cssi/SciSciGPT-SciSciNet huggingface dataset:
Building Coalitions Out of Thin Air: Transferable Development Rights and “Constituency Effects” in Land Use Law

Transferable Development Rights (TDRs) were supposed to be a solution to the intractable problems of land use, a bit of institutional design magic that married the interests of development and preservation at no cost to taxpayers and with no legal risk. Under a TDR program, development is limited or barred on properties targeted for preservation or other regulatory goals, but owners of those lots are allowed sell their unused development rights to other property owners. In theory, this allows the same amount of development to occur while preserving favored uses without tax subsidies or constitutional challenges. Reviewing their use over the last forty years, this Article shows that the traditional justifications for TDRs do not work. In practice, TDRs are not necessary to avoid takings litigation, are not costless to taxpayers, and do not balance the interests of preservation and development, but instead serve as yet another growth control in metropolitan areas where such controls have caused housing crises and major harms to the national economy. Assessed as a technocratic tool for solving problems in land use, TDRs are a failure. But this Article shows that there is a case for TDRs not as a technocratic but rather as a political tool. By giving valuable development rights to some popular or otherwise politically influential owners of regulated property, a city can build a coalition for re-zonings that might otherwise be politically impossible. The effect of TDRs on politics can be positive to the extent that TDRs strengthen constituencies or land use goals that local politics systematically undercounts, as we show through an analysis of New York City’s Special District Transfer TDR program. In particular, TDRs could help break Not In My Back Yard opposition to new development by building a competing pro-growth coalition. More generally, using TDRs as an example, the Article shows how land use law is the creator as well as creature of local politics. Existing property law helps cement anti-development coalitions, but savvy leaders could use moments in power to create stable pro-growth coalitions by enacting new laws that help mobilize new pro-growth constituencies. Understanding these “constituency effects” of land use law allows policymakers to redesign entitlements like TDRs to produce a healthier land use policies.
Direct Experimental Evidence of Hot Carrier-Driven Chemical Processes in Tip-Enhanced Raman Spectroscopy (TERS)

Nanoscale localization of electromagnetic fields using metallic nanostructures can catalyze chemical reactions in their immediate vicinity. Local optical field confinement and enhancement is also e...
Coxeter Groups, 2-Completion, Perimeter Reduction and Subgroup Separability

We show that all groups in a very large class of Coxeter groups are locally quasiconvex and have a uniform membership problem solvable in quadratic time. If a group in the class satisfies a further hypothesis it is subgroup separable and relevant homomorphisms are also calculable in quadratic time. The algorithm also decides if a finitely generated subgroup has finite index.
SERS Nanoprobe for Intracellular Monitoring of Viral Mutations

Gold nanostars, functionalized with thiolated DNA hairpins bearing a Raman-active fluorescent dye at the 3′ terminus, were engineered to identify and quantify RNA mutations in the influenza A virus...
Pioneer Design of Non-contact Synchronized Measurement Devices Using Electric and Magnetic Field Sensors

Traditional synchrophasors rely on CTs and PTs physically connected to transmission lines or buses to acquire input signals for phasor measurement. However, it is challenging to install and maintain traditional phasor measurement units in some remote areas due to lack of facilities. Since transmission lines naturally generate alternating electrical and magnetic fields in the surrounding atmosphere, this paper presents two innovative designs for non-contact synchronized measurement devices (NCSMD), including an electric field sensor based non-contact SMD (E-NCSMD) and a magnetic field sensor based non-contact SMD (M-NCSMD). Compared with conventional synchrophasors, E-NCSMD and M-NCSMD are much more flexible to be deployed and have much lower costs, making E-NCSMDs and M-NCSMD highly accessible and useful for a wide array of phasor measurement applications. Laboratory and field experiment results verified the effectiveness of the designs of both E-NCSMD and M-NCSMD.
Approximately Strategyproof Tournament Rules: On Large Manipulating Sets and Cover-Consistence

We consider the manipulability of tournament rules, in which n teams play a round robin tournament and a winner is (possibly randomly) selected based on the outcome of all binom{n}{2} matches. Prior work defines a tournament rule to be k-SNM-α if no set of ≤ k teams can fix the ≤ binom{k}{2} matches among them to increase their probability of winning by >α and asks: for each k, what is the minimum α(k) such that a Condorcet-consistent (i.e. always selects a Condorcet winner when one exists) k-SNM-α(k) tournament rule exists? A simple example witnesses that α(k) ≥ (k-1)/(2k-1) for all k, and [Jon Schneider et al., 2017] conjectures that this is tight (and prove it is tight for k=2). Our first result refutes this conjecture: there exists a sufficiently large k such that no Condorcet-consistent tournament rule is k-SNM-1/2. Our second result leverages similar machinery to design a new tournament rule which is k-SNM-2/3 for all k (and this is the first tournament rule which is k-SNM-(<1) for all k). Our final result extends prior work, which proves that single-elimination bracket with random seeding is 2-SNM-1/3 [Jon Schneider et al., 2017], in a different direction by seeking a stronger notion of fairness than Condorcet-consistence. We design a new tournament rule, which we call Randomized-King-of-the-Hill, which is 2-SNM-1/3 and cover-consistent (the winner is an uncovered team with probability 1).
Inverse-Designed Photonics for Semiconductor Foundries

Silicon photonics is becoming a leading technology in photonics, displacing traditional fiber optic transceivers and enabling new applications. Further improving the density and performance of sili...
Engineered Biosynthesis of Alkyne-Tagged Polyketides by Type I PKSs

Polyketides produced by modular polyketide synthases (PKSs) are important small molecules widely used as drugs, pesticides, and biological probes. Tagging these polyketides with a clickable functionality enables the visualization, diversification, and mode of action study through bio-orthogonal chemistry. We report the de novo biosynthesis of alkyne-tagged polyketides by modular type I PKSs through starter unit engineering. Specifically, we use JamABC, a terminal alkyne biosynthetic machinery from the jamaicamide B biosynthetic pathway, in combination with representative modular PKSs. We demonstrate that JamABC works as a trans loading system for engineered type I PKSs to produce alkyne-tagged polyketides. In addition, the production efficiency can be improved by enhancing the interactions between the carrier protein (JamC) and PKSs using docking domains and site-directed mutagenesis of JamC. This work thus provides engineering guidelines and strategies that are applicable to additional modular type I PKSs to produce targeted alkyne-tagged metabolites for chemical and biological applications.
Barriers and Facilitators to Implementation of BEST in CLASS.

The primary purpose of this paper is to review how BEST in CLASS, an evidence-based program targeting children at risk for emotional and behavior disorders, interacts with a diverse range of social...
A High-Quality Genome Assembly of the North American Song Sparrow, Melospiza melodia.

The song sparrow, Melospiza melodia, is one of the most widely distributed species of songbirds found in North America. It has been used in a wide range of behavioral and ecological studies. This species’ pronounced morphological and behavioral diversity across populations makes it a favorable candidate in several areas of biomedical research. We have generated a high-quality de novo genome assembly of M. melodia using Illumina short read sequences from genomic and in vitro proximity-ligation libraries. The assembled genome is 978.3 Mb, with a physical coverage of 24.9×, N50 scaffold size of 5.6 Mb and N50 contig size of 31.7 Kb. Our genome assembly is highly complete, with 87.5% full-length genes present out of a set of 4,915 universal single-copy orthologs present in most avian genomes. We annotated our genome assembly and constructed 15,086 gene models, a majority of which have high homology to related birds, Taeniopygia guttata and Junco hyemalis. In total, 83% of the annotated genes are assigned with putative functions. Furthermore, only ∼7% of the genome is found to be repetitive; these regions and other non-coding functional regions are also identified. The high-quality M. melodia genome assembly and annotations we report will serve as a valuable resource for facilitating studies on genome structure and evolution that can contribute to biomedical research and serve as a reference in population genomic and comparative genomic studies of closely related species.
Millimeter-Wave Four-Wave Mixing via Kinetic Inductance for Quantum Devices

Millimeter-wave superconducting devices offer a platform for quantum experiments at temperatures above 1 K, and new avenues for studying light-matter interactions in the strong coupling regime. Using the intrinsic nonlinearity associated with kinetic inductance of thin-film materials, we realize four-wave mixing at millimeter-wave frequencies, demonstrating a key component for superconducting quantum systems. We report on the performance of niobium nitride resonators around 100 GHz, patterned on thin (20--50-nm) films grown by atomic layer deposition, with sheet inductances up to $212\phantom{\rule{0.2em}{0ex}}\mathrm{pH}/◻$ and critical temperatures up to 13.9 K. For films thicker than 20 nm, we measure quality factors from $1\ifmmode\times\else\texttimes\fi{}{10}^{4}$ to $6\ifmmode\times\else\texttimes\fi{}{10}^{4}$, and explore potential loss mechanisms. Finally, we measure degenerate parametric conversion for a 95-GHz device with a forward efficiency up to $+16\phantom{\rule{0.2em}{0ex}}\mathrm{dB}$, paving the way for the development of nonlinear quantum devices at millimeter-wave frequencies.
Single cell transcriptome profiling of the human alcohol-dependent brain.

Alcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain. We utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16 000 nuclei isolated from the prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes and microglia. To our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species and the first such analysis in humans for any addictive substance. These findings greatly advance the understanding of transcriptomic changes in the brain of alcohol-dependent individuals.
Complex Evolutionary History of the Y Chromosome in Flies of the Drosophila Obscura Species Group

The Drosophila obscura species group shows dramatic variation in karyotype, including transitions among sex chromosomes. Members of the affinis and pseudoobscura subgroups contain a neo-X chromosome (a fusion of the X with an autosome), and ancestral Y genes have become autosomal in species harboring the neo-X. Detailed analysis of species in the pseudoobscura subgroup revealed that ancestral Y genes became autosomal through a translocation to the small dot chromosome. Here, we show that the Y-dot translocation is restricted to the pseudoobscura subgroup, and translocation of ancestral Y genes in the affinis subgroup likely followed a different route. We find that most ancestral Y genes have translocated to unique autosomal or X-linked locations in different taxa of the affinis subgroup, and we propose a dynamic model of sex chromosome formation and turnover in the obscura species group. Our results suggest that Y genes can find unique paths to escape unfavorable genomic environments that form after sex chromosome-autosome fusions.
Market Dynamics and Optimal Timber Salvage After a Natural Catastrophe

Forest-based natural catastrophes are regular features of timber production in the United States, especially from hurricanes, fires, and insect and disease outbreaks. These catastrophes affect timber prices and result in economic transfers. We develop a model of timber market dynamics after such a catastrophe that shows how timber salvage affects the welfare of different market groups and quantifies the impacts of salvage on product markets. A theoretical framework is developed that explores how government spending to mitigate economic losses through salvage is related to the costs of intervention. Using empirical price and quantity parameters derived for Hurricane Hugo as an example, we simulate how alternative levels of salvage would have affected southern pine timber prices and economic surplus. Results show that for this large-scale disturbance, the economic surplus generated by salvage averaged $6.25 million for each percentage change in the volume of salvaged timber up to the observed salvage rate (-16%). Consumers benefited by an average of $5.4 million for each percent of the damaged timber that was salvaged, producers of salvaged timber benefited by $6.4 million for each percent salvaged, and producers of undamaged timber lost an average of $5.6 million for each percent salvaged. Sawtimber salvage yielded welfare benefits for each cubic meter averaging more than four times those generated by pulpwood. These results therefore have implications for strategic salvage planning follow- ing catastrophic damage to forests. FOR. SCI. 50(4):495-511.
Investigating the Chemical Reactivity of Lithium Silicate Model SEI Layers

Silicon anodes suffer from an unstable solid electrolyte interphase (SEI) layer that contributes to undesirable capacity fade with cycling. A key part to addressing this unstable SEI formation is t...
Spectral graph theory of brain oscillations

The relationship between the brain's structural wiring and the functional patterns of neural activity is of fundamental interest in computational neuroscience. We examine a hierarchical, linear graph spectral model of brain activity at mesoscopic and macroscopic scales. The model formulation yields an elegant closed-form solution for the structure-function problem, specified by the graph spectrum of the structural connectome's Laplacian, with simple, universal rules of dynamics specified by a minimal set of global parameters. The resulting parsimonious and analytical solution stands in contrast to complex numerical simulations of high dimensional coupled nonlinear neural field models. This spectral graph model accurately predicts spatial and spectral features of neural oscillatory activity across the brain and was successful in simultaneously reproducing empirically observed spatial and spectral patterns of alpha-band (8-12 Hz) and beta-band (15-30 Hz) activity estimated from source localized magnetoencephalography (MEG). This spectral graph model demonstrates that certain brain oscillations are emergent properties of the graph structure of the structural connectome and provides important insights towards understanding the fundamental relationship between network topology and macroscopic whole-brain dynamics. .
Reducing the Complexity of Fingerprinting-Based Positioning using Locality-Sensitive Hashing

Localization of wireless transmitters based on channel state information (CSI) fingerprinting finds widespread use in indoor as well as outdoor scenarios. Fingerprinting localization first builds a database containing CSI with measured location information. One then searches for the most similar CSI in this database to approximate the position of wireless transmitters. In this paper, we investigate the efficacy of locality-sensitive hashing (LSH) to reduce the complexity of the nearest neighbor- search (NNS) required by conventional fingerprinting localization systems. More specifically, we propose a low-complexity and memory efficient LSH function based on the sum-to-one (STOne) transform and use approximate hash matches. We evaluate the accuracy and complexity (in terms of the number of searches and storage requirements) of our approach for line-of-sight (LoS) and non-LoS channels, and we show that LSH enables low-complexity fingerprinting localization with comparable accuracy to methods relying on exact NNS or deep neural networks.
Three dimensions, two microscopes, one code: Automatic differentiation for x-ray nanotomography beyond the depth of focus limit

Conventional tomographic reconstruction algorithms assume that one has obtained pure projection images, involving no within-specimen diffraction effects nor multiple scattering. Advances in x-ray nanotomography are leading toward the violation of these assumptions, by combining the high penetration power of x-rays, which enables thick specimens to be imaged, with improved spatial resolution that decreases the depth of focus of the imaging system. We describe a reconstruction method where multiple scattering and diffraction effects in thick samples are modeled by multislice propagation and the 3D object function is retrieved through iterative optimization. We show that the same proposed method works for both full-field microscopy and for coherent scanning techniques like ptychography. Our implementation uses the optimization toolbox and the automatic differentiation capability of the open-source deep learning package TensorFlow, demonstrating a straightforward way to solve optimization problems in computational imaging with flexibility and portability.
Perturbation Analysis for Stochastic Fluid Queueing Systems

Recent study for congestion control in high speed networks indicates that the derivative information for the congestion at the common buffer for multiple sources could be useful in achieving efficient and fair allocation of the bandwidth (Kelly, 1997; Kelly et al., 1998). In this paper we present an algorithm that estimates such derivatives for multiple on-off sources. The algorithm has its root in the infinitesimal perturbation analysis (IPA) for the classical queueing systems. Although the traditional IPA algorithm does not give unbiased derivative estimates for multi-class arrivals, we are able to prove the unbiasedness in the case of multi-class ON-OFF sources. The results in this paper may motivate a new look at the end-to-end congestion control issue.
Rad53 limits CMG helicase uncoupling from DNA synthesis at replication forks

The coordination of DNA unwinding and synthesis at replication forks promotes efficient and faithful replication of chromosomal DNA. Disruption of the balance between helicase and polymerase activities during replication stress leads to fork progression defects and activation of the Rad53 checkpoint kinase, which is essential for the functional maintenance of stalled replication forks. The mechanism of Rad53-dependent fork stabilization is not known. Using reconstituted budding yeast replisomes, we show that mutational inactivation of the leading strand DNA polymerase, Pol e, dNTP depletion, and chemical inhibition of DNA polymerases cause excessive DNA unwinding by the replicative DNA helicase, CMG, demonstrating that budding yeast replisomes lack intrinsic mechanisms that control helicase–polymerase coupling at the fork. Importantly, we find that the Rad53 kinase restricts excessive DNA unwinding at replication forks by limiting CMG helicase activity, suggesting a mechanism for fork stabilization by the replication checkpoint. In vitro assays using a fully reconstituted DNA replication system reveal that the checkpoint kinase Rad53 restrains CMG helicase activity to prevent DNA unwinding and collapse of stalled forks in response to replication stress.
Energy Flexibility for an Institutional Building with Integrated Solar System: Case Study Analysis

The integration of renewable energy technologies and energy storage systems can provide significant energy flexibility to buildings, minimizing their impact on the power grid stability. In this regard, the development of suitable load management strategies is necessary for properly estimating and optimizing the building flexibility as a function of the building-plant feature and of the environmental conditions. This paper focuses on the quantification of the energy flexibility of a high performance institutional public building located in Varennes (Quebec, Canada), with the aim of reducing both the peak load demand and the energy consumption during a certain period of a day. The building integrates innovative technologies based on renewable energy, including geothermal heat pumps, PV panels, and radiant floors. To this aim, a tool based on a combined adaptive Auto Regressive model with exogenous inputs (ARX) is developed to predict the building indoor air and concrete surface slab temperature by taking into account the optimal operation of a geothermal heat pump, run by renewable electricity from PV panels. Several modelling strategies are tested in order to increase the reliability of the proposed approach. Modeling results are explored to quantify the possible flexibility of a sunny cold day through test scenarios compared to measurements. Numerical simulation results show that the proposed flexibility strategy can achieve peak demand reduction of 40 % during morning period and 30 % during evening period. Finally, tests using real data confirm the validity of the model as a tool to estimate energy flexibility in high performance buildings.
Rediscovering Buchanan’s rediscovery: non-market exchange versus antiseptic allocation

While Buchanan is best known for the economics of politics and constitutions, his seminal contributions to this field are but one branch of his more underlying methodology and approach to doing social science. Buchanan’s fundamental project was to re-orient economics and social science toward an analysis of symbiotic exchange (catallactics) rather than of antiseptic allocation (optimization). The most definite statement of this contribution lies in Buchanan’s 1963 presidential address to the Southern Economic Association, “What should economists do?” which was later expanded into a book of the same title. This paper seeks to draw attention to several of Buchanan’s more recent but lesser known articles where he fully develops this theme. He calls on economists to rediscover Adam Smith’s “elementary notion” about the division of labor and the extent of the market, and he professes the notion of “generalized increasing returns” as a mechanism for economists to rediscover their Scottish Enlightenment roots within the neoclassical framework. In this same vein, we also discuss how Buchanan’s rediscovery might apply to two prominent and ongoing twenty-first century issues, trade restrictions and populism.
Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome.

PURPOSEPersonalized network inference on diverse clinical and in vitro model systems across cancer types can be used to delineate specific regulatory mechanisms, uncover drug targets and pathways, ...
Is Price Adjustment Asymmetric?: Evaluating the Market Share and Marketing Bottlenecks Hypothesis

Abstract Export price adjustment is asymmetric with respect to currency fluctuations in at least two circumstances. If firms face capacity constraints in distribution networks or quantitative trade restrictions, then pricing-to-market may be greater during depreciations of the exporter's currency. If firms attempt to build market share subject to the threat of trade restrictions, then pricing-to-market may be greater during appreciations of the exporter's currency. This paper tests for asymmetries using panel data on German and Japanese 7-digit industry exports. The data seldom reject the hypothesis of a symmetric response of prices to exchange rates.
MONETARY POLICY IN A WORLD WITHOUT MONEY

This paper considers whether the development of ‘electronic money’ poses any threat to the ability of central banks to control the value of their national currencies through conventional monetary policy. It argues that, even if the demand for base money for use in facilitating transactions is largely or even completely eliminated, monetary policy should continue to be effective. Macroeconomic stabilization depends only upon the ability of central banks to control a short-term nominal interest rate, and this would continue to be possible, in particular through the use of a ‘channel’ system for the implementation of policy, like those currently used in Canada, Australia and New Zealand.
The structure of the magnetopause

Abstract The solar wind is a magnetized flowing plasma that intersects the Earth's magnetosphere at a velocity much greater than that of the compressional fast mode wave that is required to deflect that flow. A bow shock forms that alters the properties of the plasma and slows the flow, enabling continued evolution of the properties of the flow on route to its intersection with the magnetopause. Thus the plasma conditions at the magnetopause can be quite unlike those in the solar wind. The boundary between this “magnetosheath” plasma and the magnetospheric plasma is many gyroradii thick and is surrounded by several boundary layers. A very important process occurring at the magnetopause is reconnection whereby there is a topological change in magnetic flux lines so that field lines can connect the solar wind plasma to the terrestrial plasma, enabling the two to mix. This connection has important consequences for momentum transfer from the solar wind to the magnetosphere. The initiation of reconnection appears to be at locations where the magnetic fields on either side of the magnetopause are antiparallel. This condition is equivalent to there being no guide field in the reconnection region, so at the reconnection point there is truly a magnetic neutral or null point. Lastly reconnection can be spatially and temporally varying, causing the region of the magnetopause to be quite dynamic.
Production of ethanol from starch by co-immobilized Zymomonas mobilis-glucoamylase in a fluidized-bed reactor.

The production of ethanol from starch was studied in a fluidized-bed reactor (FBR) using co-immobilized Zymomonas mobilis and glucoamylase. The FBR was a glass column of 2.54 cm in diameter and 120 cm in length. The Z. mobilis and glucoamylase were co-immobilized within small uniform beads (1.2-2.5 mm diameter) of K-carrageenan. The substrate for ethanol production was a soluble starch. Light steep water was used as the complex nutrient source. The experiments were performed at 35°C and pH range of 4.0-5.5. The substrate concentrations ranged from 40 to 185 g/L, and the feed rates from 10 to 37 mL/min. Under relaxed sterility conditions, the FBR was successfully operated for a period of 22 d, during which no contamination or structural failure of the biocatalyst beads was observed. Volumetric productivity as high as 38 g ethanol/(Lh), which was 74% of the maximum expected value, was obtained. Typical ethanol volumetric productivity was in the range of 15-20 g/(Lh). The average yield was 0.49 g ethanol/g substrate consumed, which was 90% of the theoretical yield. Very low levels of glucose were observed in the reactor, indicating that starch hydrolysis was the rate-limiting step.
A Statistical Model for Event Sequence Data

The identification of recurring patterns within a sequence of events is an important task in behavior research. In this paper, we consider a general probabilistic framework for identifying such patterns, by distinguishing between events that belong to a pattern and events that occur as part of background processes. The event processes, both for background events and events that are part of recurring patterns, are modeled as competing renewal processes. Using this framework, we develop an inference procedure to detect the sequences present in observed data. Our method is compared to a current approach used within the ethology literature on both simulated data and data collected to study the impact of fragmented and unpredictable maternal behavior on cognitive development of children.
A List-Mode OSEM-Based Attenuation and Scatter Compensation Method for SPECT

Reliable attenuation and scatter compensation (ASC) is a pre-requisite for quantification and beneficial for visual interpretation tasks in SPECT. In this paper, we develop a reconstruction method that uses the entire SPECT emission data, i.e. data in both the photopeak and scatter windows, acquired in list-mode format and including the energy attribute of the detected photon, to perform ASC. We implemented a GPU-based version of this method using an ordered subsets expectation maximization (OSEM) algorithm. The method was objectively evaluated using realistic simulation studies on the task of estimating uptake in the striatal regions of the brain in a 2-D dopamine transporter (DaT)-scan SPECT study. We observed that inclusion of data from the scatter window and using list-mode data yielded improved quantification compared to using data only from the photopeak window or using binned data. These results motivate further development of list-mode-based ASC methods that include scatter-window data for SPECT.
Public opinion on nuclear energy and nuclear weapons: The attitudinal nexus in the United States

Abstract Does a lack of enthusiasm for nuclear energy among the US public relate to connections with nuclear weapons? The United States is projected to decline as the global leader in nuclear power production due to stagnation in the industry. Alongside this trend, US public skepticism of nuclear energy has remained high for decades. Policymakers, industry, and pro- and anti-nuclear advocates must understand these attitudes given electricity needs, energy sector competition, and climate change. Existing scholarship explains public opinion on nuclear power by comparing its economic and environmental desirability with other energy sources. Yet, a critical area of public opinion remains understudied: the connection between nuclear energy and nuclear weapons. Scholars have theorized such a relationship in the public consciousness, but the premise has not been systematically investigated. Two studies examine this theoretical linkage. Study 1 uses a nationally representative US survey experiment ( n = 904 ) to validate that public attitudes toward civilian and military nuclear technologies are indeed related. Study 2 uses an exploratory survey experiment ( n = 1 , 003 ) to show that persuasive information about each technology affects opinion about the other. These studies provide evidence of psychological linkage. In fact, attitudes toward nuclear weapons may even drive those on nuclear energy.
Learning Calibratable Policies using Programmatic Style-Consistency

We study the important and challenging problem of controllable generation of long-term sequential behaviors. Solutions to this problem would impact many applications, such as calibrating behaviors of AI agents in games or predicting player trajectories in sports. In contrast to the well-studied areas of controllable generation of images, text, and speech, there are significant challenges that are unique to or exacerbated by generating long-term behaviors: how should we specify the factors of variation to control, and how can we ensure that the generated temporal behavior faithfully demonstrates diverse styles? In this paper, we leverage large amounts of raw behavioral data to learn policies that can be calibrated to generate a diverse range of behavior styles (e.g., aggressive versus passive play in sports). Inspired by recent work on leveraging programmatic labeling functions, we present a novel framework that combines imitation learning with data programming to learn style-calibratable policies. Our primary technical contribution is a formal notion of style-consistency as a learning objective, and its integration with conventional imitation learning approaches. We evaluate our framework using demonstrations from professional basketball players and agents in the MuJoCo physics environment, and show that our learned policies can be accurately calibrated to generate interesting behavior styles in both domains.
Improved Speech Representations with Multi-Target Autoregressive Predictive Coding

Training objectives based on predictive coding have recently been shown to be very effective at learning meaningful representations from unlabeled speech. One example is Autoregressive Predictive Coding (Chung et al., 2019), which trains an autoregressive RNN to generate an unseen future frame given a context such as recent past frames. The basic hypothesis of these approaches is that hidden states that can accurately predict future frames are a useful representation for many downstream tasks. In this paper we extend this hypothesis and aim to enrich the information encoded in the hidden states by training the model to make more accurate future predictions. We propose an auxiliary objective that serves as a regularization to improve generalization of the future frame prediction task. Experimental results on phonetic classification, speech recognition, and speech translation not only support the hypothesis, but also demonstrate the effectiveness of our approach in learning representations that contain richer phonetic content.
The Nash Equilibrium Revisited: Chaos and Complexity Hidden in Simplicity

The Nash Equilibrium is a much discussed, deceptively complex, method for the analysis of non-cooperative games (McLennan and Berg, 2005). If one reads many of the commonly available definitions the description of the Nash Equilibrium is deceptively simple in appearance. Modern research has discovered a number of new and important complex properties of the Nash Equilibrium, some of which remain as contemporary conundrums of extraordinary difficulty and complexity (Quint and Shubik, 1997). Among the recently discovered features which the Nash Equilibrium exhibits under various conditions are heteroclinic Hamiltonian dynamics, a very complex asymptotic structure in the context of two-player bi-matrix games and a number of computationally complex or computationally intractable features in other settings (Sato, Akiyama and Farmer, 2002). This paper reviews those findings and then suggests how they may inform various market prediction strategies.
Auditing News Curation Systems: A Case Study Examining Algorithmic and Editorial Logic in Apple News

This work presents an audit study of Apple News as a sociotechnical news curation system that exercises gatekeeping power in the media. We examine the mechanisms behind Apple News as well as the content presented in the app, outlining the social, political, and economic implications of both aspects. We focus on the Trending Stories section, which is algorithmically curated, and the Top Stories section, which is human-curated. Results from a crowdsourced audit showed minimal content personalization in the Trending Stories section, and a sock-puppet audit showed no location-based content adaptation. Finally, we perform an extended two-month data collection to compare the human-curated Top Stories section with the algorithmically-curated Trending Stories section. Within these two sections, human curation outperformed algorithmic curation in several measures of source diversity, concentration, and evenness. Furthermore, algorithmic curation featured more “soft news” about celebrities and entertainment, while editorial curation featured more news about policy and international events. To our knowledge, this study provides the first data-backed characterization of Apple News in the United States.
Singularities and Genus of the k-Ellipse

Abstract A k-ellipse is a plane curve consisting of all points whose distances from k fixed foci sum to a constant. We determine the singularities and genus of its Zariski closure in the complex projective plane. The paper resolves an open problem stated by Nie, Parrilo and Sturmfels in 2008.
Scalable Heterogeneous Social Network Alignment through Synergistic Graph Partition

Social network alignment has been an important research problem for social network analysis in recent years. With the identified shared users across networks, it will provide researchers with the opportunity to achieve a more comprehensive understanding of users' social activities both within and across networks. Social network alignment is a very difficult problem. Besides the challenges introduced by the network heterogeneity, the network alignment can be reduced to a combinatorial optimization problem with an extremely large search space. The learning effectiveness and efficiency of existing alignment models will be degraded significantly as the network size increases. In this paper, we focus on studying the scalable heterogeneous social network alignment problem and propose to address it with a novel two-stage network alignment model, namely Scalable Heterogeneous Network Alignment (SHNA). Based on a group of intra- and inter-network meta diagrams, SHNA first partitions the social networks into a group of sub-networks synergistically. Via the partially known anchor links, SHNA can extract the partitioned sub-network correspondence relationships. Instead of aligning the complete input network, SHNA proposes to identify the anchor links between the matched sub-network pairs, while those between the unmatched sub-networks will be pruned to effectively shrink the search space. Extensive experiments have been done to compare SHNA with the state-of-the-art baseline methods on a real-world aligned social networks dataset. The experimental results have demonstrated both the effectiveness and efficiency of SHNA in addressing the problem.
Fully interpretable deep learning model of transcriptional control.

MOTIVATION The universal expressibility assumption of Deep Neural Networks (DNNs) is the key motivation behind recent worksin the systems biology community to employDNNs to solve important problems in functional genomics and moleculargenetics. Typically, such investigations have taken a 'black box' approach in which the internal structure of themodel used is set purely by machine learning considerations with little consideration of representing the internalstructure of the biological system by the mathematical structure of the DNN. DNNs have not yet been applied to thedetailed modeling of transcriptional control in which mRNA production is controlled by the binding of specific transcriptionfactors to DNA, in part because such models are in part formulated in terms of specific chemical equationsthat appear different in form from those used in neural networks. RESULTS In this paper, we give an example of a DNN whichcan model the detailed control of transcription in a precise and predictive manner. Its internal structure is fully interpretableand is faithful to underlying chemistry of transcription factor binding to DNA. We derive our DNN from asystems biology model that was not previously recognized as having a DNN structure. Although we apply our DNNto data from the early embryo of the fruit fly Drosophila, this system serves as a test bed for analysis of much larger datasets obtained by systems biology studies on a genomic scale. . AVAILABILITY AND IMPLEMENTATION The implementation and data for the models used in this paper are in a zip file in the supplementary material. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
A GPU-Accelerated Barycentric Lagrange Treecode.

We present an MPI + OpenACC implementation of the kernel-independent barycentric Lagrange treecode (BLTC) for fast summation of particle interactions on GPUs. The distributed memory parallelization uses recursive coordinate bisection for domain decomposition and MPI remote memory access to build locally essential trees on each rank. The particle interactions are organized into target batch/source cluster interactions which efficiently map onto the GPU; target batching provides an outer level of parallelism, while the direct sum form of the barycentric particle-cluster approximation provides an inner level of parallelism. The GPU-accelerated BLTC performance is demonstrated on several test cases up to 1 billion particles interacting via the Coulomb potential and Yukawa potential.
Solar Models:. AN Historical Overview

I will summarize in four slides the 40 years of development of the standard solar model that is used to predict solar neutrino fluxes and then describe the current uncertainties in the predictions. I will dispel the misconception that the p-p neutrino flux is determined by the solar luminosity and present a related formula that gives, in terms of the p-p and 7Be neutrino fluxes, the ratio of the rates of the two primary ways of terminating the p-p fusion chain. I will also attempt to explain why it took so long, about three and a half decades, to reach a consensus view that new physics is being learned from solar neutrino experiments. Finally, I close with a personal confession and some personal remarks.
Coulomb barrier creation by means of electronic field emission in nanolayer capacitors

The main mechanism of energy loss in capacitors with nanoscale dielectric films is leakage currents. Using the example of Al-Al2O3-Al, we show that there are two main contributions, namely the cold field emission effect and the hopping conductivity through the dielectric. Our main finding is that an application of a high electric field, ∼0.6-0.7 GV m-1, causes electrons to penetrate the dielectric. If the temperature is sufficiently low, such electrons become permanently trapped in the dielectric. To achieve a strong charging of the dielectric, the voltage needs to be high enough, so that a field emission occurs from the cathode into the dielectric. Such a strongly charged dielectric layer generates a Coulomb barrier and leads to a suppression of the leakage current. Thus, after the dielectric nanolayer of the capacitor is charged, the field emission and the hopping conductivity are both suppressed, and the hysteresis of the I-V curve disappears. The phenomenon is observed at temperatures up to ∼225 K. It would be advantageous to identify insulators in which the phenomenon of the Coulomb barriers persists even up to the room temperature, but at this time it is not known whether such dielectrics exist and/or can be designed.
Measurement and Structure of Cognition in the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia.

Objectives To test whether a relatively complex model of human cognitive abilities based on Cattell-Horn-Carroll (CHC) theory, developed mainly in English-speaking samples, adequately describes correlations among tests in the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD), and to develop accurate measures of cognition for older individuals in India. Design LASI-DAD participants were recruited from participants aged 60 years and older from 14 states in the core LASI survey, with a stratified sampling design. Setting Participants were interviewed at home or in a participating hospital, according to their preferences. Participants Community-residing older adults aged 60 years and older (N = 3,224). Measurements A variety of cognitive tests were administered during two pretests and chosen for their appropriateness for measuring cognition in older adults in India and suitability for calibration with the core LASI survey and the Harmonized Cognitive Assessment Protocol. Results We evaluated the factor structure of the test battery and its conformity with a classical CHC factor model that incorporated measurement models for general cognition, five broad domains (orientation, executive functioning, language/fluency, memory, and visuospatial), and five narrow domains (reasoning, attention/speed, immediate memory, delayed memory, and recognition memory) of cognitive performance. Model fit was adequate (root mean square error of approximation = 0.051; comparative fit index = 0.916; standardized root mean squared residual = 0.060). Conclusion We demonstrated configural factorial invariance of a cognitive battery in the Indian LASI-DAD using CHC theory. Broad domain factors may be used in future research to rank individuals with respect to cognitive performance and classify cognitive impairment. J Am Geriatr Soc 68:S11-S19, 2020.
On Designing Secure and Robust Scan Chain for Protecting Obfuscated Logic

In this paper, we assess the security and testability of the state-of-the-art design-for-security (DFS) architectures in the presence of scan-chain locking/obfuscation, a group of solution that has previously proposed to restrict unauthorized access to the scan chain. We discuss the key leakage vulnerability in the recently published prior-art DFS architectures. This leakage relies on the potential glitches in the DFS architecture that could lead the adversary to make a leakage condition in the circuit. Also, we demonstrate that the state-of-the-art DFS architectures impose some substantial architectural drawbacks that moderately affect both test flow and design constraints. We propose a new DFS architecture for building a secure scan chain architecture while addressing the potential of key leakage. The proposed architecture allows the designer to perform the structural test with no limitation, enabling an untrusted foundry to utilize the scan chain for manufacturing fault testing without having a need to access the scan chain. Our proposed solution poses negligible limitation/overhead on the test flow, as well as the design criteria.
Scaling Behavior of a Turbulent Kinetic Energy Closure Scheme for the Stably Stratified Atmosphere: A Steady-State Analysis

We present a turbulent kinetic energy (TKE) closure scheme for the stably stratified atmosphere in which the mixing lengths for momentum and heat are not parameterized in the same manner. The key difference is that, while the mixing length for heat tends towards the stability independent mixing length for momentum in neutrally stratified conditions, it tends towards one based on the Brunt-V\"ais\"al\"a time scale and square root of the TKE in the limit of large stability. This enables a unique steady-state solution for TKE to be obtained, which we demonstrate would otherwise be impossible if the mixing lengths were the same. Despite the model's relative simplicity, it is shown to perform reasonably well with observational data from the 1999 Cooperative Atmosphere-Surface Exchange Study (CASES-99) using commonly employed model constants. Analyzing the scaling behavior of the non-dimensional velocity and potential temperature gradients, or of the stability (correction) functions, reveals that for large stability the present model scales in the same manner as the first-order operational scheme of Viterbo et al. (Quart. J. Roy. Meteor. Soc. 125, 2401-2426, 1999). Alternatively, it appears as a blend of two cases of the TKE closure scheme of Baas et al. (Bound.-Layer Meteor. 127, 17-36, 2008). Critically, because a unique steady-state TKE can be obtained, the present model avoids the non-physical behavior identified in one of the cases of Baas et al. (2008).