cssi/SciSciGPT-SciSciNet huggingface dataset:
Machine learning for quantum dynamics: deep learning of excitation energy transfer properties

Understanding the relationship between the structure of light-harvesting systems and their excitation energy transfer properties is of fundamental importance in many applications including the development of next generation photovoltaics. Natural light harvesting in photosynthesis shows remarkable excitation energy transfer properties, which suggests that pigment–protein complexes could serve as blueprints for the design of nature inspired devices. Mechanistic insights into energy transport dynamics can be gained by leveraging numerically involved propagation schemes such as the hierarchical equations of motion (HEOM). Solving these equations, however, is computationally costly due to the adverse scaling with the number of pigments. Therefore virtual high-throughput screening, which has become a powerful tool in material discovery, is less readily applicable for the search of novel excitonic devices. We propose the use of artificial neural networks to bypass the computational limitations of established techniques for exploring the structure-dynamics relation in excitonic systems. Once trained, our neural networks reduce computational costs by several orders of magnitudes. Our predicted transfer times and transfer efficiencies exhibit similar or even higher accuracies than frequently used approximate methods such as secular Redfield theory.
Thread-modular static analysis for relaxed memory models

We propose a memory-model-aware static program analysis method for accurately analyzing the behavior of concurrent software running on processors with weak consistency models such as x86-TSO, SPARC-PSO, and SPARC-RMO. At the center of our method is a unified framework for deciding the feasibility of inter-thread interferences to avoid propagating spurious data flows during static analysis and thus boost the performance of the static analyzer. We formulate the checking of interference feasibility as a set of Datalog rules which are both efficiently solvable and general enough to capture a range of hardware-level memory models. Compared to existing techniques, our method can significantly reduce the number of bogus alarms as well as unsound proofs. We implemented the method and evaluated it on a large set of multithreaded C programs. Our experiments show the method significantly outperforms state-of-the-art techniques in terms of accuracy with only moderate runtime overhead.
The RNA-Binding Site of Poliovirus 3C Protein Doubles as a Phosphoinositide-Binding Domain

Some viruses use phosphatidylinositol phosphate (PIP) to mark membranes used for genome replication or virion assembly. PIP-binding motifs of cellular proteins do not exist in viral proteins. Molecular-docking simulations revealed a putative site of PIP binding to poliovirus (PV) 3C protein that was validated using nuclear magnetic resonance spectroscopy. The PIP-binding site was located on a highly dynamic α helix, which also functions in RNA binding. Broad PIP-binding activity was observed in solution using a fluorescence polarization assay or in the context of a lipid bilayer using an on-chip, fluorescence assay. All-atom molecular dynamics simulations of the 3C protein-membrane interface revealed PIP clustering and perhaps PIP-dependent conformations. PIP clustering was mediated by interaction with residues that interact with the RNA phosphodiester backbone. We conclude that 3C binding to membranes will be determined by PIP abundance. We suggest that the duality of function observed for 3C may extend to RNA-binding proteins of other viruses.
Genetic Engineering as a Key to Water-Use Efficiency

ABSTRACT Eslick, R. F. and Hockett, E. A., 1974. Genetic engineering as a key to water-use efficiency. Agric. Meteoroi., 14: 13–23. Most of the present breeding systems are locked into certain germ plasm sources and the chance development of cultivars with greater water-use efficiency is very small. Extensive germ plasm pools containing genes for greater water-use efficiency exist, but heavy selection pressure is necessary to identify these genes. Plant breeders need to determine the plant characteristics contributing to water-use efficiency. Tests for these characteristics need to be simple and rapid. The four general methods of developing isogenic pairs (lines homozygous for AA and aa) are: through point mutations; by backcrossing A or a into an adapted cultivar; by crossing AA and aa and selfing Aa; and by crossing AA and aa and bulking homozygous F2 and F3 lines. The first two methods result in isogenic pairs in a “specific” genetic background and the second two in isogenic pairs in an “average„ genetic background. Genes on chromosome segments adjacent to the isogenic pair being tested may greatly influence the results obtained. Care should be used in interpreting data since the worth of a gene may be completely obscured by pleiotropic effects or compensating effects of the background containing the isogenic pairs. The purpose of this paper is to discuss two areas of plant breeding that are related to the general topic of this symposium. One area is concerned with the present status of and approaches to plant breeding and the probabilities of plant breeders detecting genes contributing to water-use efficiency. The second area is concerned with the use of isogenic analysis to detect genes associated with water-use efficiency. This presentation will draw on general information concerning plant breeding and more specifically on our experiences with barley. This is not intended to be a comprehensive review of the literature. Primarily, this discussion is directed to those that are not plant breeders.
Upward Partitioned Book Embeddings

We analyze a directed variation of the book embedding problem when the page partition is prespecified and the nodes on the spine must be in topological order (upward book embedding). Given a directed acyclic graph and a partition of its edges into k pages, can we linearly order the vertices such that the drawing is upward (a topological sort) and each page avoids crossings? We prove that the problem is NP-complete for \(k\ge 3\), and for \(k\ge 4\) even in the special case when each page is a matching. By contrast, the problem can be solved in linear time for \(k=2\) pages when pages are restricted to matchings. The problem comes from Jack Edmonds (1997), motivated as a generalization of the map folding problem from computational origami.
Machine Learning Spatial Geometry from Entanglement Features

Motivated by the close relations of the renormalization group with both the holography duality and the deep learning, we propose that the holographic geometry can emerge from deep learning the entanglement feature of a quantum many-body state. We develop a concrete algorithm, call the entanglement feature learning (EFL), based on the random tensor network (RTN) model for the tensor network holography. We show that each RTN can be mapped to a Boltzmann machine, trained by the entanglement entropies over all subregions of a given quantum many-body state. The goal is to construct the optimal RTN that best reproduce the entanglement feature. The RTN geometry can then be interpreted as the emergent holographic geometry. We demonstrate the EFL algorithm on a 1D free fermion system and observe the emergence of the hyperbolic geometry (AdS3 spatial geometry) as we tune the fermion system towards the gapless critical point (CFT2 point).
Governance and the effectiveness of public health subsidies: Evidence from Ghana, Kenya and Uganda.

Abstract Distributing subsidized health products through existing health infrastructure could substantially and cost-effectively improve health in sub-Saharan Africa. There is, however, widespread concern that poor governance – in particular, limited health worker accountability – seriously undermines the effectiveness of subsidy programs. We audit targeted bed net distribution programs to quantify the extent of agency problems. We find that around 80% of the eligible receive the subsidy as intended, and up to 15% of subsidies are leaked to ineligible people. Supplementing the program with simple financial or monitoring incentives for health workers does not improve performance further and is thus not cost-effective in this context.
Did the Exchange Rate Floor Prevent Deflation in the Czech Republic

To fight deflationary pressures at the zero lower bound, in November 2013, the Czech National Bank (CNB) introduced a one-sided floor on the exchange rate, as an additional monetary policy instrument. This paper investigates the impact of the FX floor on inflation in the Czech Republic, by comparing actual inflation with counterfactuals in the absence of the exchange rate floor. Three different empirical strategies are implemented: an event study, difference-in-difference regressions and a synthetic control method. The empirical results provide evidence that the exchange rate was effective in fighting deflationary pressures and prevented inflation from going into negative territory. The magnitude of the effect ranges between 0.5 to 1.5 percentage points. The results are robust to different econometric specifications.
Competitive learning modulates memory consolidation during sleep

Abstract Competition between memories can cause weakening of those memories. Here we investigated memory competition during sleep in human participants by presenting auditory cues that had been linked to two distinct picture-location pairs during wake. We manipulated competition during learning by requiring participants to rehearse picture-location pairs associated with the same sound either competitively (choosing to rehearse one over the other, leading to greater competition) or separately; we hypothesized that greater competition during learning would lead to greater competition when memories were cued during sleep. With separate-pair learning, we found that cueing benefited spatial retention. With competitive-pair learning, no benefit of cueing was observed on retention, but cueing impaired retention of well-learned pairs (where we expected strong competition). During sleep, post-cue beta power (16–30 Hz) indexed competition and predicted forgetting, whereas sigma power (11–16 Hz) predicted subsequent retention. Taken together, these findings show that competition between memories during learning can modulate how they are consolidated during sleep.
A map of gene expression in neutrophil-like cell lines

Human neutrophils are central players in innate immunity, a major component of inflammatory responses, and a leading model for cell motility and chemotaxis. However, primary neutrophils are short-lived, limiting their experimental usefulness in the laboratory. Thus, human myeloid cell lines have been characterized for their ability to undergo neutrophil-like differentiation in vitro. The HL-60 cell line and its PLB-985 sub-line are commonly used to model human neutrophil behavior, but how closely gene expression in differentiated cells resembles that of primary neutrophils has remained unclear. In this study, we compared the effectiveness of differentiation protocols and used RNA sequencing (RNA-seq) to compare the transcriptomes of HL-60 and PLB-985 cells with published data for human and mouse primary neutrophils. Among commonly used differentiation protocols for neutrophil-like cell lines, addition of dimethyl sulfoxide (DMSO) gave the best combination of cell viability and expression of markers for differentiation. However, combining DMSO with the serum-free-supplement Nutridoma resulted in increased chemotactic response, phagocytic activity, oxidative burst and cell surface expression of the neutrophil markers FPR1 and CD11b without a cost in viability. RNA-seq analysis of HL-60 and PLB-985 cells before and after differentiation showed that differentiation broadly increases the similarity in gene expression between the cell lines and primary neutrophils. Furthermore, the gene expression pattern of the differentiated cell lines correlated slightly better with that of human neutrophils than the mouse neutrophil pattern did. Finally, we created a publicly available gene expression database that is searchable by gene name and protein domain content, where users can compare gene expression in HL-60, PLB-985 and primary human and mouse neutrophils. Our study verifies that a DMSO-based differentiation protocol for HL-60 and PLB-985 cell lines gives superior differentiation and cell viability relative to other common protocols, and indicates that addition of Nutridoma may be preferable for studies of chemotaxis, phagocytosis, or oxidative burst. Our neutrophil gene expression database will be a valuable tool to identify similarities and differences in gene expression between the cell lines and primary neutrophils, to compare expression levels for genes of interest, and to improve the design of tools for genetic perturbations.
Antagonism in olfactory receptor neurons and its implications for the perception of odor mixtures

When ordering in a coffee shop, you probably recognize and enjoy the aroma of freshly roasted coffee beans. But as well as coffee, you can also smell the croissants behind the counter and maybe even the perfume or cologne of the person next to you. Each of these scents consists of a collection of chemicals, or odorants. To distinguish between the aroma of coffee and that of croissants, your brain must group the odorants appropriately and then keep the groups separate from each other. This is not a trivial task. Odorants bind to proteins called odorant receptors found on the surface of cells in the nose called olfactory receptor neurons. But each odorant does not have its own dedicated receptor. Instead, a single odorant will bind to multiple types of odorant receptors, and thus, each olfactory receptor neuron may respond to multiple odorants. So how does the brain encode mixtures of odorants in a way that allows us to distinguish one aroma from another? Reddy, Zak et al. have developed a computational model to explain how this process works. The model assumes that an odorant triggers a response in an olfactory receptor neuron via two steps. First, the odorant binds to an odorant receptor. Second, the bound odorant activates the receptor. But the odorant that binds most strongly to a receptor will not necessarily be the odorant that is best at activating that receptor. This allows a phenomenon called competitive antagonism to occur. This is when one odorant in a mixture binds more strongly to a receptor than the other odorants, but only weakly activates that receptor. In so doing, the strongly bound odorant prevents the other odorants from binding to and activating the receptor. This helps tame the dominating influence of background odors, which might otherwise saturate the responses of individual olfactory receptor neurons. Reddy, Zak et al. show that processes such as competitive antagonism enable olfactory receptor neurons to encode all of the odors within a mixture. The model can explain various phenomena observed in experiments and it adds to our understanding of how the brain generates our sense of smell. The model may also be relevant to other biological systems that must filter weak signals from a dominant background. These include the immune system, which must distinguish a small set of foreign proteins from the much larger number of proteins that make up our bodies.
THE RISK OF FIRE SALES IN THE TRI-PARTY REPO MARKET

This paper studies the risk of “fire sales” in the tri-party repo market, a large and important market where securities dealers find short-term funding for a substantial portion of their own and their clients' assets. We distinguish between fire sales of assets by a dealer who, facing a run that could lead to default, sells securities to generate liquidity, and fire sales of assets by repo investors after a dealer's default has occurred. While fire sales do cause damage no matter how they arise, the tools available to lessen the harm from the two types of fire sales are different. We find that limited tools are available to mitigate the risk of predefault fire sales and that no established tools currently exist to mitigate the risk of postdefault sales. (JEL G01, G18)
Recipient-Biased Competition for an Intracellularly Generated Cross-Fed Nutrient Is Required for Coexistence of Microbial Mutualists.

Many mutualistic microbial relationships are based on nutrient cross-feeding. Traditionally, cross-feeding is viewed as being unidirectional, from the producer to the recipient. This is likely true when a producer's waste, such as a fermentation product, has value only for a recipient. However, in some cases the cross-fed nutrient holds value for both the producer and the recipient. In such cases, there is potential for nutrient reacquisition by producer cells in a population, leading to competition against recipients. Here, we investigated the consequences of interpartner competition for cross-fed nutrients on mutualism dynamics by using an anaerobic coculture pairing fermentative Escherichia coli and phototrophic Rhodopseudomonas palustris In this coculture, E. coli excretes waste organic acids that provide a carbon source for R. palustris In return, R. palustris cross-feeds E. coli ammonium (NH4+), a compound that both species value. To explore the potential for interpartner competition, we first used a kinetic model to simulate cocultures with varied affinities for NH4+ in each species. The model predicted that interpartner competition for NH4+ could profoundly impact population dynamics. We then experimentally tested the predictions by culturing mutants lacking NH4+ transporters in both NH4+ competition assays and mutualistic cocultures. Both theoretical and experimental results indicated that the recipient must have a competitive advantage in acquiring cross-fed NH4+ to sustain the mutualism. This recipient-biased competitive advantage is predicted to be crucial, particularly when the communally valuable nutrient is generated intracellularly. Thus, the very metabolites that form the basis for mutualistic cross-feeding can also be subject to competition between mutualistic partners.IMPORTANCE Mutualistic relationships, particularly those based on nutrient cross-feeding, promote stability of diverse ecosystems and drive global biogeochemical cycles. Cross-fed nutrients within these systems can be either waste products valued by only one partner or nutrients valued by both partners. Here, we explored how interpartner competition for a communally valuable cross-fed nutrient impacts mutualism dynamics. We discovered that mutualism stability necessitates that the recipient have a competitive advantage against the producer in obtaining the cross-fed nutrient, provided that the nutrient is generated intracellularly. We propose that the requirement for recipient-biased competition is a general rule for mutualistic coexistence based on the transfer of intracellularly generated, communally valuable resources.
Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study.

Background: Smoking is the leading cause of preventable death in the world today. Ecological research on smoking in context currently relies on self-reported smoking behavior. Emerging smartwatch technology may more objectively measure smoking behavior by automatically detecting smoking sessions using robust machine learning models. Objective: This study aimed to examine the feasibility of detecting smoking behavior using smartwatches. The second aim of this study was to compare the success of observing smoking behavior with smartwatches to that of conventional self-reporting. Methods: A convenience sample of smokers was recruited for this study. Participants (N=10) recorded 12 hours of accelerometer data using a mobile phone and smartwatch. During these 12 hours, they engaged in various daily activities, including smoking, for which they logged the beginning and end of each smoking session. Raw data were classified as either smoking or nonsmoking using a machine learning model for pattern recognition. The accuracy of the model was evaluated by comparing the output with a detailed description of a modeled smoking session. Results: In total, 120 hours of data were collected from participants and analyzed. The accuracy of self-reported smoking was approximately 78% (96/123). Our model was successful in detecting 100 of 123 (81%) smoking sessions recorded by participants. After eliminating sessions from the participants that did not adhere to study protocols, the true positive detection rate of the smartwatch based-detection increased to more than 90%. During the 120 hours of combined observation time, only 22 false positive smoking sessions were detected resulting in a 2.8% false positive rate. Conclusions: Smartwatch technology can provide an accurate, nonintrusive means of monitoring smoking behavior in natural contexts. The use of machine learning algorithms for passively detecting smoking sessions may enrich ecological momentary assessment protocols and cessation intervention studies that often rely on self-reported behaviors and may not allow for targeted data collection and communications around smoking events. [JMIR Mhealth Uhealth 2017;5(12):e189]
Neonatal hyperoxia promotes asthma-like features through IL-33–dependent ILC2 responses

Background Premature infants often require oxygen supplementation and, therefore, are exposed to oxidative stress. Following oxygen exposure, preterm infants frequently develop chronic lung disease and have a significantly increased risk of asthma. Objective We sought to identify the underlying mechanisms by which neonatal hyperoxia promotes asthma development. Methods Mice were exposed to neonatal hyperoxia followed by a period of room air recovery. A group of mice was also intranasally exposed to house dust mite antigen. Assessments were performed at various time points for evaluation of airway hyperresponsiveness, eosinophilia, mucus production, inflammatory gene expression, and T H and group 2 innate lymphoid cell (ILC2) responses. Sera from term- and preterm-born infants were also collected and levels of IL-33 and type 2 cytokines were measured. Results Neonatal hyperoxia induced asthma-like features including airway hyperresponsiveness, mucus hyperplasia, airway eosinophilia, and type 2 pulmonary inflammation. In addition, neonatal hyperoxia promoted allergic T H responses to house dust mite exposure. Elevated IL-33 levels and ILC2 responses were observed in the lungs most likely due to oxidative stress caused by neonatal hyperoxia. IL-33 receptor signaling and ILC2s were vital for the induction of asthma-like features following neonatal hyperoxia. Serum IL-33 levels correlated significantly with serum levels of IL-5 and IL-13 but not IL-4 in preterm infants. Conclusions These data demonstrate that an axis involving IL-33 and ILC2s is important for the development of asthma-like features following neonatal hyperoxia and suggest therapeutic potential for targeting IL-33, ILC2s, and oxidative stress to prevent and/or treat asthma development related to prematurity.
Soft pair excitations and double-log divergences due to carrier interactions in graphene

Interactions between charge carriers in graphene lead to logarithmic renormalization of observables mimicking the behavior known in (3+1)-dimensional quantum electrodynamics (QED). Here we analyze soft electron-hole $(e\text{\ensuremath{-}}h)$ excitations generated as a result of fast charge dynamics, a direct analog of the signature QED effect---multiple soft photons produced by the QED vacuum shakeup. We show that such excitations are generated in photon absorption, when a photogenerated high-energy $e\text{\ensuremath{-}}h$ pair cascades down in energy and gives rise to multiple soft $e\text{\ensuremath{-}}h$ excitations. This fundamental process is manifested in a double-log divergence in the emission rate of soft pairs and a characteristic power-law divergence in their energy spectrum of the form $\frac{1}{\ensuremath{\omega}}\text{ln}\left(\frac{\ensuremath{\omega}}{\mathrm{\ensuremath{\Delta}}}\right)$. Strong carrier-carrier interactions make pair production a prominent pathway in the photoexcitation cascade.
Growing Pains: The Transformative Journey from a Nascent to a Formal Not-For-Profit Venture

This article examines how a social venture transitions from nascent to formal status and argues that the transformation of the organization set in motion by establishing formal boundaries is a deeply profound one. Drawing from the nonprofit and social entrepreneurship literature on what prompts and energizes individuals to initiate new not-for-profit ventures, and linking it to a notion of revolutionary crisis as organizations emerge and develop, we seek to illuminate and explore the tension, and its consequences, between nonprofit entrepreneurs and the organization they create as the new venture transitions from nascent to formal. We do this by presenting the results from an in-depth case study examining the gestation and boundary-forming phases of Robert’s Place Cooperative, a plucky start-up cooperative in a midsize Midwestern city.
Effects of Susceptor Geometry on Gan Growth on Si(111) with a New MOCVD Reactor

High quality GaN films on AlN buffer layers were grown on Si(111) with a new, commercial, two-injector vertical rotating disk MOCVD reactor (CVD, Inc.). It was found that the geometry of the susceptor greatly affected the structural quality of the epilayers on Si. For the original susceptor geometry, though single crystal GaN films could be obtained, the films were dark gray in appearance with a rough morphology, and the best x-ray rocking curve FWHM was 2.33°. After modifying the susceptor geometry, transparent, mirror-like single crystal GaN films were obtained with the best x-ray rocking curve FWHM being 0.24°. Photoluminescence (PL) and infrared reflectance (IR) spectra of the grown films were compared. The film growth rate was found to increase with decrease of the growth pressure. A 2-D simulation of the flow, heat transfer, and chemical species transport in the reactor showed a more symmetric flow, larger velocity gradient, and lower upward velocity with the modified susceptor, which may be the main reason for the improvement of the structural quality of the films.
Dispersing points on intervals

Abstract We consider a problem of dispersing points on disjoint intervals on a line. Given n pairwise disjoint intervals sorted on a line, we want to find a point in each interval such that the minimum pairwise distance of these points is maximized. Based on a greedy strategy, we present a linear time algorithm for the problem. Further, we also solve in linear time the cycle version of the problem where the intervals are given on a cycle.
Maxillary expansion in an animal model with light, continuous force.

ABSTRACT Objectives: Maxillary constriction is routinely addressed with rapid maxillary expansion (RME). However, the heavy forces delivered by most RME appliances to expand the palate may lead to deleterious effects on the teeth and supporting tissues. The objective of this study was to explore a more physiologic maxillary expansion with light continuous force. Materials and Methods: Twenty 6-week-old Sprague-Dawley rats were equally divided into experimental (EXPT) and control (CTRL) groups. A custom-fabricated archwire expansion appliance made from 0.014-inch copper-nickel-titanium wire was activated 5 mm and bonded to the maxillary molar segments of animals in the EXPT group for 21 days. The force applied to each maxillary segment was 5 cN. Microfocus x-ray computed tomography and histological analyses were used to compare the tooth movement and bone morphology in the midpalatal suture and buccal aspect of the alveolar process between the EXPT and CTRL groups. Descriptive statistics (mean ± standard e...
Re-evaluating the effectiveness of inflation targeting

Abstract This paper estimates the treatment effect of inflation targeting on macroeconomic variables using a semiparametric single index method by taking into account the model misspecification of parametric propensity scores. Our study uses a broader set of preconditions for inflation targeting and macroeconomic outcome variables than the existing literature. The results suggest no significant difference in the inflation level and inflation volatility between targeters and non-targeters after the adoption of inflation targeting. We find that inflation targeting reduces sacrifice ratio and interest rate volatility in the developed economies, and that it enhances fiscal discipline in both the industrial and developing countries.
GaN-Based High-Power-Density Electrolytic-Free Universal Input LED Driver

This paper presents a high-power-density high-power-factor GaN-based two-stage electrolytic-free offline LED driver. The LED driver achieves high power density through the use of a hybrid film–ceramic stacked switched capacitor (SSC) energy buffer, and a comprehensive optimization methodology that evaluates various converter topologies and designs and minimizes overall system volume while maintaining high efficiency. Based on this optimization approach, a totem-pole bridgeless boost power factor correction (PFC) converter is selected for the first stage, while a stacked-input isolated LLC dc–dc converter is selected for the second stage. The optimization procedure also minimizes the passive volume of the SSC energy buffer incorporating the volumetric energy density of commercially available capacitors. The optimized SSC energy buffer utilized in the proposed LED driver has 50% less passive volume than a capacitor-only solution. A 600-W prototype LED driver designed using the proposed approach for universal input voltage ${{(90}}-{ 305 \ \text{V}}_{{\text{rms}}})$ and 24-V output voltage is built and tested. The PFC stage achieves a peak efficiency of 98% while the LLC stage achieves a peak efficiency of 95%. The prototyped LED driver achieves a power density of 28 W/in3.
The enemy votes: Weapons improvisation and bargaining failure

Belligerents could in principle avoid the ex post costs of conflict by revealing all private information about their violent capabilities and then calculating odds of success ex ante. Incentives to misrepresent private information for strategic gain, however, can cause miscalculations that lead to war. I argue some private information can lead to miscalculation not because it is purposefully misrepresented for strategic gain but because it is too decentralized to be easily revealed. The decentralized private information that produces improvised weapons requires a process of discovering suitable local resources and battlefield testing driven by local military entrepreneurs which frustrates information revelation. Decentralized private information used to improvise new weapons and capabilities like those which emerged in Afghanistan and Iraq show that it can take many years, decades, or even an indeterminate amount of time for fighting to reveal relevant information about violent capabilities.
Widespread excess ice in Arcadia Planitia, Mars

The distribution of subsurface water ice on Mars is a key constraint on past climate, while the volumetric concentration of buried ice (pore-filling versus excess) provides information about the process that led to its deposition. We investigate the subsurface of Arcadia Planitia by measuring the depth of terraces in simple impact craters and mapping a widespread subsurface reflection in radar sounding data. Assuming that the contrast in material strengths responsible for the terracing is the same dielectric interface that causes the radar reflection, we can combine these data to estimate the dielectric constant of the overlying material. We compare these results to a three-component dielectric mixing model to constrain composition. Our results indicate a widespread, decameters-thick layer that is excess water ice ~104 km3 in volume. The accumulation and long-term preservation of this ice is a challenge for current Martian climate models.
Equations of State and Anisotropy of Fe-Ni-Si Alloys

We present powder X‐ray diffraction data on body centered cubic (bcc)‐ and hexagonal close packed (hcp)‐structured Fe_(0.91)Ni_(0.09) and Fe_(0.8)Ni_(0.1)Si_(0.1) at 300 K up to 167 and 175 GPa, respectively. The alloys were loaded with tungsten powder as a pressure calibrant and helium as a pressure transmitting medium into diamond anvil cells, and their equations of state and axial ratios were measured with high statistical quality. These equations of state are combined with thermal parameters from previous reports to improve the extrapolation of the density, adiabatic bulk modulus, and bulk sound speed to the pressures and temperatures of Earth's inner core. We propagate uncertainties and place constraints on the composition of Earth's inner core by combining these results with available data on light‐element alloys of iron and seismic observations. For example, the addition of 4.3 to 5.3 wt% silicon to Fe_(0.95)Ni_(0.05) alone can explain geophysical observations of the inner core boundary, as can up to 7.5 wt% sulfur with negligible amounts of silicon and oxygen. Our findings favor an inner core with less than ∼2 wt% oxygen and less than 1 wt% carbon, although uncertainties in electronic and anharmonic contributions to the equations of state may shift these values. The compositional space widens toward the center of the Earth, considering inner core seismic gradients. We demonstrate that hcp‐Fe_(0.91)Ni_(0.09) and hcp‐Fe_(0.8)Ni_(0.1)Si_(0.1) have measurably greater c/aaxial ratios than those of hcp‐Fe over the measured pressure range. We further investigate the relationship between the axial ratios, their pressure derivatives, and elastic anisotropy of hcp‐structured materials.
Increased mandated disclosure frequency and price formation: evidence from the 8-K expansion regulation

Regulators claim that increased mandated disclosure frequency should lead to more efficient price formation. However, analytical models suggest that mandating disclosure may actually impede the price formation process, and prior empirical studies have been unable to document a relation between mandatory disclosure and improved price formation. We re-examine this relationship using a recent SEC regulation that increased the frequency of mandated event disclosures in form 8-K. We show that price formation improves after the mandate, where firms with the largest increases in mandatory disclosure experience the greatest improvements in price formation. Our evidence is consistent with the idea that mandating an increase in the frequency that material events must be disclosed is associated with improved price formation.
Extended depth of field in an intrinsically wavefront-encoded biometric iris camera

This work describes a design process that greatly increases the depth of field of a simple three-element lens system intended for biometric iris recognition. The system is optimized to produce a point spread function that is insensitive to defocus so that recorded images may be deconvolved without the knowledge of the exact object distance. This is essentially a variation on the technique of wavefront encoding; however, the desired encoding effect is achieved by aberrations intrinsic to the lens system itself, without the need for a pupil phase mask.
The Valuation of Ecosystem Services in International Investment Arbitration

AbstractEcosystem services are essential to human life, inextricably woven into the foundations of our civilizations and economies. This article lays the theoretical foundation for the incorporatio...
Lower Lipschitz bounds for phase retrieval from locally supported measurements

Abstract In this short note, we consider the worst case noise robustness of any phase retrieval algorithm which aims to reconstruct all nonvanishing vectors x ∈ C d (up to a single global phase multiple) from the magnitudes of shifted local correlation measurements. Examples of such measurements include both spectrogram measurements of x using locally supported windows and masked Fourier transform intensity measurements of x using bandlimited masks. As a result, the robustness results considered herein apply to a wide range of both ptychographic and Fourier ptychographic imaging scenarios. In particular, the main results imply that the accurate recovery of high-resolution images of extremely large samples using highly localized probes is likely to require an extremely large number of measurements in order to be robust to worst case measurement noise, independent of the recovery algorithm employed. Furthermore, recent pushes to achieve high-speed and high-resolution ptychographic imaging of integrated circuits for process verification and failure analysis will likely need to carefully balance probe design (e.g., their effective time–frequency support) against the total number of measurements acquired in order for their imaging techniques to be stable to measurement noise, no matter what reconstruction algorithms are applied.
An exact and explicit implied volatility inversion formula

In this paper, we develop an exact and explicit (model-independent) Taylor series representation of the implied volatility based on the novel applications of an extended Faa di Bruno formula under the operator calculus setting, and the Lagrange inversion theorem. We rigorously establish that our formula converges to the true implied volatility as the truncation order increases. Numerical examples illustrate the remarkable accuracy and efficiency of the formula. The formula distinguishes from previous literature as it converges to the true exact implied volatility, is a closed-form formula whose coefficients are explicitly determined and do not involve numerical iterations.
Polar Coding for the Multiple Access Wiretap Channel via Rate-Splitting and Cooperative Jamming

We consider strongly secure communication over a discrete memoryless multiple access wiretap channel with two transmitters. No degradation or symmetry assumptions are made on the channel. Our main result is that any rate pair known to be achievable with a random coding like proof, is also achievable with an explicit and low-complexity polar coding scheme. Moreover, if the rate pair is known to be achievable without time-sharing, then time-sharing is not needed in our polar coding scheme as well. Our proof technique relies on rate-splitting, which introduces two virtual transmitters, and cooperative jamming strategies implemented by these virtual transmitters. Specifically, our coding scheme combines point-to-point codes that either aim at secretly conveying a message to the legitimate receiver or at performing cooperative jamming. Each point-to-point code relies on block Markov encoding to be able to deal with an arbitrary channel and strong secrecy. Consequently, our coding scheme is the combination of inter-dependent block Markov constructions. We assess reliability and strong secrecy through a detailed analysis of the dependencies between the random variables involved in the scheme.
Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task

In the third shared task of the Computational Approaches to Linguistic Code-Switching (CALCS) workshop, we focus on Named Entity Recognition (NER) on code-switched social-media data. We divide the shared task into two competitions based on the English-Spanish (ENG-SPA) and Modern Standard Arabic-Egyptian (MSA-EGY) language pairs. We use Twitter data and 9 entity types to establish a new dataset for code-switched NER benchmarks. In addition to the CS phenomenon, the diversity of the entities and the social media challenges make the task considerably hard to process. As a result, the best scores of the competitions are 63.76% and 71.61% for ENG-SPA and MSA-EGY, respectively. We present the scores of 9 participants and discuss the most common challenges among submissions.
Closing the Loop: Improving Transit through Crowdsourced Information:

Offering real-time arrival information to riders via mobile applications has been shown to improve the rider’s perception of transit, and even increase ridership. This direct connection to riders a...
A Fractional Notion of Length and an Associated Nonlocal Curvature

In this paper, a new notion of fractional length of a smooth curve, which depends on a parameter $$\sigma ,$$ is introduced that is analogous to the fractional perimeter functional of sets. It is shown that in an appropriate limit, the fractional length converges to the traditional notion of length up to a multiplicative constant. Since a curve that connects two points of minimal length must have zero curvature, the Euler–Lagrange equation associated with the fractional length is used to motivate a nonlocal notion of curvature for a curve. This is analogous to how the fractional perimeter has been used to define a nonlocal mean-curvature.
Temperature Variability and Mortality: Evidence from 16 Asian Countries

This paper presents an empirical analysis devised to understand the complex relationship between extreme temperatures and mortality in 16 Asian countries where more than 50% of the world's populati...
HIV-1 Protease Uses Bi-Specific S2/S2' Subsites to Optimize Cleavage of Two Classes of Target Sites

Retroviral proteases (PRs) have a unique specificity that allows cleavage of sites with or without a P1' proline. A P1' proline is required at the MA/CA cleavage site due to its role in a post-cleavage conformational change in the capsid protein. However, the HIV-1 PR prefers to have large hydrophobic amino acids flanking the scissile bond, suggesting that PR recognizes two different classes of substrate sequences. We analyzed the cleavage rate of over 150 combinations of six different HIV-1 cleavage sites to explore rate determinants of cleavage. We found that cleavage rates are strongly influenced by the two amino acids flanking the amino acids at the scissile bond (P2-P1/P1'-P2'), with two complementary sets of rules. When P1' is proline, the P2 side chain interacts with a polar region in the S2 subsite of the PR, while the P2' amino acid interacts with a hydrophobic region of the S2' subsite. When P1' is not proline, the orientations of the P2 and P2' side chains with respect to the scissile bond are reversed; P2 residues interact with a hydrophobic face of the S2 subsite, while the P2' amino acid usually engages hydrophilic amino acids in the S2' subsite. These results reveal that the HIV-1 PR has evolved bi-functional S2 and S2' subsites to accommodate the steric effects imposed by a P1' proline on the orientation of P2 and P2' substrate side chains. These results also suggest a new strategy for inhibitor design to engage the multiple specificities in these subsites.
Tree-to-tree neural networks for program translation

Program translation is an important tool to migrate legacy code in one language into an ecosystem built in a different language. In this work, we are the first to employ deep neural networks toward tackling this problem. We observe that program translation is a modular procedure, in which a sub-tree of the source tree is translated into the corresponding target sub-tree at each step. To capture this intuition, we design a tree-to-tree neural network to translate a source tree into a target one. Meanwhile, we develop an attention mechanism for the tree-to-tree model, so that when the decoder expands one non-terminal in the target tree, the attention mechanism locates the corresponding sub-tree in the source tree to guide the expansion of the decoder. We evaluate the program translation capability of our tree-to-tree model against several state-of-the-art approaches. Compared against other neural translation models, we observe that our approach is consistently better than the baselines with a margin of up to 15 points. Further, our approach can improve the previous state-of-the-art program translation approaches by a margin of 20 points on the translation of real-world projects.
Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects

This paper empirically assesses the wage effects of the Job Corps program, one of the largest federally funded job training programs in the U.S. Even with the aid of a randomized experiment, the impact of a training program on wages is difficult to study because of sample selection, a pervasive problem in applied microeconometric research. Wage rates are only observed for those who are employed, and employment status itself may be affected by the training program. This paper develops an intuitive trimming procedure for bounding average treatment effects in the presence of sample selection. In contrast to existing methods, the procedure requires neither exclusion restrictions nor a bounded support for the outcome of interest. Identification results, estimators, and their asymptotic distribution are presented. The bounds suggest that the program raised wages, consistent with the notion that the Job Corps raises earnings by increasing human capital, rather than solely through encouraging work. The estimator is generally applicable to typical treatment evaluation problems in which there is nonrandom sample selection/attrition. Copyright , Wiley-Blackwell.
Frame-Level Speaker Embeddings for Text-Independent Speaker Recognition and Analysis of End-to-End Model

In this paper, we propose a Convolutional Neural Network (CNN) based speaker recognition model for extracting robust speaker embeddings. The embedding can be extracted efficiently with linear activation in the embedding layer. To understand how the speaker recognition model operates with text-independent input, we modify the structure to extract frame-level speaker embeddings from each hidden layer. We feed utterances from the TIMIT dataset to the trained network and use several proxy tasks to study the networks ability to represent speech input and differentiate voice identity. We found that the networks are better at discriminating broad phonetic classes than individual phonemes. In particular, frame-level embeddings that belong to the same phonetic classes are similar (based on cosine distance) for the same speaker. The frame level representation also allows us to analyze the networks at the frame level, and has the potential for other analyses to improve speaker recognition.
Household financial planning strategies for managing longevity risk

[enter Abstract Body]This study examines how longevity risk, in conjunction with other postretirement risks, impacts retirement consumption decisions and retirement wealth needs. We develop a theoretical model that directly examines the relationship between longevity risk and consumption/savings, and empirically test these theoretical implications by simulating retirement outcomes for representative households, including longevity, inflation, investment, health, and long‐term care risks. Our study shows that the top third of households by longevity need approximately 20% more retirement wealth than those households who live only an average life span. Investigations of various risk mitigation strategies suggest that combination strategies, particularly those that include delayed retirement, can significantly reduce the retirement wealth target. This research provides valuable new insights on household financial planning strategies for managing longevity risk. Full Text Available Here: https://doi.org/10.1002/cfp2.1007
Characteristics of petroleum product prices: A survey

Abstract We review and synthesize the empirical evidence on several factors related to petroleum product prices: (1) the general distributional characteristics of petroleum product prices; (2) the influence of refinery outages, extreme weather, and similar circumstances on product prices; (3) the way that price discovery occurs for petroleum products; (4) the predictive accuracy of petroleum product futures prices for future spot prices; and (5) the impact of speculation on product prices.