cssi/SciSciGPT-SciSciNet huggingface dataset:
Perturbed-History Exploration in Stochastic Linear Bandits.

We propose a new online algorithm for minimizing the cumulative regret in stochastic linear bandits. The key idea is to build a perturbed history, which mixes the history of observed rewards with a pseudo-history of randomly generated i.i.d. pseudo-rewards. Our algorithm, perturbed-history exploration in a linear bandit (LinPHE), estimates a linear model from its perturbed history and pulls the arm with the highest value under that model. We prove a $\tilde{O}(d \sqrt{n})$ gap-free bound on the expected $n$-round regret of LinPHE, where $d$ is the number of features. Our analysis relies on novel concentration and anti-concentration bounds on the weighted sum of Bernoulli random variables. To show the generality of our design, we extend LinPHE to a logistic reward model. We evaluate both algorithms empirically and show that they are practical.
Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching:

This article presents a robotic pick-and-place system that is capable of grasping and recognizing both known and novel objects in cluttered environments. The key new feature of the system is that i...
A Novel Approach to the Automatic Designation of Predefined Census Enumeration Areas and Population Sampling Frames : A Case Study in Somalia

Enumeration areas are the operational geographic units for the collection, dissemination, and analysis of census data and are often used as a national sampling frame for various types of surveys. Traditionally, enumeration areas are created by manually digitizing small geographic units on high-resolution satellite imagery or physically walking the boundaries of units, both of which are highly time, cost, and labor intensive. In addition, creating enumeration areas requires considering the size of the population and area within each unit. This is an optimization problem that can best be solved by a computer. This paper, for the first time, produces an automatic designation of predefined census enumeration areas based on high-resolution gridded populationand settlement data sets and using publicly available natural and administrative boundaries. This automated approach is compared with manually digitized enumeration areas that were created in urban areas in Mogadishu and Hargeisa for the United Nations Population Estimation Survey for Somalia in 2014. The automatically generated enumeration areas are consistent with standard enumeration areas, including having identifiable boundaries to field teams on the ground, and appropriate sizing and population for coverage by an enumerator. Furthermore, the automated urban enumeration areas have no gaps. The paper extends this work to rural Somalia, for which no records exist of previous enumeration area demarcations. This work shows the time,labor, and cost-saving value of automated enumeration area delineation and points to the potential for broadlyavailable tools that are suitable for low-income and data-poor settings but applicable to potentially wider contexts.
Ray Tracing Analysis for UAV-Assisted Integrated Access and Backhaul Millimeter Wave Networks

The use of Millimeter-wave (mmWave) spectrum in cellular communications has recently attracted growing interest to support the expected massive increase in traffic demands. However, the high path-loss at mmWave frequencies poses severe challenges. In this paper, we analyze the potential coverage gains of using unmanned aerial vehicles (UAVs), as hovering relays, in integrated access and backhaul (IAB) mmWave cellular scenarios. Specifically, we utilize the WinProp software package, which employs ray tracing methodology, to study the propagation characteristics of outdoor mmWave channels at 30 and 60 GHz frequency bands in a Manhattan-like environment. In doing so, we propose the implementation of amplify-and-forward (AF) and decode-and-forward (DF) relaying mechanisms in the WinProp software. We show how the 3D deployment of UAVs can be defined based on the coverage ray tracing maps at access and backhaul links. Furthermore, we propose an adaptive UAV transmission power for the AF relaying. We demonstrate, with the aid of ray tracing simulations, the performance gains of the proposed relaying modes in terms of downlink coverage, and the received signal to interference and noise ratio (SINR).
Reinforcement Learning based Dynamic Model Selection for Short-Term Load Forecasting

With the growing prevalence of smart grid technology, short-term load forecasting (STLF) becomes particularly important in power system operations. There is a large collection of methods developed for STLF, but selecting a suitable method under varying conditions is still challenging. This paper develops a novel reinforcement learning based dynamic model selection (DMS) method for STLF. A forecasting model pool is first built, including ten state-of-the-art machine learning based forecasting models. Then a Q-learning agent learns the optimal policy of selecting the best forecasting model for the next time step, based on the model performance. The optimal DMS policy is applied to select the best model at each time step with a moving window. Numerical simulations on two-year load and weather data show that the Q-learning algorithm converges fast, resulting in effective and efficient DMS. The developed STLF model with Q-learning based DMS improves the forecasting accuracy by approximately 50%, compared to the state-of-the-art machine learning based STLF models.
Diatoms diversify and turn over faster in freshwater than marine environments

Many clades that span the marine-freshwater boundary are disproportionately more diverse in the younger, shorter lived, and scarcer freshwater environments than they are in the marine realm. This disparity is thought to be related to differences in diversification rates between marine and freshwater lineages. However, marine and freshwaters are not ecologically homogeneous, so the study of diversification across the salinity divide should also account for other potentially interacting variables. In diatoms, freshwater and substrate-associated (benthic) lineages are several-fold more diverse than their marine and suspended (planktonic) counterparts. These imbalances provide an excellent system to understand whether these variables interact with diversification. Using multistate hidden-state speciation and extinction models, we found that freshwater lineages diversify faster than marine lineages regardless of whether they inhabit the plankton or the benthos. Freshwater lineages also had higher turnover rates (speciation + extinction), suggesting that habitat transitions impact speciation and extinction rates jointly. The plankton-benthos contrast was also consistent with state-dependent diversification, but with modest differences in diversification and turnover rates. Asymmetric and bidirectional transitions rejected hypotheses about the plankton and freshwaters as absorbing, inescapable habitats. Our results further suggest that the high turnover rate of freshwater diatoms is related to high turnover of freshwater systems themselves.
Automatic Argument Quality Assessment - New Datasets and Methods.

We explore the task of automatic assessment of argument quality. To that end, we actively collected 6.3k arguments, more than a factor of five compared to previously examined data. Each argument was explicitly and carefully annotated for its quality. In addition, 14k pairs of arguments were annotated independently, identifying the higher quality argument in each pair. In spite of the inherent subjective nature of the task, both annotation schemes led to surprisingly consistent results. We release the labeled datasets to the community. Furthermore, we suggest neural methods based on a recently released language model, for argument ranking as well as for argument-pair classification. In the former task, our results are comparable to state-of-the-art; in the latter task our results significantly outperform earlier methods.
Using Embeddings to Correct for Unobserved Confounding in Networks

We consider causal inference in the presence of unobserved confounding. We study the case where a proxy is available for the unobserved confounding in the form of a network connecting the units. For example, the link structure of a social network carries information about its members. We show how to effectively use the proxy to do causal inference. The main idea is to reduce the causal estimation problem to a semi-supervised prediction of both the treatments and outcomes. Networks admit high-quality embedding models that can be used for this semi-supervised prediction. We show that the method yields valid inferences under suitable (weak) conditions on the quality of the predictive model. We validate the method with experiments on a semi-synthetic social network dataset.
A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems

A classic reachability problem for safety of dynamic systems is to compute the set of initial states from which the state trajectory is guaranteed to stay inside a given constraint set over a given time horizon. In this paper, we leverage existing theory of reachability analysis and risk measures to devise a risk-sensitivereachability approach for safety of stochasticdynamic systems under non-adversarial disturbances over a finite time horizon. Specifically, we first introduce the notion of a risk-sensitive safe set asa set of initial states from which the risk of large constraint violations can be reduced to a required level via a control policy, where risk is quantified using the Conditional Value-at-Risk(CVaR) measure. Second, we show how the computation of a risk-sensitive safe set can be reduced to the solution to a Markov Decision Process (MDP), where cost is assessed according to CVaR. Third, leveraging this reduction, we devise a tractable algorithm to approximate a risk-sensitive safe set and provide arguments about its correctness. Finally, we present a realistic example inspired from stormwater catchment design to demonstrate the utility of risk-sensitive reachability analysis. In particular, our approach allows a practitioner to tune the level of risk sensitivity from worst-case (which is typical for Hamilton-Jacobi reachability analysis) to risk-neutral (which is the case for stochastic reachability analysis).
Microbiome composition shapes rapid genomic adaptation of Drosophila melanogaster

Population genomic data has revealed patterns of genetic variation associated with adaptation in many taxa. Yet understanding the adaptive process that drives such patterns is challenging; it requires disentangling the ecological agents of selection, determining the relevant timescales over which evolution occurs, and elucidating the genetic architecture of adaptation. Doing so for the adaptation of hosts to their microbiome is of particular interest with growing recognition of the importance and complexity of host-microbe interactions. Here, we track the pace and genomic architecture of adaptation to an experimental microbiome manipulation in replicate populations of Drosophila melanogaster in field mesocosms. Shifts in microbiome composition altered population dynamics and led to divergence between treatments in allele frequencies, with regions showing strong divergence found on all chromosomes. Moreover, at divergent loci previously associated with adaptation across natural populations, we found that the more common allele in fly populations experimentally enriched for a certain microbial group was also more common in natural populations with high relative abundance of that microbial group. These results suggest that microbiomes may be an agent of selection that shapes the pattern and process of adaptation and, more broadly, that variation in a single ecological factor within a complex environment can drive rapid, polygenic adaptation over short timescales.
Age-Delay Tradeoffs in Single Server Systems

Information freshness and low latency communication is important to many emerging applications. While Age of Information (AoI) serves as a metric of information freshness, packet delay is a traditional metric of communication latency. We prove that there is a natural tradeoff between the AoI and packet delay. We consider a single server system, in which at most one update packet can be serviced at a time. The system designer controls the order in which the packets get serviced and the service time distribution, with a given service rate. We analyze two tradeoff problems that minimize packet delay and the variance in packet delay, respectively, subject to an average age constraint. We prove a strong age-delay and age-delay variance tradeoff, wherein, as the average age approaches its minimum, the delay and its variance approach infinity. We show that the service time distribution that minimizes average age, must necessarily have an unbounded-second moment.
The path towards groundwater management in the borderlands of Mexico and Texas

Binational efforts to understand, assess, and manage shared groundwater resources on the Mexico‐Texas border are limited and politically sensitive. On the Mexico side, long‐standing centralized groundwater governance structures have created institutional barriers at the local level to the expansion of knowledge and cooperation over these transboundary resources. On the Texas side, property rights related to groundwater resources limit the scope of options available for cooperative management of cross‐border aquifers. In order to develop more effective cross‐border relations and enhance knowledge, cooperative management, and sustainability of the region's shared aquifers, stakeholders in the border between Mexico and Texas should pursue local and regional arrangements that focus primarily on water quality and environmental issues. Additionally, in order for the results of local efforts to be permanent and sustainable, they must consider the more formal, long‐term cooperative models that tend to have stronger systemic impacts and funding commitments. In addition, stakeholders and officials must make a better effort to educate the public on the science and facts in order to avoid past experiences where fear and political lobbying scuttled viable and promising cooperative efforts.
The Wriggle polynomial for virtual tangles

We generalize the Wriggle polynomial, first introduced by L. Folwaczny and L. Kauffman, to the case of virtual tangles. This generalization naturally arises when considering the self-crossings of t...
Immediate detection of predicates in pervasive environments

An important problem in pervasive environments is detecting predicates on sensed variables in an asynchronous distributed setting to determine context and to respond. We do not assume the availability of synchronized physical clocks because they may not be available or may be too expensive for predicate detection in such environments with a (relatively) low event occurrence rate. We address the problem of detecting each occurrence of a global predicate, at the earliest possible instant, by proposing a suite of three on-line middleware protocols having varying degrees of accuracy. We analyze the degree of accuracy for the proposed protocols. The extent of false negatives and false positives is determined by the run-time message processing latencies.
Convergence Diagnostics for Markov Chain Monte Carlo

Markov chain Monte Carlo (MCMC) is one of the most useful approaches to scientific computing because of its flexible construction, ease of use, and generality. Indeed, MCMC is indispensable for per...
R Coronae Borealis Pulsations

The Cepheid-like pulsations of some of the R CrB stars should in principle make it possible to determine their masses and hence to place constraints on possible evolution scenarios. We briefly review the evidence for these pulsations and discuss the problem of how these low-mass, hydrogen-deficient carbon stars could have evolved to their present position in the H-R diagram. Linear and nonlinear pulsation calculations are reviewed. It is found that for these large luminosity to mass ratio (L/M) stars a region of pulsation instability extends considerably hotter than for normal high luminosity Cepheids. The envelopes of these models are so nonadiabatic that the identification of modes becomes very difficult since there is frequently no clearly defined nodal structure. For the most extreme L/M cases it is found that the models are unstable in the sense that they appear on the verge of ejecting the outer layers.
Field Experiments and the Practice of Economics

Abhijit Banerjee delivered his Prize Lecture on Sunday 8 December 2019, at the Aula Magna, Stockholm University.
Mean Row Values in (u, v)-Calkin–Wilf Trees

We fix integers \(u,v \ge 1\), and consider an infinite binary tree \(\mathscr {T}^{(u,v)}(z)\) with a root node whose value is a positive rational number z. For every vertex a/b, we label the left child as \(a/(ua+b)\) and right child as \((a+vb)/b\). The resulting tree is known as the (u, v)-Calkin–Wilf tree. As z runs over \([1/u,v]\cap \mathbb {Q}\), the vertex sets of \(\mathscr {T}^{(u,v)}(z)\) form a partition of \(\mathbb {Q}^+\). When \(u=v=1\), the mean row value converges to 3/2 as the row depth increases. Our goal is to extend this result for any \(u,v\ge 1\). We show that, when \(z\in [1/u,v]\cap \mathbb {Q}\), the mean row value in \(\mathscr {T}^{(u,v)}(z)\) converges to a value close to \(v+\log 2/u\) uniformly on z.
Sharp estimates for oscillatory integral operators via polynomial partitioning

The sharp range of $L^p$-estimates for the class of Hormander-type oscillatory integral operators is established in all dimensions under a positive-definite assumption on the phase. This is achieved by generalising a recent approach of the first author for studying the Fourier extension operator, which utilises polynomial partitioning arguments. The main result implies improved bounds for the Bochner–Riesz conjecture in dimensions $n \geqslant 4$.
Forschung und Innovation für die Zukunft

Die Erforschung neuer piezoelektrischer Kristalle, Materialien, Beschichtungen, piezoresistiver Halbleiterstrukturen und optischer Messprinzipien bildet bei Kistler die Basis fur die Sensoren der Zukunft. Trends in der Sensorik gehen in Richtung mehr Funktionalitat sowie groserer Systemfahigkeit und Miniaturisierung. Der Aufbau eines weltweiten Netzwerks von Technologiekompetenzen erweist sich als eines der Erfolgsrezepte, um den kunftigen Systemanforderungen gerecht zu werden.
Incentivized Exploration for Multi-Armed Bandits under Reward Drift

We study incentivized exploration for the multi-armed bandit (MAB) problem where the players receive compensation for exploring arms other than the greedy choice and may provide biased feedback on reward. We seek to understand the impact of this drifted reward feedback by analyzing the performance of three instantiations of the incentivized MAB algorithm: UCB, e-Greedy, and Thompson Sampling. Our results show that they all achieve O(log T) regret and compensation under the drifted reward, and are therefore effective in incentivizing exploration. Numerical examples are provided to complement the theoretical analysis.
The Spectral Gap of the 2-D Stochastic Ising Model with Nearly Single-Spin Boundary Conditions

We establish upper bounds for the spectral gap of the stochastic Ising model at low temperature in an N×N box, with boundary conditions which are “plus” except for small regions at the corners which are either free or “minus.” The spectral gap decreases exponentially in the size of the corner regions, when these regions are of size at least of order logN. This means that removing as few as O(logN) plus spins from the corners produces a spectral gap far smaller than the order N−2 gap believed to hold under the all-plus boundary condition. Our results are valid at all subcritical temperatures.
Benchmarking results for the Newton–Anderson method

Abstract This paper primarily presents numerical results for the Anderson accelerated Newton method on a set of benchmark problems. The results demonstrate superlinear convergence to solutions of both degenerate and nondegenerate problems. The convergence for nondegenerate problems is also justified theoretically. For degenerate problems, those whose Jacobians are singular at a solution, the domain of convergence is studied. It is observed in that setting that Newton–Anderson has a domain of convergence similar to Newton, but it may be attracted to a different solution than Newton if the problems are slightly perturbed.
Cyb5r3 links FoxO1-dependent mitochondrial dysfunction with β-cell failure

Abstract Objective Diabetes is characterized by pancreatic β-cell dedifferentiation. Dedifferentiating β cells inappropriately metabolize lipids over carbohydrates and exhibit impaired mitochondrial oxidative phosphorylation. However, the mechanism linking the β-cell's response to an adverse metabolic environment with impaired mitochondrial function remains unclear. Methods Here we report that the oxidoreductase cytochrome b5 reductase 3 (Cyb5r3) links FoxO1 signaling to β-cell stimulus/secretion coupling by regulating mitochondrial function, reactive oxygen species generation, and nicotinamide actin dysfunction (NAD)/reduced nicotinamide actin dysfunction (NADH) ratios. Results The expression of Cyb5r3 is decreased in FoxO1-deficient β cells. Mice with β-cell-specific deletion of Cyb5r3 have impaired insulin secretion, resulting in glucose intolerance and diet-induced hyperglycemia. Cyb5r3-deficient β cells have a blunted respiratory response to glucose and display extensive mitochondrial and secretory granule abnormalities, consistent with altered differentiation. Moreover, FoxO1 is unable to maintain expression of key differentiation markers in Cyb5r3-deficient β cells, suggesting that Cyb5r3 is required for FoxO1-dependent lineage stability. Conclusions The findings highlight a pathway linking FoxO1 to mitochondrial dysfunction that can mediate β-cell failure.
Lighter U-net for segmenting white matter hyperintensities in MR images

White matter hyperintensities (WMH) is one of main consequences of small vessel diseases. Automated WMH segmentation techniques play an important role in clinical research and practice. U-Net has been demonstrated to yield the best precise segmentation results so far. However, sometimes it losses more detailed information as network goes deeper. In addition, it usually depends on data augmentation or a large number of filters. Large filters increase the complexity of model, which may be an obstacle for real-time segmentation on cloud computing. To solve these two issues, a new architecture, Lighter U-Net is proposed to reinforce feature use, to reduce the number of parameters as well as to retain sufficient receptive fields without losing resolution. The extensive experiments suggest that the proposed network achieves comparable performance as the state-of-the-art methods by only using 17% parameters of standard U-Net.
TCD-NPE: A Re-configurable and Efficient Neural Processing Engine, Powered by Novel Temporal-Carry-deferring MACs

In this paper, we first propose the design of Temporal-Carry-deferring MAC (TCD-MAC) and illustrate how our proposed solution can gain significant energy and performance benefit when utilized to process a stream of input data. We then propose using the TCD-MAC to build a reconfigurable, high speed, and low power Neural Processing Engine (TCD-NPE). We, further, propose a novel scheduler that lists the sequence of needed processing events to process an MLP model in the least number of computational rounds in our proposed TCD-NPE. We illustrate that our proposed TCD-NPE significantly outperform similar neural processing solutions that use conventional MACs in terms of both energy consumption and execution time.
Capacity-Achieving Private Information Retrieval Codes From MDS-Coded Databases With Minimum Message Size

We consider constructing capacity-achieving linear codes with minimum message size for private information retrieval (PIR) from N non-colluding databases, where each message is coded using maximum distance separable (MDS) codes, such that it can be recovered from accessing the contents of any T databases. It is shown that the minimum message size (sometimes also referred to as the sub-packetization factor) is significantly, in fact exponentially, lower than previously believed. More precisely, when ${K}> {T}/\text{gcd}({N},{T})$ where K is the total number of messages in the system and $\gcd (\cdot,\cdot)$ means the greatest common divisor, we establish, by providing both novel code constructions and a matching converse, the minimum message size as ${{\textrm {lcm}}}({N}-{T},{T})$ , where ${{\textrm {lcm}}}(\cdot,\cdot)$ means the least common multiple. On the other hand, when $K$ is small, we show that it is in fact possible to design codes with a message size even smaller than ${{\textrm {lcm}}}({N}-{T},{T})$ .
The Innovation Consequences of Mandatory Patent Disclosures

Abstract We investigate the effect of patent disclosures on corporate innovation. Using the American Inventor's Protection Act (AIPA) as a shock that increased patent disclosures, we find an increase in innovation for firms whose rivals reveal more information after the AIPA and a decrease in innovation for firms whose own disclosures are divulged to competitors as a result of the law. These findings suggest patent disclosures generate both spillover benefits and proprietary costs. Our findings provide justification for patent disclosure requirements by demonstrating positive externalities: rivals' disclosures facilitate a firm's innovation. However, we also highlight that mandatory patent disclosures can impose proprietary costs on firms. These results broadly contribute to our understanding of the real effects of disclosure, such that forcing firms to share proprietary information can be privately costly but beneficial to other firms.
Efficient reassembling of three-regular planar graphs

A reassembling of a simple graph $$G = (V,E)$$ is an abstraction of a problem arising in earlier studies of network analysis (Bestavros and Kfoury, in: Proceedings of IFIP working conference on domain-specific 1640 languages (DSL 2011), EPTCS volume 66, 2011; Kfoury, in: Proceedings of SBLP 2011: Brazilian symposium on programming; Kfoury, in Sci Comput Program 93(Part A):19–38; Soule et al., in: Proceedings of 4th international workshop on equation-based object oriented modeling languages and tools, Zurich). There are several equivalent definitions of graph reassembling; in this report we use a definition which makes it closest to the notion of graph carving. A reassembling is a rooted binary tree whose nodes are subsets of V and whose leaf nodes are singleton sets, with each of the latter containing a distinct vertex of G. The parent of two nodes in the reassembling is the union of the two children’s vertex sets. The root node of the reassembling is the full set V. The edge-boundary degree of a node in the reassembling is the number of edges in G that connect vertices in the node’s set to vertices not in the node’s set. A reassembling’s $$\alpha $$-measure is the largest edge-boundary degree of any node in the reassembling. A reassembling of G is $$\alpha $$-optimal if its $$\alpha $$-measure is the minimum among all $$\alpha $$-measures of G’s reassemblings. The problem of finding an $$\alpha $$-optimal reassembling of a simple graph in general was already shown to be NP-hard (Kfoury and Mirzaei, in J Comb Optim 33(3):1057–1089; Mirzaei and Kfoury, in: Efficient reassembling of graphs, Part 2: the balanced case. CoRR, arXiv:1602.02863; among others). In this report we present an algorithm which, given a 3-regular plane graph $$G = (V,E)$$ as input, returns a reassembling of G with an $$\alpha $$-measure independent of $$n = |\,V\,|$$ and upper-bounded by 2k, where k is the edge-outerplanarity of G. (Edge-outerplanarity is distinct but closely related to the usual notion of outerplanarity; as with outerplanarity, for a fixed edge-outerplanarity k, the number n of vertices can be arbitrarily large). Our algorithm runs in linear time $${{\mathcal {O}}}(n)$$. Moreover, we construct a class of 3-regular plane graphs for which this $$\alpha $$-measure is optimal, by proving that 2k is the lower bound on the $$\alpha $$-measure of any reassembling of a graph in that class.
Ecological and individual data both indicate that influenza inhibits rhinovirus infection.

We read the article “Virus–virus interactions impact the population dynamics of influenza and the common cold” by Nickbakhsh et al. (1) with great interest. The authors analyzed a large Scottish dataset consisting of virology results from patients with acute respiratory illnesses and used mathematical models to identify a negative interaction between influenza and rhinovirus (RV) infection. Furthermore, they performed epidemiologic simulations demonstrating that influenza-mediated induction of a refractory period could account for the significant reduction in RV illness prevalence. In fact, we demonstrated that influenza can induce a refractory period using individual-level data obtained from a cohort of children that … [↵][1]1To whom correspondence may be addressed. Email: kloepfer{at}iu.edu. [1]: #xref-corresp-1-1
Carbon Assimilation Strategies in Ultrabasic Groundwater: Clues from the Integrated Study of a Serpentinization-Influenced Aquifer

ABSTRACT Serpentinization is a low-temperature metamorphic process by which ultramafic rock chemically reacts with water. Such reactions provide energy and materials that may be harnessed by chemosynthetic microbial communities at hydrothermal springs and in the subsurface. However, the biogeochemistry mediated by microbial populations that inhabit these environments is understudied and complicated by overlapping biotic and abiotic processes. We applied metagenomics, metatranscriptomics, and untargeted metabolomics techniques to environmental samples taken from the Coast Range Ophiolite Microbial Observatory (CROMO), a subsurface observatory consisting of 12 wells drilled into the ultramafic and serpentinite melange of the Coast Range Ophiolite in California. Using a combination of DNA and RNA sequence data and mass spectrometry data, we found evidence for several carbon fixation and assimilation strategies, including the Calvin-Benson-Bassham cycle, the reverse tricarboxylic acid cycle, the reductive acetyl coenzyme A (acetyl-CoA) pathway, and methylotrophy, in the microbial communities inhabiting the serpentinite-hosted aquifer. Our data also suggest that the microbial inhabitants of CROMO use products of the serpentinization process, including methane and formate, as carbon sources in a hyperalkaline environment where dissolved inorganic carbon is unavailable. IMPORTANCE This study describes the potential metabolic pathways by which microbial communities in a serpentinite-influenced aquifer may produce biomass from the products of serpentinization. Serpentinization is a widespread geochemical process, taking place over large regions of the seafloor and at continental margins, where ancient seafloor has accreted onto the continents. Because of the difficulty in delineating abiotic and biotic processes in these environments, major questions remain related to microbial contributions to the carbon cycle and physiological adaptation to serpentinite habitats. This research explores multiple mechanisms of carbon fixation and assimilation in serpentinite-hosted microbial communities.
Ultrathin Plasmonic Tungsten Oxide Quantum Wells with Controllable Free Carrier Densities.

Localized surface plasmon resonances (LSPR) of nanostructures can be tuned by controlling their morphology, local dielectric environment, and free carrier concentration. We report the colloidal synthesis of an ∼3 tungsten-oxygen (W-O) layer thick (∼1 nm), two-dimensional (2D) WO3-x nanoplatelets (NPLs) (x ≈ 0.55-1.03), which display tunable near-infrared LSPR properties and additionally high free electron density (Ne) that arises predominantly from the large shape factor of 2D NPLs. Importantly, the W to O composition ratios inferred from their LSPR measurements show much higher percentage of oxygen vacancies than those determined by X-ray diffraction analysis, suggesting that the aspect ratio of ultrathin WO3-x NPLs is the key to producing an unprecedentedly large Ne, although synthesis temperature is also an independent factor. We find that NPL formation is kinetically controlled, whereas thermodynamic parameter manipulation leads to Ne values as high as 4.13 × 1022 cm-3, which is close to that of plasmonic noble metals, and thus our oxide-based nanostructures can be considered as quasi-metallic. The unique structural properties of 2D nanomaterials along with the high Ne of WO3-x NPLs provide an attractive alternative to plasmonic noble metal nanostructures for various plasmon-driven energy conversions and design of photochromic nanodevices.
Real zeros of random sums with i.i.d. coefficients

Let $\{f_k\}$ be a sequence of entire functions that are real valued on the real-line. We study the expected number of real zeros of random sums of the form $P_n(z)=\sum_{k=0}^n\eta_k f_k(z)$, where $\{\eta_k\}$ are real valued i.i.d.~random variables. We establish a formula for the density function $\rho_n$ for the expected number of real zeros of $P_n$. As a corollary, taking the random variables $\{\eta_k\}$ to be i.i.d.~standard Gaussian, appealing to Fourier inversion we recover the representation for the density function previously given by Vanderbei through means of a different proof. Placing the restrictions on the common characteristic function $\phi$ of $\{\eta_k\}$ that $|\phi(s)|\leq (1+as^2)^{-q}$, with $a>0$ and $q\geq 1$, as well as that $\phi$ is three times differentiable with each the second and third derivatives being uniformly bounded, we achieve an upper bound on the density function $\rho_n$ with explicit constants that depend only on the restrictions on $\phi$. As an application we considered the limiting value of $\rho_n$ when the spanning functions $f_k(z)=p_k(z)$, $k=0,1,\dots, n$, where $\{p_k\}$ are Bergman polynomials on the unit disk.
On Applications of Bootstrap in Continuous Space Reinforcement Learning

In decision making problems for continuous state and action spaces, linear dynamical models are widely employed. Specifically, policies for stochastic linear systems subject to quadratic cost functions capture a large number of applications in reinforcement learning. Selected randomized policies have been studied in the literature recently that address the trade-off between identification and control. However, little is known about policies based on bootstrapping observed states and control inputs. In this work, we show that bootstrap-based policies achieve a square root scaling of regret with respect to time. We also obtain results on the accuracy of learning the model’s dynamics. Corroborative numerical analysis that illustrates the technical results is also provided.
Tunable Transcriptional Interference at the Endogenous Alcohol Dehydrogenase Gene Locus in Drosophila melanogaster.

Neighboring sequences of a gene can influence its expression. In the phenomenon known as transcriptional interference, transcription at one region in the genome can repress transcription at a nearby region in cis. Transcriptional interference occurs at a number of eukaryotic loci, including the alcohol dehydrogenase (Adh) gene in Drosophila melanogaster. Adh is regulated by two promoters, which are distinct in their developmental timing of activation. It has been shown using transgene insertion that when the promoter distal from the Adh start codon is deleted, transcription from the proximal promoter becomes de-regulated. As a result, the Adh proximal promoter, which is normally active only during the early larval stages, becomes abnormally activated in adults. Whether this type of regulation occurs in the endogenous Adh context, however, remains unclear. Here, we employed the CRISPR/Cas9 system to edit the endogenous Adh locus and found that removal of the distal promoter also resulted in the untimely expression of the proximal promoter-driven mRNA isoform in adults, albeit at lower levels than previously reported. Importantly, transcription from the distal promoter was sufficient to repress proximal transcription in larvae and that the degree of this repression was dependent on the degree of distal promoter activity. Finally, upregulation of the distal Adh transcript led to the enrichment of histone 3 lysine 36 trimethylation over the Adh proximal promoter. We conclude that the endogenous Adh locus is developmentally regulated by transcriptional interference in a tunable manner.
Whole-Genome Comparisons of Staphylococcus agnetis Isolates from Cattle and Chickens

ABSTRACT Staphylococcus agnetis has been previously associated with subclinical or clinically mild cases of mastitis in dairy cattle and is one of several staphylococcal species that have been isolated from the bones and blood of lame broilers. We reported that S. agnetis could be obtained frequently from bacterial chondronecrosis with osteomyelitis (BCO) lesions of lame broilers (A. Al-Rubaye et al., PLoS One 10:e0143336, 2015 [https://doi.org/10.1371/journal.pone.0143336]). A particular isolate, S. agnetis 908, can induce lameness in over 50% of exposed chickens, exceeding normal BCO incidences in broiler operations. We reported the assembly and annotation of the genome of isolate 908. To better understand the relationship between dairy cattle and broiler isolates, we assembled 11 additional genomes for S. agnetis isolates, an additional chicken BCO strain, and ten isolates from cattle milk, mammary gland secretions, or udder skin from the collection at the University of Missouri. To trace phylogenetic relationships, we constructed phylogenetic trees based on multilocus sequence typing and genome-to-genome distance comparisons. Chicken isolate 908 clustered with two of the cattle isolates, along with three isolates from chickens in Denmark and an isolate of S. agnetis we isolated from a BCO lesion on a commercial broiler farm in Arkansas. We used a number of BLAST tools to compare the chicken isolates to those from cattle and identified 98 coding sequences distinguishing isolate 908 from the cattle isolates. None of the identified genes explain the differences in host or tissue tropism. These analyses are critical to understanding how staphylococci colonize and infect different hosts and potentially how they can transition to alternative niches (bone versus dermis). IMPORTANCEStaphylococcus agnetis has been recently recognized as associated with disease in dairy cattle and meat-type chickens. The infections appear to be limited in cattle and systemic in broilers. This report details the molecular relationships between cattle and chicken isolates in order to understand how this recently recognized species infects different hosts with different disease manifestations. The data show that the chicken and cattle isolates are very closely related, but the chicken isolates all cluster together, suggesting a single jump from cattle to chickens.
Young star clusters in starburst environments

Recent high-resolution observations with the Hubble Space Telescope (HST) reveal that young star clusters of extraordinary luminosity and compactness ("super star clusters") are commonly found in starburst systems. Cluster formation appears to be a dominant mode of star formation in starbursts. The principal properties of the young clusters are summarized. A new ultraviolet HST imaging survey of the central regions of nearby galaxies indicates that young clusters form in a wide range of environments. Circumnuclear star-forming rings, in particular, are richly populated with clusters, and several examples from recent imaging studies are discussed. There has been much speculation that super star clusters represent present-day analogs of young globular clusters. I will present evidence suggesting that at least some super star clusters indeed have masses and mass densities comparable to those of evolved globular clusters in the Milky Way.
A first course in string theory

String theory made understandable. Barton Zwiebach is once again faithful to his goal of making string theory accessible to undergraduates. He presents the main concepts of string theory in a concrete and physical way to develop intuition before formalism, often through simplified and illustrative examples. Complete and thorough in its coverage, this new edition now includes AdS/CFT correspondence and introduces superstrings. It is perfectly suited to introductory courses in string theory for students with a background in mathematics and physics. New sections cover strings on orbifolds, cosmic strings, moduli stabilization, and the string theory landscape. Now with almost 300 problems and exercises, with password-protected solutions for instructors at www.cambridge.org/zwiebach.
SparkINFERNO: a scalable high-throughput pipeline for inferring molecular mechanisms of non-coding genetic variants.

Summary We report Spark-based INFERence of the molecular mechanisms of NOn-coding genetic variants (SparkINFERNO), a scalable bioinformatics pipeline characterizing non-coding genome-wide association study (GWAS) association findings. SparkINFERNO prioritizes causal variants underlying GWAS association signals and reports relevant regulatory elements, tissue contexts and plausible target genes they affect. To achieve this, the SparkINFERNO algorithm integrates GWAS summary statistics with large-scale collection of functional genomics datasets spanning enhancer activity, transcription factor binding, expression quantitative trait loci and other functional datasets across more than 400 tissues and cell types. Scalability is achieved by an underlying API implemented using Apache Spark and Giggle-based genomic indexing. We evaluated SparkINFERNO on large GWASs and show that SparkINFERNO is more than 60 times efficient and scales with data size and amount of computational resources. Availability and implementation SparkINFERNO runs on clusters or a single server with Apache Spark environment, and is available at https://bitbucket.org/wanglab-upenn/SparkINFERNO or https://hub.docker.com/r/wanglab/spark-inferno. Contact lswang@pennmedicine.upenn.edu. Supplementary information Supplementary data are available at Bioinformatics online.
When do shelter-in-place orders fight COVID-19 best? Policy heterogeneity across states and adoption time

Shelter in place orders (SIPOs) require residents to remain home for all but essential activities. Between March 19 and April 20, 2020, 40 states and the District of Columbia adopted SIPOs. This study explores the impact of SIPOs on health, with particular attention to heterogeneity in their impacts. First, using daily state-level social distancing data from SafeGraph and a difference-in-differences approach, we document that adoption of a SIPO was associated with a 9 to 10 percent increase in the rate at which state residents remained in their homes full-time. Then, using daily state-level coronavirus case data collected by the Centers for Disease Control and Prevention, we find that approximately three weeks following the adoption of a SIPO, cumulative COVID-19 cases fell by approximately 53.5 percent. Event-study analyses confirm common COVID-19 case trends in the week prior to SIPO adoption and show that SIPO-induced case reductions grew larger over time. However, this average effect masks important heterogeneity across states - early adopters and high population density states appear to reap larger benefits from their SIPOs. Finally, we find that statewide SIPOs were associated with a reduction in coronavirus-related deaths, but estimated mortality effects were imprecisely estimated.
THE NEURAL TUBE PATTERNS VESSELS DEVELOPMENTALLY USING THE VEGF SIGNALING PATHWAY

Embryonic blood vessels form in a reproducible pattern that interfaces with other embryonic structures and tissues, but the sources and identities of signals that pattern vessels are not well characterized. We hypothesized that the neural tube provides vascular patterning signal(s) that direct formation of the perineural vascular plexus (PNVP) that encompasses the neural tube at mid-gestation. Both surgically placed ectopic neural tubes and ectopic neural tubes engineered genetically were able to recruit a vascular plexus, showing that the neural tube is the source of a vascular patterning signal. In mouse-quail chimeras with the graft separated from the neural tube by a buffer of host cells, graft-derived vascular cells contributed to the PNVP, indicating that the neural tube signal(s) can act at a distance. Murine neural tube vascular endothelial growth factor A (VEGFA) expression was temporally and spatially correlated with PNVP formation, suggesting it is a component of the neural tube signal. A collagen explant model was developed in which presomitic mesoderm explants formed a vascular plexus in the presence of added VEGFA. Co-cultures between presomitic mesoderm and neural tube also supported vascular plexus formation, indicating that the neural tube could replace the requirement for VEGFA. Moreover, a combination of pharmacological and genetic perturbations showed that VEGFA signaling through FLK1 is a required component of the neural tube vascular patterning signal. Thus, the neural tube is the first structure identified as a midline signaling center for embryonic vascular pattern formation in higher vertebrates, and VEGFA is a necessary component of the neural tube vascular patterning signal. These data suggest a model whereby embryonic structures with little or no capacity for angioblast generation act as a nexus for vessel patterning.
Growth volatility and financial liberalization

We examine the effects of both equity market liberalization and capital account openness on real consumption growth variability. We show that financial liberalization is mostly associated with lower consumption growth volatility. Our results are robust, surviving controls for business-cycle effects, economic and financial development, the quality of institutions, and other variables. Countries that have more open capital accounts experience a greater reduction in consumption growth volatility after equity market openings. We also find that financial liberalizations are associated with declines in the ratio of consumption growth volatility to GDP growth volatility, suggesting improved risk sharing. Our results are weaker for liberalizing emerging markets but we never observe a significant increase in real volatility. Moreover, we demonstrate significant differences in the volatility response depending on the size of the banking and government sectors and certain institutional factors.
Hypertension among Haitians Living in the Bahamas

For many Haitians in the Bahamas, migration and the process of adapting to life in an often hostile environment creates stress and may be correlated with high blood pressure. This study examines the social determinants of hypertension among Haitians in the Bahamas by exploring how experiences of migration create stress that is believed to cause high blood pressure. The Haitian explanatory model of high blood pressure, tansyon, explains the relationships between variables such as diet, stress, and poverty, and the blood. Research was conducted in several Haitian communities in New Providence and Abaco using ethnographic methods such as interviews and participant observation. Information about hypertension was also obtained during community blood pressure education workshops conducted in collaboration with Haitian community associations. This study offers valuable insights for public health efforts in the Bahamas on the issue of hypertension in the Haitian community. This study is relevant to researchers studying the connections between hypertension and migration for populations originating from less developed countries.