PCI rings and rings with the right restricted minimum condition that are not right artinian). In order to provide a deeper understanding of the set of completely prime right ideals in a general ring, we study the special subset of comonoform right ideals.
Solitons in a Bilocal Field Theory

We obtain a bilocal classical field theory as the large N limit of the chiral Gross-Neveu (or non-Abelian Thirring) model. Exact classical solutions that describe topological solitons are obtained. It is shown that their mass spectrum agrees with the large N limit of the spectrum of the chiral Gross-Neveu model.
Noise-Contrastive Estimation for Multivariate Point Processes

The log-likelihood of a generative model often involves both positive and negative terms. For a temporal multivariate point process, the negative term sums over all the possible event types at each time and also integrates over all the possible times. As a result, maximum likelihood estimation is expensive. We show how to instead apply a version of noise-contrastive estimation---a general parameter estimation method with a less expensive stochastic objective. Our specific instantiation of this general idea works out in an interestingly non-trivial way and has provable guarantees for its optimality, consistency and efficiency. On several synthetic and real-world datasets, our method shows benefits: for the model to achieve the same level of log-likelihood on held-out data, our method needs considerably fewer function evaluations and less wall-clock time.