cssi/SciSciGPT-SciSciNet huggingface dataset:
Explaining bond returns in heterogeneous agent models: The importance of higher-order moments

Abstract This paper examines the higher-order moments and nonlinear dynamic properties of discount bond returns in an equilibrium heterogeneous agent economy with incomplete markets and borrowing constraints. We find that while it is possible for the economic model to match the mean and variance of the observed bond returns by choosing the parameters such that the borrowing constraint is binding sufficiently often, the implied higher-order moments are at odds with the data. To match the higher-order moments, one needs a model in which the borrowing constraint is binding at times but not too often. In this case, one does not match the first two moments. Using the seminonparametric density estimation and the nonlinear impulse response analysis, we find that our economic model can mimic the asymmetric effect of return shocks on conditional volatility as documented for the real bond returns. However, the economic model has difficulty replicating the dynamic properties observed in the data when the parameter values are chosen to match the first two moments of the observed bond returns.
The Impact of Technology on the Labor Procurement Process

We construct a mathematical model to explore why digitization of employee recruiting process so far has not resulted in employers reporting hiring better candidates faster. We model multidimensional impact of Internet technology with increases in the total number of applications, in the rate at which applications arrive, and in departure rates of applicants. We also assume that technology leads to a stochastic decrease in the quality of the applicants. We then model a firm's recruiting process and investigate analytically and numerically the expected outcome. We show that the decrease in quality can be the dominant effect resulting in poorer outcome.
Choosing between Centralized and Decentralized Models of Tax Administration

The fundamental questions addressed in this article are the following: what is the most appropriate approach to organizing the vertical structure of tax administration, and what are the determinant factors that may make an approach more or less optimal in any particular country? Both centralized and multi-level tax administration have certain advantages and disadvantages. However, given the general approach to fiscal decentralization in a country and, more in particular, assignment of taxes and other revenue sources to different levels of government, it is possible to identify better and worse approaches to organizing tax administration.
Full Sp[]Ed Ahead: Expanding the IDEA Idea to Let all Students Ride the Same Bus

Some commentators and public officials have suggested that the schoolhouse "door to special education services has opened too widely and too indiscriminately..." under the Individuals with Disabilities Act (IDEA). In her Article responding to calls to shrink the eligibility definition, Professor Wendy Hensel alludes to "The Short Bus" that students with disabilities often ride. Meanwhile, No Child Left Behind (NCLB) — the most significant federal education policy reform in place for "general education" students — dictates a level of academic progress and instructional interventions to assist all pupils — those with disabilities along with other marginalized students. In this Essay, I call for an end to the line drawing and hoop jumping. Like Professor Hensel, I believe the public policy focus should not be on the breadth or narrowness of the definition of disability. I also share her belief that educators and policymakers must continue to grapple with the extent of services, if for no other reason than the spiraling cost. However, in moving toward an educational system that is more inclusive in the implementation of IDEA's "least restrictive environment" principle — and the success-for-all mandate of NCLB — we should end the divide between disabled students and their nondisabled peers who also require intensive academic or other educational supports. We must evaluate the remedial needs of a broader group of students — those situated outside the traditional and legal disability circle — and craft individualized programs for them as well. Moreover, I argue that we should strengthen another important factor that is key to the success of students with disabilities: adequate preparation of teachers and other professional staff. Finally, the right to monitor children's programs and progress that is now available to parents of disabled youth should be extended to parents of other students in need.
The performance of stocks that are reverse split

An unusually high number of Nasdaq National Market stocks were reverse split following the decline in Nasdaq prices in the year 2000. We test whether these splits were driven by the overall market decline. We find that the performance of stocks with reverse splits in poor overall stock market conditions is better (less negative) than that in good market conditions, and that the differences in performance appear three to five months after the split. This suggests that the longer-term outcomes of reverse stock splits are associated with the market environment at the time of the split. In view of this, changes that Nasdaq made to relax some of its listing standards are well justified.
The Paths to Legal Equality: A Reply to Dean Sullivan

In her characteristically insightful and incisive paper, Dean Sullivan orients debates about how to constitutionalize equality of the sexes along five axes: (1) general versus specific; (2) symmetrical versus asymmetrical; (3) applicable only to public entities versus applicable to private ones as well; (4) negative versus positive; and (5) judicially enforceable versus hortatory norms. She notes that "American constitutional law operates under strong conventions" preferring the first of each pair of dichotomies, whereas international documents such as the Convention on the Elimination of all forms of Discrimination Against Women ("CEDAW") as well as the constitutions of many other democracies do not.' With one exception, to which I shall return momentarily, there is a mutually enforcing internal coherence to this pattern. Dichotomies two, three, and four present a choice between formal, or thin, equality and a more substantive, or thick, equality.2 Constitutions with thick conceptions of equality place strong affirmative obligations on the government, thereby taxing the institutional capabilities of courts. This pressure can lead courts to interpret those obligations as hortatory or at least nonjusticiable.3
Land Allocation in Vietnam's Agrarian Transition

While liberalizing key factor markets is a crucial step in the transition from a socialist control-economy to a market economy, the process can be stalled by imperfect information, high transaction costs, and covert resistance from entrenched interests. The authors study land-market adjustment in the wake of Vietnam's reforms aiming to establish a free market in land-use rights following de-collectivization. Inefficiencies in the initial administrative allocation are measured against an explicit counterfactual market solution. The authors' tests using a farm-household panel data set spanning the reforms suggest that land allocation responded positively but slowly to the inefficiencies of the administrative allocation. They find no sign that the transition favored the land rich or that it was thwarted by the continuing power over land held by local officials.
Prices, output, and hours: An empirical analysis based on a sticky price model

Abstract I show that a simple sticky price model based on Rotemberg (1982) is consistent with a variety of facts concerning the correlation of prices, hours, and output. It is consistent with the negative correlation between forecastable movements in prices and output as well as the smaller negative correlation between forecastable movements in prices and hours. It is also consistent with the positive correlations of unexpected movements in prices, output, and hours. These patterns are harder to reconcile with the flexible price version of the model. In particular, they require that money respond differently to forecastable and to unforecastable real shocks.
Principal Component Analysis of High-Frequency Data

We develop the necessary methodology to conduct principal component analysis at high frequency. We construct estimators of realized eigenvalues, eigenvectors, and principal components, and provide ...
The Regulation of Armed Non-State Actors: Promoting the Application of the Laws of War to Conflicts Involving National Liberation Movements

The regulation of armed non-state actors is a challenge to the state-centric international law paradigm. The vast majority of international legal instruments which impact the regulation of armed actors are open to ratification by states only. This leads to the unfortunate situation in which armed nonstate actors often fall outside the remit of international law and their use of force and, indeed, the use of force against them, is left unregulated, which can only be to the detriment of combatants and civilians alike. However, there is an emerging trend, led by the International Committee of the Red Cross (ICRC) and non-governmental organizations (NGOs) such as Geneva Call, to accommodate non-state actors under the international humanitarian law (IHL) framework. This article seeks to investigate how non-state actors, specifically national liberation movements, are and could be regulated by IHL. It seeks to give an overview of the relevant legal provisions and illustrates the difficulties faced by national liberation movements if they do wish to accede to IHL instruments and apply IHL in their conflicts. As it is the aim of IHL to protect both combatants and civilians in armed conflicts, it is important that this body of law is practically applied and implemented in all conflict situations to the greatest extent possible. However, in the past, national liberation movements have encountered difficulties when seeking to apply IHL to their conflicts due to the nature of the legal framework and, indeed, the nature of international law itself. International law, the body of law that governs states in their relationships with one another, generally struggles to accommodate non-state actors. The international legal instruments dealing with the laws of war, namely the Geneva Conventions of 1949,1 the Hague Regulations of 1907,2 and more modern international conventions seeking to regulate weapons such as the Ottawa Treaty of 1997 banning landmines,3 were all drafted by states with the regulation of states in mind. These instruments almost exclusively limit ratification to states and do not allow for the accession of non-states. This means that non-state actors, including national liberation movements, face many difficulties when seeking to be bound by and apply IHL provisions in their conflicts, thus limiting the protection available to those fighting and caught up in these conflicts. However, non-state actors are active in various theatres of war and it is therefore vital that a realistic IHL framework that accommodates non-state actors be formulated.
Stepping stones: Principal career paths and school outcomes

More than one out of every five principals leaves their school each year. In some cases, these career changes are driven by the choices of district leadership. In other cases, principals initiate the move, often demonstrating preferences to work in schools with higher achieving students from more advantaged socioeconomic backgrounds. Principals often use schools with many poor or low-achieving students as stepping stones to what they view as more desirable assignments. We use longitudinal data from one large urban school district to study the relationship between principal turnover and school outcomes. We find that principal turnover is, on average, detrimental to school performance. Frequent turnover of school leadership results in lower teacher retention and lower student achievement gains. Leadership changes are particularly harmful for high poverty schools, low-achieving schools, and schools with many inexperienced teachers. These schools not only suffer from high rates of principal turnover but are also unable to attract experienced successors. The negative effect of leadership changes can be mitigated when vacancies are filled by individuals with prior experience leading other schools. However, the majority of new principals in high poverty and low-performing schools lack prior leadership experience and leave when more attractive positions become available in other schools.
Social networks and unraveling in labor markets

Abstract This paper studies the phenomenon of early hiring in entry-level labor markets affected by social networks. We offer a model in which information is revealed over time. At first, workers have noisy information about their own ability. The early information is ‘soft’ and non-verifiable, and workers can convey the information credibly only to firms that are connected to them. Later on, ‘hard’ accurate verifiable information becomes available. We characterize the effects of changes to the network structure on the unraveling of the market towards early hiring. Moreover, we show that an efficient design of the matching procedure can prevent unraveling.
The Effect of Supermajority Vote Requirements for Tax Increase in California: A Synthetic Control Method Approach

My article examines whether supermajority vote requirements (SMVR) to raise taxes in California’s constitution suppresses state tax burdens. SMVR is a politically popular but contentious measure that 16 states have adopted and many other states have attempted to adopt. The rationale behind the rule is to contain the growth of government by making it costly to form a winning coalition to raise taxes. Nonetheless, the current empirical literature is mixed at best and suffers from causal inference. I take a different approach from extant literature and estimate the causal effect of SMVR on tax burdens in California by using synthetic control methods. The results show that, from 1979 to 2008, SMVR reduced the state nonproperty tax burden by an average of $1.44 per $100 of personal income, which is equivalent to 21% of the total tax burden for each year. The effect of SMVR was immediate after its adoption, but has abated over time.
Steady state versus pulsed tokamak reactors

We have carried out a detailed analysis that compares steady state versus pulsed tokamak reactors. The motivations are as follows. Steady state current drive has turned out to be more difficult than expected - it takes too many watts to drive an Ampere, which has a negative effect on power balance and economics. This is partially compensated by the recent development of high temperature REBCO superconductors, which offers the promise of more compact, lower cost tokamak reactors, both steady state and pulsed. Of renewed interest is the reduction in size of pulsed reactors because of the possibility of higher field OH transformers for a given required pulse size. Our main conclusion is that pulsed reactors may indeed be competitive with steady state reactors and this issue should be re-examined with more detailed engineering level studies.
CorDEL: A Contrastive Deep Learning Approach for Entity Linkage

Entity linkage (EL) is a critical problem in data cleaning and integration. In the past several decades, EL has typically been done by rule-based systems or traditional machine learning models with hand-curated features, both of which heavily depend on manual human inputs. With the ever-increasing growth of new data, deep learning (DL) based approaches have been proposed to alleviate the high cost of EL associated with the traditional models. Existing exploration of DL models for EL strictly follows the well-known twin-network architecture. However, we argue that the twin-network architecture is sub-optimal to EL, leading to inherent drawbacks of existing models. In order to address the drawbacks, we propose a novel and generic contrastive DL framework for EL. The proposed framework is able to capture both syntactic and semantic matching signals and pays attention to subtle but critical differences. Based on the framework, we develop a contrastive DL approach for EL, CorDEL, with a simple yet powerful variant called CorDEL-Sum. We evaluate CorDEL with extensive experiments conducted on both public benchmark datasets and a real-world dataset. CorDEL outperforms previous state-of-the-art models by 5.2% on public benchmark datasets. Moreover, CorDEL yields a 29.4% improvement over the current best DL model on the real-world dataset, while reducing the number of training parameters by 96.8%.
Rapid Mixing of Glauber Dynamics up to Uniqueness via Contraction

For general antiferromagnetic 2-spin systems, including the hardcore model on weighted independent sets and the antiferromagnetic Ising model, there is an FPTAS for the partition function on graphs of maximum degree $\Delta$ when the infinite regular tree lies in the uniqueness region by Li et al. (2013). Moreover, in the tree non-uniqueness region, Sly (2010) showed that there is no FPRAS to estimate the partition function unless $\text{NP}=\text{RP}$ . The algorithmic results follow from the correlation decay approach due to Weitz (2006) or the polynomial interpolation approach developed by Barvinok (2016). However the running time is only polynomial for constant $\Delta$ . For the hardcore model, recent work of Anari et al. (2020) establishes rapid mixing of the simple single-site Markov chain known as the Glauber dynamics in the tree uniqueness region. Our work simplifies their analysis of the Glauber dynamics by considering the total pairwise influence of a fixed vertex $v$ on other vertices, as opposed to the total influence of other vertices on $v$ , thereby extending their work to all 2-spin models and improving the mixing time. More importantly our proof ties together the three disparate algorithmic approaches: we show that contraction of the so-called tree recursions with a suitable potential function, which is the primary technique for establishing efficiency of Weitz's correlation decay approach and Barvinok's polynomial interpolation approach, also establishes rapid mixing of the Glauber dynamics. We emphasize that this connection holds for all 2-spin models (both antiferromagnetic and ferromagnetic), and existing proofs for the correlation decay or polynomial interpolation approach immediately imply rapid mixing of the Glauber dynamics. Our proof utilizes that the graph partition function is a divisor of the partition function for Weitz's self-avoiding walk tree. This fact leads to new tools for the analysis of the influence of vertices, and may be of independent interest for the study of complex zeros.
Thermodynamic stability of hnRNP A1 low complexity domain revealed by high-pressure NMR.

We have investigated the pressure- and temperature-induced conformational changes associated with the low complexity domain of hnRNP A1, an RNA-binding protein able to phase separate in response to cellular stress. Solution NMR spectra of the hnRNP A1 low-complexity domain fused with protein-G B1 domain were collected from 1 to 2500 bar and from 268 to 290 K. While the GB1 domain shows the typical pressure-induced and cold temperature-induced unfolding expected for small globular domains, the low-complexity domain of hnRNP A1 exhibits unusual pressure and temperature dependences. We observed that the low-complexity domain is pressure sensitive, undergoing a major conformational transition within the prescribed pressure range. Remarkably, this transition has the inverse temperature dependence of a typical folding-unfolding transition. Our results suggest the presence of a low-lying extended and fully solvated state(s) of the low-complexity domain that may play a role in phase separation. This study highlights the exquisite sensitivity of solution NMR spectroscopy to observe subtle conformational changes and illustrates how pressure perturbation can be used to determine the properties of metastable conformational ensembles.
Global Transcriptional Response of Methylorubrum extorquens to Formaldehyde Stress Expands the Role of EfgA and Is Distinct from Antibiotic Translational Inhibition

The potency and indiscriminate nature of formaldehyde reactivity upon biological molecules make it a universal stressor. However, some organisms such as Methylorubrum extorquens possess means to rapidly and effectively mitigate formaldehyde-induced damage. EfgA is a recently identified formaldehyde sensor predicted to halt translation in response to elevated formaldehyde as a means to protect cells. Herein, we investigate growth and changes in gene expression to understand how M. extorquens responds to formaldehyde with and without the EfgA-formaldehyde-mediated translational response, and how this mechanism compares to antibiotic-mediated translation inhibition. These distinct mechanisms of translation inhibition have notable differences: they each involve different specific players and in addition, formaldehyde also acts as a general, multi-target stressor and a potential carbon source. We present findings demonstrating that in addition to its characterized impact on translation, functional EfgA allows for a rapid and robust transcriptional response to formaldehyde and that removal of EfgA leads to heightened proteotoxic and genotoxic stress in the presence of increased formaldehyde levels. We also found that many downstream consequences of translation inhibition were shared by EfgA-formaldehyde- and kanamycin-mediated translation inhibition. Our work uncovered additional layers of regulatory control enacted by functional EfgA upon experiencing formaldehyde stress, and further demonstrated the importance this protein plays at both transcriptional and translational levels in this model methylotroph.
A RECONSIDERATION OF THE DOCTRINAL FOUNDATIONS OF MONETARY POLICY RULES: FISHER VERSUS CHICAGO

There has long been a presumption that the price-level stabilization frameworks of Irving Fisher and Chicagoans Henry Simons and Lloyd Mints were essentially equivalent. I show that there were subtle, but important, differences in the rationales underlying the policies of Fisher and the Chicagoans. Fisher’s framework involved substantial discretion in the setting of the policy instruments; for the Chicagoans the objective of a policy rule was to tie the hands of the authorities in order to reduce discretion and, thus, monetary policy uncertainty. In contrast to Fisher, the Chicagoans provided assessments of the workings of alternative rules, assessed various criteria—including simplicity and reduction of political pressures—in the specification of rules, and concluded that rules would provide superior performance compared with discretion. Each of these characteristics provided a direct link to the rules-based framework of Milton Friedman. Like Friedman’s framework, Simons’s preferred rule targeted a policy instrument.
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits

Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users’ preferences over a high-dimensional gait parameter space. However, existing preference-based learning methods have only explored low-dimensional domains due to computational limitations. To learn user preferences in high dimensions, this work presents LINECOSPAR, a human-in-the-loop preference-based framework that enables optimization over many parameters by iteratively exploring one-dimensional subspaces. Additionally, this work identifies gait attributes that characterize broader preferences across users. In simulations and human trials, we empirically verify that LINECOSPAR is a sample-efficient approach for high-dimensional preference optimization. Our analysis of the experimental data reveals a correspondence between human preferences and objective measures of dynamicity, while also highlighting differences in the utility functions underlying individual users’ gait preferences. This result has implications for exoskeleton gait synthesis, an active field with applications to clinical use and patient rehabilitation.
On Nonconvex Optimization for Machine Learning: Gradients, Stochasticity, and Saddle Points

Gradient descent (GD) and stochastic gradient descent (SGD) are the workhorses of large-scale machine learning. While classical theory focused on analyzing the performance of these methods in convex optimization problems, the most notable successes in machine learning have involved nonconvex optimization, and a gap has arisen between theory and practice. Indeed, traditional analyses of GD and SGD show that both algorithms converge to stationary points efficiently. But these analyses do not take into account the possibility of converging to saddle points. More recent theory has shown that GD and SGD can avoid saddle points, but the dependence on dimension in these analyses is polynomial. For modern machine learning, where the dimension can be in the millions, such dependence would be catastrophic. We analyze perturbed versions of GD and SGD and show that they are truly efficient—their dimension dependence is only polylogarithmic. Indeed, these algorithms converge to second-order stationary points in essentially the same time as they take to converge to classical first-order stationary points.
A Semicircle Law for Derivatives of Random Polynomials

Let $x_1, \dots, x_n$ be $n$ independent and identically distributed random variables with mean zero, unit variance, and finite moments of all remaining orders. We study the random polynomial $p_n$ having roots at $x_1, \dots, x_n$. We prove that for $\ell \in \mathbb{N}$ fixed as $n \rightarrow \infty$, the $(n-\ell)-$th derivative of $p_n^{}$ behaves like a Hermite polynomial: for $x$ in a compact interval,$${n^{\ell/2}} \frac{\ell!}{n!} \cdot p_n^{(n-\ell)}\left( \frac{x}{\sqrt{n}}\right) \rightarrow He_{\ell}(x + \gamma_n),$$ where $He_{\ell}$ is the $\ell-$th probabilists' Hermite polynomial and $\gamma_n$ is a random variable converging to the standard $\mathcal{N}(0,1)$ Gaussian as $n \rightarrow \infty$. Thus, there is a universality phenomenon when differentiating a random polynomial many times: the remaining roots follow a Wigner semicircle distribution.
The influence of auditor narcissism and moral disengagement on risk assessments of a narcissistic client CFO

Abstract Global capital markets rely heavily on independent and skeptical auditors as gatekeepers to provide assurance that corporate financial reports are free of material fraud. The rise of narcissism among the ranks of both client and audit professionals challenge this gatekeeper function. In addition, auditor moral disengagement may undermine auditor skepticism, further eroding public confidence in the integrity of financial reporting and the audit process. We conduct a quasi-experiment with 118 auditors from three international audit firms. In a simulated interview with a client CFO, we examine whether auditors underestimate risks of fraudulent financial statements due to the interactive effects of (1) client narcissism (manipulated verbally and nonverbally) and (2) auditor narcissism. We also examine the influence of auditor moral disengagement on client risk assessments. Results indicate that CFO verbal and nonverbal narcissism significantly influenced auditors’ assessment of management-related client risk. Moreover, auditor narcissism was found to interactively influence client risk inferences such that auditors higher in narcissism exhibited narcissistic tolerance (lower risk assessments) when the hypothetical CFO displayed high verbal narcissism. Auditor moral disengagement was negatively associated with client risk assessments. We discuss the implication of these findings on future audit judgment research, audit firm policy and training on maintaining auditor skepticism, and the audit oversight role of standard-setters.
Computationally-efficient spatiotemporal correlation analysis super-resolves anomalous diffusion

Anomalous diffusion dynamics in confined nanoenvironments govern the macroscale properties and interactions of many biophysical and material systems. Currently, it is difficult to quantitatively link the nanoscale structure of porous media to anomalous diffusion within them. Fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) has been shown to extract nanoscale structure and Brownian diffusion dynamics within gels, liquid crystals, and polymers, but has limitations which hinder its wider application to more diverse, biophysically-relevant datasets. Here, we parallelize the least-squares curve fitting step on a GPU improving computation times by up to a factor of 40, implement anomalous diffusion and two-component Brownian diffusion models, and make fcsSOFI more accessible by packaging it in a user-friendly GUI. We apply fcsSOFI to simulations of the protein fibrinogen diffusing in polyacrylamide of varying matrix densities and super-resolve locations where slower, anomalous diffusion occurs within smaller, confined pores. The improvements to fcsSOFI in speed, scope, and usability will allow for the wider adoption of super-resolution correlation analysis to diverse research topics.
Face distributions of embeddings of complete graphs

A longstanding open question of Archdeacon and Craft asks whether every complete graph has a minimum genus embedding with at most one nontriangular face. We exhibit such an embedding for each complete graph except $K_8$, the complete graph on 8 vertices, and we go on to prove that no such embedding can exist for this graph. Our approach also solves a more general problem, giving a complete characterization of the possible face distributions (i.e. the numbers of faces of each length) realizable by minimum genus embeddings of each complete graph. We also tackle analogous questions for nonorientable and maximum genus embeddings.
Toward a theory of international new ventures

The formation of organizations that are international from inception—international new ventures—is an increasingly important phenomenon that is incongruent with traditionally expected characteristics of multinational enterprises. A framework is presented that explains the phenomenon by integrating international business, entrepreneurship, and strategic management theory. That framework describes four necessary and sufficient elements for the existence of international new ventures: (1) organizational formation through internalization of some transactions, (2) strong reliance on alternative governance structures to access resources, (3) establishment of foreign location advantages, and (4) control over unique resources.
Federalism for the Worst Case

Recent scholarship has argued that the United States is vulnerable to a slide towards authoritarianism and that it may possess few institutional features protecting against such a slide. This Article argues that this literature overlooks the importance of federalism. Since the founding, courts, policymakers, and scholars have envisioned federalism as a bulwark against tyranny. But this Article builds off recent comparative experiences with democratic erosion to provide a new, institutionally-focused account of this relationship, which draws out structures that other work overlooks. It highlights the importance of autonomous state officials carrying out sensitive functions in areas such as electoral administration, judging, policing, and prosecuting in blocking common pathways towards authoritarianism. Our institutional account foregrounds often-overlooked designs that protect separate structures in the states, like federal inability to remove state officials even during emergency, and it sheds new light on old doctrinal problems like the anti-commandeering doctrine. Further, it highlights a tradeoff between the costs that U.S. federalism is often seen as imposing and the significant — and unique — anti-tyranny protection that it provides during a democratic emergency. Finally, it suggests ways in which federalism might be designed abroad in contexts where democratic erosion is an especially salient risk.
Supervised and unsupervised approaches for controlling narrow lexical focus in sequence-to-sequence speech synthesis

Although Sequence-to-Sequence (S2S) architectures have become state-of-the-art in speech synthesis, capable of generating outputs that approach the perceptual quality of natural samples, they are limited by a lack of flexibility when it comes to controlling the output. In this work we present a framework capable of controlling the prosodic output via a set of concise, interpretable, disentangled parameters. We apply this framework to the realization of emphatic lexical focus, proposing a variety of architectures designed to exploit different levels of supervision based on the availability of labeled resources. We evaluate these approaches via listening tests that demonstrate we are able to successfully realize controllable focus while maintaining the same, or higher, naturalness over an established baseline, and we explore how the different approaches compare when synthesizing in a target voice with or without labeled data.
De Novo Acetate Production is Coupled to Central Carbon Metabolism in Mammals

In cases of nutritional excess, there is incomplete catabolism of a nutritional source and secretion of a waste product (overflow metabolism), such as the conversion of glucose to lactate (the Warburg Effect) in tumors. Here we report that excess glucose metabolism generates acetate, a key nutrient not presently known to be produced de novo in mammals. Conversion of pyruvate, the product of glycolysis, to acetate occurs through two mechanisms: 1) coupling to reactive oxygen species (ROS), and 2) a neomorphic enzyme activity from keto acid dehydrogenases that enable it to function as a pyruvate decarboxylase. Furthermore, we demonstrate that glucose-derived acetate is sufficient to maintain acetyl-coenzyme A (Ac-CoA) pools and cell proliferation in certain limited metabolic environments such as during mitochondrial dysfunction or ATP citrate lyase (ACLY) deficiency. Thus, de novo acetate production is coupled to the activity of central carbon metabolism providing possible regulatory mechanisms and links to pathophysiology.
Sequential Strangeness Freeze-out

I will describe the latest results from lattice QCD pertaining to a potential flavour hierarchy in the hadronic freeze-out from the QCD crossover region. I will compare these results to a variety of improved hadronic resonance gas calculations and to experimental data of fluctuations of net-charge, net-proton and net-kaon multiplicity distributions, which serve as a proxy for the susceptibilities of conserved quantum numbers on the lattice. I will conclude that there is intriguing evidence for a flavour dependent freezeout, and I will suggest expansions to the experimental program at RHIC and the LHC that could potentially demonstrate the impact of a flavour separation during hadronization.
Local Currency Bond Markets Law Reform: A Methodology for Emerging Markets and Developing Economies

Recent financial crises including the ongoing one caused by the COVID-19 pandemic have consistently drawn attention to the need to strengthen the quality of public debt management in emerging markets and developing countries. Deeper and more efficient domestic government debt markets-being, a key segment of the LCBM for many emerging markets and developing economies-play a key role in reducing financial vulnerability to shocks and enable governments to finance critical economic and fiscal policy measures in response to them. Policymakers and international organizations have long recognized that developing and strengthening LCBMs is a key policy prescription to sound public debt management. Robust legal and regulatory frameworks are recognized as being critical building blocks for the structure, development and functioning of LCBMs. This Working Paper seeks to outline a strategically anchored methodology that can be applied to design, build and implement the legal and tax foundations for the development of LCBMs that would adequately address common challenges and impediments.
All-sky dynamical response of the Galactic halo to the Large Magellanic Cloud.

Gravitational interactions between the Large Magellanic Cloud (LMC) and the stellar and dark matter halo of the Milky Way are expected to give rise to disequilibrium phenomena in the outer Milky Way1–7. A local wake is predicted to trail the orbit of the LMC, and a large-scale overdensity is predicted to exist across a large area of the northern Galactic hemisphere. Here we report the detection of both the local wake and northern overdensity (hereafter the ‘collective response’) in a map of the Galaxy based on 1,301 stars at Galactocentric distances between 60 and 100 kiloparsecs. The location of the wake is in good agreement with an N-body simulation that includes the dynamical effect of the LMC on the Milky Way halo. The density contrast of the wake and collective response are stronger in the data than in the simulation. The detection of a strong local wake is independent evidence that the Magellanic clouds are on their first orbit around the Milky Way. The wake traces the path of the LMC, which will provide insight into the orbit of the LMC, which in turn is a sensitive probe of the mass of the LMC and the Milky Way. These data demonstrate that the outer halo is not in dynamical equilibrium, as is often assumed. The morphology and strength of the wake could be used to test the nature of dark matter and gravity. The detection of structure in the distribution of giant stars in the outer Galactic halo shows the substantial global impact of the Magellanic clouds on our Galaxy.
Deep hedging of long-term financial derivatives

Abstract This study presents a deep reinforcement learning approach for global hedging of long-term financial derivatives. A similar setup as in Coleman et al. (2007) is considered with the risk management of lookback options embedded in guarantees of variable annuities with ratchet features. The deep hedging algorithm of Buehler et al. (2019a) is applied to optimize neural networks representing global hedging policies with both quadratic and non-quadratic penalties. To the best of the author’s knowledge, this is the first paper that presents an extensive benchmarking of global policies for long-term contingent claims with the use of various hedging instruments (e.g. underlying and standard options) and with the presence of jump risk for equity. Monte Carlo experiments demonstrate the vast superiority of non-quadratic global hedging as it results simultaneously in downside risk metrics two to three times smaller than best benchmarks and in significant hedging gains. Analyses show that the neural networks are able to effectively adapt their hedging decisions to different penalties and stylized facts of risky asset dynamics only by experiencing simulations of the financial market exhibiting these features. Numerical results also indicate that non-quadratic global policies are significantly more geared towards being long equity risk which entails earning the equity risk premium.
Pretreatment with LCK inhibitors chemosensitizes cisplatin‐resistant endometrioid ovarian tumors

Ovarian cancer is the most fatal gynecologic malignancy in the United States. While chemotherapy is effective in the vast majority of ovarian cancer patients, recurrence and resistance to standard systemic therapy is nearly inevitable. We discovered that activation of the non-receptor tyrosine kinase Lymphocyte Cell-Specific Protein-Tyrosine Kinase (LCK) promoted cisplatin resistance. Here, we hypothesized that treating high grade, platinum resistant endometrioid cancer cells with an LCK inhibitor (LCKi) followed by co-treatment with cisplatin would lead to increased cisplatin efficacy. Our objective was to assess clinical outcomes associated with increased LCK expression, test our hypothesis of utilizing LCKi as pre-treatment followed by co-treatment with cisplatin in platinum resistant ovarian cancer in vitro, and evaluate our findings in vivo to assess LCKi applicability as a therapeutic agent. Kaplan-Meier (KM) plotter data indicated LCK expression is associated with significantly worse median progression-free survival (HR 3.19, p = 0.02), and a trend toward decreased overall survival in endometrioid ovarian tumors with elevated LCK expression (HR 2.45, p = 0.41). In vitro, cisplatin resistant ovarian endometrioid cells treated first with LCKi followed by combination LCKi-cisplatin treatment showed decreased cell viability and increased apoptosis. Immunoblot studies revealed LCKi led to increased expression of phosphorylated H2A histone family X ( $$\gamma$$ -H2AX), a marker for DNA damage. In vivo results demonstrate treatment with LCKi followed by LCKi-cisplatin led to significantly slowed tumor growth. We identified a strategy to therapeutically target cisplatin resistant endometrioid ovarian cancer leading to chemosensitization to platinum chemotherapy via treatment with LCKi followed by co-treatment with LCKi-cisplatin.
Bayesian survival analysis using gamma processes with adaptive time partition

In Bayesian semi-parametric analyses of time-to-event data, non-parametric process priors are adopted for the baseline hazard function or the cumulative baseline hazard function for a given finite ...
Can service-learning boost science achievement, civic engagement, and social skills? A randomized controlled trial of Connect Science

Abstract This randomized controlled trial examined the efficacy of an elementary school service-learning program, Connect Science (CS), on classroom practices and students' science achievement, civic engagement, and social skills. Fourth grade teachers were enrolled into intervention versus control conditions resulting in 41 classrooms (20 intervention) with 868 students (423 intervention). Intervention group teachers taught CS and control group teachers taught “business-as-usual” science over a 14–22 week period. CS had a positive impact on classroom practices (Next Generation Science Standards and CS practices). Analyses showed positive impact of CS on science achievement and energy attitudes and behaviors. Use of CS practices mediated the relation between CS and energy attitudes and behaviors. Improved social skills were evident in conditions of high fidelity of implementation.
Goodness-of-Fit Test for Mismatched Self-Exciting Processes

Recently there have been many research efforts in developing generative models for self-exciting point processes, partly due to their broad applicability for real-world applications. However, rarely can we quantify how well the generative model captures the nature or ground-truth since it is usually unknown. The challenge typically lies in the fact that the generative models typically provide, at most, good approximations to the ground-truth (e.g., through the rich representative power of neural networks), but they cannot be precisely the ground-truth. We thus cannot use the classic goodness-of-fit (GOF) test framework to evaluate their performance. In this paper, we develop a GOF test for generative models of self-exciting processes by making a new connection to this problem with the classical statistical theory of Quasi-maximum-likelihood estimator (QMLE). We present a non-parametric self-normalizing statistic for the GOF test: the Generalized Score (GS) statistics, and explicitly capture the model misspecification when establishing the asymptotic distribution of the GS statistic. Numerical simulation and real-data experiments validate our theory and demonstrate the proposed GS test's good performance.
Input-output framework for actuated boundary layers

The input-output approach is expanded to investigate actuated wall-bounded shear flows whose geometries and input signals span a range of pulse-width modulated signals common in experimental flow control studies. The model is validated through comparisons to experiments and simulations of three different plasma actuator geometries. An important benefit of this analytical method is the low computational cost associated with its use, enabling efficient parametric studies.
Multi-Modal Identification of State-Sponsored Propaganda on Social Media

The prevalence of state-sponsored propaganda on the Internet has become a cause for concern in the recent years. While much effort has been made to identify state-sponsored Internet propaganda, the problem remains far from being solved because the ambiguous definition of propaganda leads to unreliable data labelling, and the huge amount of potential predictive features causes the models to be inexplicable. This paper is the first attempt to build a balanced dataset for this task. The dataset is comprised of propaganda by three different organizations across two time periods. A multi-model framework for detecting propaganda messages solely based on the visual and textual content is proposed which achieves a promising performance on detecting propaganda by the three organizations both for the same time period (training and testing on data from the same time period) ( $\mathrm{F}1=0.869$ ) and for different time periods (training on past, testing on future) ( $\mathrm{F}1=0.697$ ). To reduce the influence of false positive predictions, we change the threshold to test the relationship between the false positive and true positive rates and provide explanations for the predictions made by our models with visualization tools to enhance the interpretability of our framework. Our new dataset and general framework provide a strong benchmark for the task of identifying state-sponsored Internet propaganda and point out a potential path for future work on this task.
Fmrp regulates oligodendrocyte lineage cell specification and differentiation

Neurodevelopment requires the precise integration of a wide variety of neuronal and glial cell types. During early embryonic development, motor neurons and then oligodendrocyte precursor cells (OPCs) are specified from neural progenitors residing in the periventricular pMN progenitor domain of the spinal cord. Following gliogenesis, OPCs can differentiate as oligodendrocytes (OLs)-the myelinating glial cells of the central nervous system-or remain as OPCs. To generate unique cell types capable of highly divergent functions, these specification and differentiation events require specialized gene expression programs. RNA binding proteins (RBPs) regulate mRNA localization and translation in the developing nervous system and are linked to many neurodevelopmental disorders. One example is Fragile X syndrome (FXS), caused by the loss of the RBP fragile X mental retardation protein (FMRP). Importantly, infants with FXS have reduced white matter and we previously showed that zebrafish Fmrp is autonomously required in OLs to promote myelin sheath growth. We now find that Fmrp regulates cell specification in pMN progenitor cells such that fmr1 mutant zebrafish generate fewer motor neurons and excess OPCs. Fmrp subsequently promotes differentiation of OPCs, leading to fewer differentiating OLs in the developing spinal cord of fmr1 larvae. Although the early patterning of spinal progenitor domains appears largely normal in fmr1 mutants during early embryogenesis, Shh signaling is greatly diminished. Taken together, these results suggest cell stage-specific requirements for Fmrp in the specification and differentiation of oligodendrocyte lineage cells.