cssi/SciSciGPT-SciSciNet huggingface dataset:
Domain reduction for monotonicity testing: a o(d) tester for boolean functions in d-dimensions

We describe a O(d5/6)-query monotonicity tester for Boolean functions f : [n]d → {0, 1} on the n-hypergrid. This is the first o(d) monotonicity tester with query complexity independent of n. Motivated by this independence of n, we initiate the study of monotonicity testing of measurable Boolean functions f: Rd → {0, 1} over the continuous domain, where the distance is measured with respect to a product distribution over Rd. We give a O(d5/6)-query monotonicity tester for such functions. Our main technical result is a domain reduction theorem for monotonicity. For any function f : [n]d → {0, 1}, let ef be its distance to monotonicity. Consider the restriction f of the function on a random [k]d sub-hypergrid of the original domain. We show that for k = poly(d/ef), the expected distance of the restriction is E[ef] = Ω(ef). Previously such a result was only known for d = 1 (Berman-Raskhodnikova-Yaroslavtsev, STOC 2014). Our result for testing Boolean functions over [n]d then follows by applying the d5/6 · poly(1/e, log n, log d)-query hypergrid tester of Black-Chakrabarty-Seshadhri (SODA 2018). To obtain the result for testing Boolean functions over Rd, we use standard measure theoretic tools to reduce monotonicity testing of a measurable function f to monotonicity testing of a discretized version of f over a hypergrid domain [N]d for large, but finite, N (that may depend on f). The independence of N in the hypergrid tester is crucial to getting the final tester over Rd.
Institutional Logics and Technology Development: Evidence from the Wind and Solar Energy Industries

The relationship between regionally tied institutional logics and the location of organizations is an important issue in organization theory. Recent work highlights how supportive regional logics c...
Analysis and combinatorics of partition zeta functions

We examine “partition zeta functions” analogous to the Riemann zeta function but summed over subsets of integer partitions. We prove an explicit formula for a family of partition zeta functions alr...
Changes in ambient temperature are the prevailing cue in determining Brachypodium distachyon diurnal gene regulation

Plants are continuously exposed to diurnal fluctuations in light and temperature, and spontaneous changes in their physical or biotic environment. The circadian clock coordinates regulation of gene expression with a 24 h period, enabling the anticipation of these events. We used RNA sequencing to characterize the Brachypodium distachyon transcriptome under light and temperature cycles, as well as under constant conditions. Approximately 3% of the transcriptome was regulated by the circadian clock, a smaller proportion than reported in most other species. For most transcripts that were rhythmic under all conditions, including many known clock genes, the period of gene expression lengthened from 24 to 27 h in the absence of external cues. To functionally characterize the cyclic transcriptome in B. distachyon, we used Gene Ontology enrichment analysis, and found several terms significantly associated with peak expression at particular times of the day. Furthermore, we identified sequence motifs enriched in the promoters of similarly phased genes, some potentially associated with transcription factors. When considering the overlap in rhythmic gene expression and specific pathway behavior, thermocycles was the prevailing cue that controlled diurnal gene regulation. Taken together, our characterization of the rhythmic B. distachyon transcriptome represents a foundational resource with implications in other grass species.
P-Partitions and Quasisymmetric Power Sums

The $(P, \omega)$-partition generating function of a labeled poset $(P, \omega)$ is a quasisymmetric function enumerating certain order-preserving maps from $P$ to $\mathbb{Z}^+$. We study the expansion of this generating function in the recently introduced type 1 quasisymmetric power sum basis $\{\psi_\alpha\}$. Using this expansion, we show that connected, naturally labeled posets have irreducible $P$-partition generating functions. We also show that series-parallel posets are uniquely determined by their partition generating functions. We conclude by giving a combinatorial interpretation for the coefficients of the $\psi_\alpha$-expansion of the $(P, \omega)$-partition generating function akin to the Murnaghan-Nakayama rule.
LATTE: Application Oriented Social Network Embedding

In recent years, many research works propose to embed the network structured data into a low-dimensional feature space, where each node will be represented as a feature vector. However, due to the detachment of the embedding process with external tasks, the learned embedding results by most existing embedding models can be ineffective for application tasks with specific objectives, e.g., community detection, network alignment or information diffusion. In this paper, we propose to study the application oriented heterogeneous social network embedding problem. Significantly different from the existing works, besides the network structure preservation, the problem should also incorporate the objectives of external applications in the objective function. To resolve the problem, we propose a novel network embedding framework, namely “app$\underline{L} ic \underline{A}$tion orien$\underline{T} ed ne \underline{T}$work$\underline{E}$mbedding” (LATTE). In LATTE, the heterogeneous network structure can be applied to compute the node “diffusive proximity” scores, which capture both the local and global network structures. Based on these computed scores, LATTE learns the network representation feature vectors by extending the autoencoder model to the heterogeneous network scenario, which can also effectively unite the objectives of network embedding and external application tasks. Extensive experiments have been done on real-world heterogeneous social network datasets with community detection as an example task, and the experimental results have demonstrated the outstanding performance of LATTE. Experiental results on other tasks are provided in the full-version of this paper at [16].
Using text analytics to apprehend urban sustainability development

This research aims to specify critical urban sustainability issues by mining unstructured text data derived from the C40 city datasets of the Carbon Disclosure Project. The current study identifies underlying topical issues exhibited by text corpora, enables creation of smarter data visualizations, and forms useful profiles. Four underlying topical areas are examined: economic opportunities, climate risks, incentives to reduce greenhouse gas emissions, and emissions reduction activities. For each area, we built text data visualization profiles. Developing these text data visualization profiles enables greater attention to be paid to the list of topical issues shown in the profiles. Given the number of discovered topic issues, we generate an urban sustainability activity index and use it to identify which cities were detailing their actions toward becoming more sustainable cities. The city officials and municipal planners of either C40 or non-C40 cities worldwide can benchmark this study and put the process of text data visualization at the center of their process of generating citywide sustainable development.
Superfield Component Decompositions and the Scan for Prepotential Supermultiplets in 10D Superspaces

The first complete and explicit SO(1,9) Lorentz descriptions of all component fields contained in the $$ \mathcal{N} $$ = 1, $$ \mathcal{N} $$ = 2A, and $$ \mathcal{N} $$ = 2B unconstrained scalar 10D superfields are presented. These are made possible by a discovery of the dependence of the superfield component expansion on the branching rules of irreducible representations in one ordinary Lie algebra into one of its Lie subalgebras. Adinkra graphs for ten dimensional superspaces are defined for the first time, whose nodes depict spin bundle representations of SO(1,9). A consequential deliverable of this advance is it provides the first explicit, in terms of component fields, examples of all the off-shell 10D Nordstrom SG theories relevant to string theory, without off-shell central charges that are reducible but with finite numbers of fields. An analogue of Breitenlohner’s approach is implemented to scan for superfields that contain graviton(s) and gravitino(s), which are the candidates for the superconformal prepotential superfields of 10D off-shell supergravity theories and Yang-Mills theories.
An estimate on energy of min-max Seiberg-Witten Floer generators

Previously, Cristofaro-Gardiner, Hutchings and Ramos have proved that embedded contact homology (ECH) capacities can recover the volume of a contact 3-manifod in their paper "the asymptotics of ECH capacities" . There were two main steps to proving this theorem: The first step used an estimate for the energy of min-max Seiberg-Witten Floer generators. The second step used embedded balls in a certain symplectic four manifold. In this paper, stronger estimates on the energy of min-max Seiberg-Witten Floer generators are derived. This stronger estimate implies directly the "ECH capacities recover volume" theorem (without the help of embedded balls in a certain symplectic four manifold), and moreover, gives an estimate on its speed.
Ghostbusters: unitarity and causality of non-equilibrium effective field theories

Abstract: For a non-equilibrium physical system defined along a closed time path (CTP), a key constraint is the so-called largest time equation, which is a consequence of unitarity and implies causality. In this paper, we present a simple proof that if the propagators of a non-equilibrium effective action have the proper pole structure, the largest time equation is obeyed to all loop orders. Ghost fields and BRST symmetry are not needed. In particular, the arguments for the proof can also be used to show that if ghost fields are introduced, their contributions vanish.
Uncertainty quantification (UQ) as an archetype for research: Integrating UQ into undergraduate research education

This submission is for a Work In Progress paper in the Innovative Practice Category. This paper presents the results of a research study that examined the effects of teaching undergraduates about scientific research through the lens of Uncertainty Quantification (UQ) on their understanding of scientific research. UQ is a vibrant area of mathematical, scientific, and engineering research that can be studied in every discipline of scientific inquiry. Here, we present the initial findings of this program. We discuss the path forward for a broader implementation of UQ as a tool to engage undergraduates in scientific research, encourage them to pursue STEM careers. We also discuss the practical implications of understanding UQ in a broader societal context where research-based decision-making requires accounting for uncertainties.
Smart Jamming Attacks in 5G New Radio: A Review

The fifth generation of wireless cellular networks (5G) is expected to be the infrastructure for emergency services, natural disasters rescue, public safety, and military communications. 5G, as any previous wireless cellular network, is vulnerable to jamming attacks, which create deliberate interference to hinder the communication of legitimate users. Therefore, jamming 5G networks can be a real threat to public safety. Thus, there is a strong need to investigate to what extent these networks are vulnerable to jamming attacks. For this investigation, we consider the 3GPP standard released in 2017, which is widely accepted as the primary reference for the deployment of these networks. First, we describe the key elements of 5G New Radio (NR) architecture, such as different channels and signals exchanged between the base station and user equipment. Second, we conduct an in-depth review of the jamming attack models and we assess the 5G NR vulnerabilities to these jamming attacks. Then, we present the state-of-the-art detection and mitigation techniques, and we discuss their suitability to defeat smart jammers in 5G wireless networks. Finally, we provide some recommendations and future research directions at the end of this paper.
Associations of waking cortisol with DHEA and testosterone across the pubertal transition: Effects of threat-related early life stress.

Abstract Atypical regulation of the hypothalamic-pituitary-adrenal (HPA) axis is a putative mechanism underlying the association between exposure to early life stress (ELS) and the subsequent development of mental and physical health difficulties. Recent research indicates that puberty is a period of HPA-axis plasticity during which the effects of exposure to ELS on cortisol regulation may change. In particular, increases in the sex hormones that drive pubertal maturation, including dehydroepiandrosterone (DHEA) and testosterone, may be implicated in pubertal recalibration of cortisol regulation. In the current study, we examined the associations among levels of objectively-rated threat-related ELS and salivary waking cortisol, DHEA, and testosterone in a sample of 178 adolescents (55 % female) who were in early puberty at baseline (Tanner stages 1–3; mean Tanner stage[SD] = 1.93[0.64]; mean age[SD] = 11.42[1.04]) and were followed up approximately two years later (mean Tanner stage[SD] = 3.46[0.86]; mean age[SD] = 13.38[1.06]). Using multi-level modeling, we disaggregated the effects of between-individual levels and within-individual increases in pubertal stage and sex hormones on change in cortisol. Controlling for between-individual differences in average pubertal stage, the association between levels of cortisol and DHEA was more strongly positive among adolescents who evidenced greater within-individual increases in pubertal stage across time. Both higher average levels and greater within-individual increases in DHEA and testosterone were associated with increases in cortisol across time, indicating positive coupling of developmental changes in these hormones; however, coupling was attenuated in adolescents who were exposed to more severe threat-related ELS prior to puberty. These findings advance our understanding of the development of the HPA-axis and its association with childhood environmental risk during puberty.
Doubly Balanced Connected Graph Partitioning

We introduce and study the doubly balanced connected graph partitioning problem: Let G=(V, E) be a connected graph with a weight (supply/demand) function p : V → {−1, +1} satisfying p(V)=∑ jip(V1)m,mp(V2)m≤ cp, and max{ mV1 / V2m,mV2 / V1m} ≤ cs, for some constants cp and cs. When G is 2-connected, we show that a solution with cp=1 and cs=2 always exists and can be found in randomized polynomial time. Moreover, when G is 3-connected, we show that there is always a “perfect” solution (a partition with p(V1)=p(V2)=0 and mV1m=mV2m, if mVm≡ 0 (mod 4)), and it can be found in randomized polynomial time. Our techniques can be extended, with similar results, to the case in which the weights are arbitrary (not necessarily ±1), and to the case that p(V)≠ 0 and the excess supply/demand should be split evenly. They also apply to the problem of partitioning a graph with two types of nodes into two large connected subgraphs that preserve approximately the proportion of the two types.
The 2-Neutrino Exchange Potential with Mixing: A Probe of Neutrino Physics and CP Violation

The 2-neutrino exchange potential is a Standard Model weak potential arising from the exchange of virtual neutrino-antineutrino pairs which must include all neutrino properties, including the number of flavors, their masses, fermionic nature (Dirac or Majorana), and CP violation. We describe a new approach for calculating the spin-independent 2-neutrino exchange potential, including the mixing of three neutrino mass states and CP violation.
Using global observation protocols to inform research on teaching effectiveness and school improvement: Strengths and emerging limitations

An essential feature of many modern teacher observation protocols is their “global” approach to measuring instruction. Global protocols provide a summary evaluation of multiple domains of instruction from observers’ overall review of classroom processes. Although these protocols have demonstrated strengths, including their comprehensiveness and advanced state of development, in this analysis we argue that global protocols also have inherent limitations affecting both research use and applied school improvement efforts. Analyzing the Measures of Effective Teaching study data, we interrogate a set of five potential limitations of global protocols. We conclude by discussing fine-grained measures of instruction, including tools that rely on automated methods of observation, as an alternative with the potential to overcome many of the fundamental limitations of global protocols.
Benchmarking Black Hole Heat Engines, II

We extend to nonstatic black holes our benchmarking scheme that allows for cross–comparison of the efficiencies of asymptotically AdS black holes used as working substances in heat engines. We use a circular cycle in the p–V plane as the benchmark cycle. We study Kerr black holes in four spacetime dimensions as an example. As in the static case, we find an exact formula for the benchmark efficiency in an ideal gas-like limit, which may serve as an upper bound for rotating black hole heat engines in a thermodynamic ensemble with fixed angular velocity. We use the benchmarking scheme to compare Kerr to static black holes charged under Maxwell and Born–Infeld sectors.
Heterolytic Hydrogen Activation: Understanding Support Effects in Water-Gas Shift, Hydrodeoxygenation, and CO Oxidation Catalysis.

Identifying the role of oxide supports in transition metal catalysis is critical toward our understanding of heterogeneous catalysis. The water-gas shift (WGS) reaction is a prototypical example wh...
Observation of Electron Trapping in an Intense Laser Beam

High-energy electrons have been trapped in an intense, single-beam, ponderomotive-optical trap. Thomson-scattered light from the center of a tightly focused pulsed laser beam is enhanced when a novel trapping focus is used. The observed spatial distribution and energy dependence of the scattered light agree with the results of computer simulations for ordinary and trapping beams. (c) 1999 The American Physical Society.
Soil organic carbon in drylands: shrub encroachment and vegetation management effects dwarf those of livestock grazing

Dryland ecosystems occur worldwide and play a prominent, but potentially shifting, role in global biogeochemical cycling. Widespread woody plant proliferation, often associated with declines in palatable grasses, has jeopardized livestock production in drylands and prompted attempts to reduce woody cover by chemical or mechanical means. Woody encroachment also has the potential to significantly alter terrestrial carbon storage. However, little is known of the long-term biogeochemical consequences of woody encroachment in the broader context of its interaction with common dryland land uses, including "brush management" (woody plant clearing) and livestock grazing. Present assessments exhibit considerable variation in the consequences of these land use/land cover changes, with evidence that brush management may counteract sizeable impacts of shrub encroachment on soil biogeochemical pools. A challenge to assessing the net effects of brush management in shrub-encroached grasslands on soil organic carbon (SOC) and total nitrogen (N) pools is that land management practices are typically considered in isolation, when they are co-occurring phenomena. Furthermore, few studies have assessed spatial patterns in brush management and how these are affected in decades following treatment on sites with contrasting grazing histories. To address these uncertainties and interactions, we quantified the impacts of shrub encroachment and their subsequent mortality resulting from brush management (herbicide application) on SOC and N pools in a Sonoran Desert grassland where long-term grazing manipulations (>100 yr) co-occur with shrub encroachment and brush management. Pools of SOC and N associated with herbicided shrubs declined markedly over ~40 yr, offsetting 66% of the increases from shrub encroachment. However, spatial patterns in SOC induced by shrubs persisted over the decades following brush management. Century-long protection from grazing did little to change SOC and N pools. Accordingly, shrub encroachment and shrub mortality from brush management each far outweighed livestock grazing impacts. Consideration of the patterns of SOC and N through space (e.g., bole-to-dripline gradients), time (e.g., shrub age/size), land use (e.g., livestock grazing and brush management), and their interactions will position us to improve predictions of SOC and N responses to land use/land cover change, inform C-based management decisions, and objectively evaluate trade-offs with other ecosystem services.
Estimating the number of connected components in a graph via subgraph sampling

Learning properties of large graphs from samples has been an important problem in statistical network analysis since the early work of Goodman (Ann. Math. Stat. 20 (1949) 572–579) and Frank (Scand. J. Stat. 5 (1978) 177–188). We revisit a problem formulated by Frank (Scand. J. Stat. 5 (1978) 177–188) of estimating the number of connected components in a large graph based on the subgraph sampling model, in which we randomly sample a subset of the vertices and observe the induced subgraph. The key question is whether accurate estimation is achievable in the sublinear regime where only a vanishing fraction of the vertices are sampled. We show that it is impossible if the parent graph is allowed to contain high-degree vertices or long induced cycles. For the class of chordal graphs, where induced cycles of length four or above are forbidden, we characterize the optimal sample complexity within constant factors and construct linear-time estimators that provably achieve these bounds. This significantly expands the scope of previous results which have focused on unbiased estimators and special classes of graphs such as forests or cliques. Both the construction and the analysis of the proposed methodology rely on combinatorial properties of chordal graphs and identities of induced subgraph counts. They, in turn, also play a key role in proving minimax lower bounds based on construction of random instances of graphs with matching structures of small subgraphs.
Breakdown of Fourier’s Law in Nanotube Thermal Conductors

We present experimental evidence that the room temperature thermal conductivity (kappa) of individual multiwalled carbon and boron-nitride nanotubes does not obey Fourier's empirical law of thermal conduction. Because of isotopic disorder, kappa's of carbon nanotubes and boron-nitride nanotubes show different length dependence behavior. Moreover, for these systems we find that Fourier's law is violated even when the phonon mean free path is much shorter than the sample length.
Functional sarcoplasmic reticulum for calcium-handling of human embryonic stem cell-derived cardiomyocytes: Insights for driven maturation

Functional sarcoplasmic reticulum for calcium-handling of human embryonic stem cell-derived cardiomyocytes: Insights for driven maturation
Hopf Bifurcation in the presence of symmetry

Using group theoretic techniques, we obtain a generalization of the Hopf Bifurcation Theorem to differential equations with symmetry, analogous to a static bifurcation theorem of Cicogna. We discuss the stability of the bifurcating branches, and show how group theory can often simplify stability calculations. The general theory is illustrated by three detailed examples: O(2) acting on R2, O(n) on Rn, and O(3) in any irreducible representation on spherical harmonics.
CHAPTER 5 – Spectral Transforms

Publisher Summary This chapter discusses image processing techniques and algorithms in the physical context of remote sensing. The chapters also describes tools for spectral and spatial transforms that are useful in the correction and calibration of images for atmospheric and sensor effects. Spectral transformations alter the spectral space and spatial transformations alter the image space. Many of these transformed spaces are useful for thematic classification and are collectively called feature spaces in that context. A variety of spectral transformations are examined, ranging from nonlinear spectral band ratios to linear transformations of various types. Some are designed to improve quantitative analysis of remote-sensing images, while others simply enhance subtle information so that it is visible. The chapter concludes the following points: (1) spectral band ratios can help isolate spectral signatures from imagery by reducing topographic shading; (2) ratios involving near infrared (NIR) and red spectral bands are useful for vegetation measurements; (3) the principal components transform is optimal for data compression, but because it is data dependent, the resulting features have different interpretations for different images; (4) the tasseled-cap transform provides a fixed but sensor-specific transform that is based on soil and vegetation signatures; and (5) color–image composites can be enhanced for visual interpretation by a variety of spectral transforms, however, these transforms are not to be used for quantitative data analysis.
Amplification Mechanisms in Liquidity Crises

I describe two amplifications mechanisms that operate during crises and discuss the benefits of policy given each mechanism. The first mechanism involves asset prices and balance sheets. A negative shock to agents' balance sheets causes them to liquidate assets, lowering prices, further deteriorating balance sheets and amplifying the shock. The second mechanism involves investors' Knightian uncertainty. Unusual shocks to untested financial innovations increase agents' uncertainty about their investments, causing them to disengage from markets and amplifying the crisis. Liquidity provision by the central bank alleviates the crisis in both mechanisms. Ex ante policies such as liquidity/capital requirements may also be beneficial.
Phase Transitions in Spin Glasses

Some recent progress in Monte Carlo simulations of spin glasses will be presented. The problem of slow dynamics at low temperatures is partially alleviated by use of the parallel tempering (replica exchange) method. A useful technique to check for equilibration (applicable only for a Gaussian distribution) will be discussed. It will be argued that a finite size scaling analysis of the scaled correlation length of the system is a good approach with which to investigate phase transitions in spin glasses. This method will be used to study two questions: (i) whether there is a phase transition in zero field in the Heisenberg spin glass in three dimensions, and (ii) whether there is phase transition in a magnetic field in an Ising spin glass, also in three dimensions.
Newsvendor Decisions with Two-Sided Learning

A substantial collection of work in operations management considers settings where a firm faces uncertain demand that depends on parameters that are ex ante unknown but can be learned by observing ...
Pandemic Police States

The COVID-19 outbreak prompted governments around the world to employ a range of emergency methods to combat the pandemic In many countries these emergency measures relied heavily on police powers, which refer to the capacity of governments to forcefully regulate behavior and impose order as defined by those in control of the state apparatus Throughout the world police powers have been used to limit free association through government-imposed stay-at-home orders, impose social distancing rules, close non-essential businesses, and impose lockdowns State orders have been enforced through various forms of direct monitoring, indirect surveillance, and in some instances, violence We discuss the theoretical foundations of the troubling aspects of pandemic police states We then catalog some pandemic police state activities associated with the COVID-19 pandemic We conclude with the implications for peace studies
Flexible Formulation of Spatial Integration Constraints in Aerodynamic Shape Optimization

In aircraft design, spatial integration limits aerodynamic and structural performance. While the outer mold line shape determines aircraft aerodynamic characteristics, aircraft systems and passenge...
Improved two-stage protein expression and purification via autoinduction of both autolysis and auto DNA/RNA hydrolysis conferred by phage lysozyme and DNA/RNA endonuclease.

We report improved release of recombinant proteins in Escherichia coli, which relies on combined cellular autolysis and DNA/RNA autohydrolysis, conferred by the tightly controlled autoinduction of both phage lysozyme and the nonspecific DNA/RNA endonuclease from Serratia marcescens. Autoinduction occurs in a two-stage process wherein heterologous protein expression and autolysis enzymes are induced upon entry into stationary phase by phosphate depletion. Cytoplasmic lysozyme and periplasmic endonuclease are kept from inducing lysis until membrane integrity is disrupted. After cell harvest, the addition of detergent (0.1% Triton X-100) and a single 30 min freeze-thaw cycle results in >90% release of protein, green fluorescent protein. This cellular lysis is accompanied by complete oligonucleotide hydrolysis. The approach has been validated for shake flask cultures, high-throughput cultivation in microtiter plates, and larger scale stirred-tank bioreactors. This tightly controlled system enables robust growth and resistance to lysis in routine media when cells are propagated and autolysis/hydrolysis genes are only induced upon phosphate depletion.
Association of extended dosing intervals or delays in pembrolizumab-based regimens with survival outcomes in advanced non-small cell lung cancer

Abstract Background Besides modeling/simulation-based analysis, no post-approval studies have evaluated the optimal administration frequency of pembrolizumab in non–small-cell lung cancer (NSCLC). Patients and Methods We performed a multicenter retrospective cohort study to evaluate the association between survival outcomes and treatment extensions/delays of pembrolizumab-based regimens in patients with advanced NSCLC. Those who had received at least 4 cycles in routine practice were divided into 2 groups: nonstandard (Non-Std, ≥ 2 cycles at intervals > 3 weeks + 3 days) and standard (Std, all cycles every 3 weeks or 1 cycle > 3 weeks + 3 days). Results Among 150 patients, 92 (61%) were eligible for the study (Non-Std, 27; Std, 65). The reasons for patients with extensions/delays in the Non-Std group included: immune-related adverse events (irAEs) (33%), non–irAE-related medical issues (26%), and patient-physician preference (41%). The Non-Std group was more likely to have a higher programmed death-ligand 1 tumor proportion score, a higher number of treatment cycles, and pembrolizumab monotherapy. Univariate and 6-month landmark analyses showed longer median overall survival and progression-free survival in the Non-Std group compared with the Std group. After multivariable adjustment for confounding factors, there was no significant difference in overall survival (hazard ratio, 1.2; 95% confidence interval, 0.3-4.8; P = .824) or progression-free survival (hazard ratio, 2.6; 95% confidence interval, 0.7-9.6; P = .157) between the 2 groups. Conclusion Our study shows that a significant proportion of patients with advanced NSCLC receive pembrolizumab-based regimens with extended intervals or delays in routine clinical practice and with similar outcomes to those receiving treatment at label-specified 3-week intervals. Given the durability of benefit seen and the potential for cost reduction and decreased infusion frequency in these patients, this requires validation in prospective trials.
How media coverage of corporate social responsibility and irresponsibility influences cross‐border acquisitions

Research Summary This study contributes to the growing strategic corporate social responsibility (CSR) literature by examining the intersection of acquisition studies and international expansion research and highlighting the unexplored impact of media coverage of CSR and corporate social irresponsibility (CSI) in shaping completion and duration outcomes of cross‐border acquisitions. A quantitative analysis of 4,087 cross‐border acquisition announcements by firms from Brazil, Russia, India, China, and South Africa (1990–2011) shows that while media coverage of CSR is not important, media coverage of CSI is associated with lower likelihood of and longer duration till acquisition completion. By theoretically and empirically distinguishing media coverage of CSR from CSI, this paper pushes the existing literature to acknowledge these distinct concepts and their varying effects. In sum, managers should beware media coverage of CSI when acquiring abroad. Managerial Summary Cross‐border acquisitions by firms from emerging markets often do not reach completion or are badly delayed, damaging the firms' attempts to expand. A key barrier to completing deals is that employees, customers, regulators, media, and other stakeholders in the target market are suspicious of these firms, fearing that they will be poor corporate citizens. I examine whether media coverage of acquirers' social activities helps overcome these suspicions. I find that media coverage of socially responsible activities does not facilitate deal completion. Strikingly, however, media coverage of irresponsible actions, such as labor or environmental issues, delays or blocks deal completion. The implication is that firms from emerging markets, which increasingly are expanding abroad, need to avoid activities that people outside their country will interpret as inappropriate.
Greedy coordinate descent method on non-negative quadratic programming

The coordinate descent (CD) method has recently become popular for solving very large-scale problems, partly due to its simple update, low memory requirement, and fast convergence. In this paper, we explore the greedy CD on solving non-negative quadratic programming (NQP). The greedy CD generally has much more expensive per-update complexity than its cyclic and randomized counterparts. However, on the NQP, these three CDs have almost the same per-update cost, while the greedy CD can have significantly faster overall convergence speed. We also apply the proposed greedy CD as a subroutine to solve linearly constrained NQP and the non-negative matrix factorization. Promising numerical results on both problems are observed on instances with synthetic data and also image data.
"The Squawk Bot": Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering.

Multimodal analysis that uses numerical time series and textual corpora as input data sources is becoming a promising approach, especially in the financial industry. However, the main focus of such analysis has been on achieving high prediction accuracy while little effort has been spent on the important task of understanding the association between the two data modalities. Performance on the time series hence receives little explanation though human-understandable textual information is available. In this work, we address the problem of given a numerical time series, and a general corpus of textual stories collected in the same period of the time series, the task is to timely discover a succinct set of textual stories associated with that time series. Towards this goal, we propose a novel multi-modal neural model called MSIN that jointly learns both numerical time series and categorical text articles in order to unearth the association between them. Through multiple steps of data interrelation between the two data modalities, MSIN learns to focus on a small subset of text articles that best align with the performance in the time series. This succinct set is timely discovered and presented as recommended documents, acting as automated information filtering, for the given time series. We empirically evaluate the performance of our model on discovering relevant news articles for two stock time series from Apple and Google companies, along with the daily news articles collected from the Thomson Reuters over a period of seven consecutive years. The experimental results demonstrate that MSIN achieves up to 84.9% and 87.2% in recalling the ground truth articles respectively to the two examined time series, far more superior to state-of-the-art algorithms that rely on conventional attention mechanism in deep learning.
Exploration with limited memory: streaming algorithms for coin tossing, noisy comparisons, and multi-armed bandits

Consider the following abstract coin tossing problem: Given a set of n coins with unknown biases, find the most biased coin using a minimal number of coin tosses. This is a common abstraction of various exploration problems in theoretical computer science and machine learning and has been studied extensively over the years. In particular, algorithms with optimal sample complexity (number of coin tosses) have been known for this problem for quite some time. Motivated by applications to processing massive datasets, we study the space complexity of solving this problem with optimal number of coin tosses in the streaming model. In this model, the coins are arriving one by one and the algorithm is only allowed to store a limited number of coins at any point – any coin not present in the memory is lost and can no longer be tossed or compared to arriving coins. Prior algorithms for the coin tossing problem with optimal sample complexity are based on iterative elimination of coins which inherently require storing all the coins, leading to memory-inefficient streaming algorithms. We remedy this state-of-affairs by presenting a series of improved streaming algorithms for this problem: we start with a simple algorithm which require storing only O(logn) coins and then iteratively refine it further and further, leading to algorithms with O(loglog(n)) memory, O((n)) memory, and finally a one that only stores a single extra coin in memory – the same exact space needed to just store the best coin throughout the stream. Furthermore, we extend our algorithms to the problem of finding the k most biased coins as well as other exploration problems such as finding top-k elements using noisy comparisons or finding an -best arm in stochastic multi-armed bandits, and obtain efficient streaming algorithms for these problems.
Manipulation Detection in Satellite Images Using Deep Belief Networks.

Satellite images are more accessible with the increase of commercial satellites being orbited. These images are used in a wide range of applications including agricultural management, meteorological prediction, damage assessment from natural disasters and cartography. Image manipulation tools including both manual editing tools and automated techniques can be easily used to tamper and modify satellite imagery. One type of manipulation that we examine in this paper is the splice attack where a region from one image (or the same image) is inserted ("spliced") into an image. In this paper, we present a one-class detection method based on deep belief networks (DBN) for splicing detection and localization without using any prior knowledge of the manipulations. We evaluate the performance of our approach and show that it provides good detection and localization accuracies in small forgeries compared to other approaches.
Comparative Statics in Markets for Indivisible Goods

Abstract This paper builds upon Caplin and Leahy (2014), which introduced a new mathematical apparatus for understanding allocation markets with nontransferable utility, as such covering the housing market and other markets for large indivisible goods. In the current paper we complete the study of comparative statics initiated therein. We introduce homotopy methods to characterize how equilibrium changes in response to arbitrary parameter changes. Generically, we show that there can be five and only five qualitatively distinct forms of market transition: Graft; Prune and Plant; Prune and Graft; Cycle and Reverse; and Shift and Replant. Our path-following methods identify new algorithms for computing market equilibria.
Interphase boundary segregation and precipitate coarsening resistance in ternary alloys: An analytic phase-field model describing chemical effects

Abstract Many experimental and first principles studies on precipitation hardening alloys show that segregation of elemental species to the matrix-precipitate interphase boundary (IB) reduces the boundary’s energy. This segregation mechanism can thermally stabilize the microstructure against precipitate coarsening processes and allow for higher operating temperatures in structural applications. In this paper, we develop a phase-field modeling framework to describe IB solute segregation in ternary alloys. The interfacial thermodynamics is effectively described by defining an IB phase with a characteristic free energy-concentration dependence. Equilibrium for the IB phase is established via the parallel tangent plane construction, analogous to classical treatments for segregation to free surfaces and grain boundaries. Analytic steady-steady solutions elucidating the dependence of IB properties on bulk phase composition, temperature and model parameters are derived for a one-dimensional system. Analytic relations for the classical thermodynamic quantities–IB energy and relative solute excess–are derived and the Gibbs adsorption equation is shown to hold; therefore, predictions of the model can be compared with experiments and atomistic simulations. An application of the model is demonstrated for Zn segregation to Mg/Mg2Sn using representative IB parameters. A two-particle coarsening simulation of IB segregation is performed: the result demonstrates enhanced coarsening resistance of the ternary alloy relative to the binary alloy.
Political corruption and mergers and acquisitions

Abstract This research examines the relation between political corruption and mergers and acquisitions (M&As). We find that local corruption increases firm acquisitiveness but decreases firm targetiveness. The levels of corruption in acquirer areas relate positively to the bid premiums and negatively to the likelihood of deal completion. Corruption motivates acquiring firms to use excess cash for payment, which mitigates the negative effect of corruption on acquirer shareholder value. The evidence indicates that acquisitions help acquiring firms convert cash into hard-to-extract assets and relocate assets from the high to low corruption areas, thereby shielding their liquid assets from expropriation by local officials.
Her9/Hes4 is required for retinal photoreceptor development, maintenance, and survival.

The intrinsic and extrinsic factors that regulate vertebrate photoreceptor specification and differentiation are complex, and our understanding of all the players is far from complete. Her9, the zebrafish ortholog of human HES4, is a basic helix-loop-helix-orange transcriptional repressor that regulates neurogenesis in several developmental contexts. We have previously shown that her9 is upregulated during chronic rod photoreceptor degeneration and regeneration in adult zebrafish, but little is known about the role of her9 during retinal development. To better understand the function of Her9 in the retina, we generated zebrafish her9 CRISPR mutants. Her9 homozygous mutants displayed striking retinal phenotypes, including decreased numbers of rods and red/green cones, whereas blue and UV cones were relatively unaffected. The reduction in rods and red/green cones correlated with defects in photoreceptor subtype lineage specification. The remaining rods and double cones displayed abnormal outer segments, and elevated levels of apoptosis. In addition to the photoreceptor defects, her9 mutants also possessed a reduced proliferative ciliary marginal zone, and decreased and disorganized Muller glia. Mutation of her9 was larval lethal, with no mutants surviving past 13 days post fertilization. Our results reveal a previously undescribed role for Her9/Hes4 in photoreceptor differentiation, maintenance, and survival.
Patterns of adolescent gun carrying and gun-related crime arrests in Indianapolis, Indiana over an 11-year time period.

Abstract Adolescent males are disproportionately affected by homicide as both victims and offenders. Indianapolis has seen increases in youth homicides over the past few years; gun carrying increases an individual's risk for involvement in firearm violence. It is unclear how often youth are arrested for gun carrying and gun-related crimes. Examining these patterns may identify an opportunity for intervention. This study is a descriptive epidemiology analysis that examines patterns of gun carrying and gun-related crime arrests among justice involved youth in Marion County (Indianapolis), Indiana. We accessed juvenile court records from January 1, 2006 to December 31, 2016 on all individuals arrested for a gun carrying offense (i.e., illegal possession of a firearm or gun; n = 711) and all individuals arrested for a gun-related crime (i.e., homicide, robbery, aggravated assault; n = 150). Data were analyzed in fall 2019. Proportions of juvenile arrests for both gun carrying (47.0 per 1000 arrests) and gun-related crime (25.4 per 1000 arrests) have substantially increased compared to ten-years ago (4.5 per 1000 arrests and 2.0 per 1000 arrests, respectively). Of those arrested, 27.7 per 100,000 population were arrested for a repeated gun-related offense; of which 21.5 per 100,000 were first arrested for gun carrying and 6.2 per 100,000 were arrested for a gun-related crime. The majority of gun-related repeat offenders were first arrested for gun carrying; therefore, these gun-carrying arrests may be an opportunity to intervene on an individual level by providing treatment, other needed resources, and discussing safe firearm storage with families and communities.
Large deflections of a structurally damped panel in a subsonic flow

The large deflections of panels in subsonic flow are considered, specifically a fully clamped von Karman plate accounting for both rotational inertia in plate filaments and (mild) structural damping. The panel is taken to be embedded in the boundary of the positive half-space in $$\mathbb R^3$$ containing a linear, subsonic potential flow. Solutions are constructed via a semigroup approach despite the lack of natural dissipativity associated with the generator of the linear dynamics. The flow–plate dynamics are then reduced—via an explicit Neumann-to-Dirichlet (downwash-to-pressure) solver for the flow—to a memory-type dynamical system for the plate. For the non-conservative plate dynamics, a global attractor is explicitly constructed via Lyapunov and recent quasi-stability methods. Finally, it is shown that, via the compactness of the attractor and finiteness of the dissipation integral, all trajectories converge strongly to the set of stationary states.
Practical quantum computation of chemical and nuclear energy levels using quantum imaginary time evolution and Lanczos algorithms

Various methods have been developed for the quantum computation of the ground and excited states of physical and chemical systems, but many of them require either large numbers of ancilla qubits or high-dimensional optimization in the presence of noise. The quantum imaginary-time evolution (QITE) and quantum Lanczos (QLanczos) methods proposed in Motta et al. (2020) eschew the aforementioned issues. In this study, we demonstrate the practical application of these algorithms to challenging quantum computations of relevance for chemistry and nuclear physics, using the deuteron-binding energy and molecular hydrogen binding and excited state energies as examples. With the correct choice of initial and final states, we show that the number of timesteps in QITE and QLanczos can be reduced significantly, which commensurately simplifies the required quantum circuit and improves compatibility with NISQ devices. We have performed these calculations on cloud-accessible IBM Q quantum computers. With the application of readout-error mitigation and Richardson error extrapolation, we have obtained ground and excited state energies that agree well with exact results obtained from diagonalization.