cssi/SciSciGPT-SciSciNet huggingface dataset:
Training and Spontaneous Reinforcement of Neuronal Assemblies by Spike Timing Plasticity

The synaptic connectivity of cortex is plastic, with experience shaping the ongoing interactions between neurons. Theoretical studies of spike timing-dependent plasticity (STDP) have focused on either just pairs of neurons or large-scale simulations. A simple analytic account for how fast spike time correlations affect both microscopic and macroscopic network structure is lacking. We develop a low-dimensional mean field theory for STDP in recurrent networks and show the emergence of assemblies of strongly coupled neurons with shared stimulus preferences. After training, this connectivity is actively reinforced by spike train correlations during the spontaneous dynamics. Furthermore, the stimulus coding by cell assemblies is actively maintained by these internally generated spiking correlations, suggesting a new role for noise correlations in neural coding. Assembly formation has often been associated with firing rate-based plasticity schemes; our theory provides an alternative and complementary framework, where fine temporal correlations and STDP form and actively maintain learned structure in cortical networks.
Testing moving average trading strategies on ETFs

Abstract The evidence for the profitability of MA strategies documented in the literature is usually based on non-tradable indices or portfolios/factors and the use of the zero return or risk-free rate as the benchmark. In this paper we implement MA strategies using ETFs and examine the performance of such strategies using a variety of risk-adjusted performance measures. We find that relative to the buy-and-hold strategy, MA strategies have lower average returns and Sharpe ratios, but fare better under factor-adjusted performance measures such as the CAPM alpha. We also find that MA strategies become less profitable when they are implemented using ETFs than using their underlying indices. In addition, we propose a quasi-intraday version of the standard MA strategy (QUIMA) that allows investors to trade immediately upon observing MA crossover signals. The QUIMA strategy outperforms the standard one that only trades at the close of a trading day, when the long-term MA lag length is no more than 50 days.
The Second Great Debate Revisited: Exploring the Impact of the Qualitative-Quantitative Divide in International Relations

Half a century after the Second Great Debate in International Relations (IR) started, scholars still perceive the qualitative versus quantitative division as their principal divide, and yet we do not have a good grasp of the impact of this divide. My research explores how the divide shaped the incentives and behaviors of scholars and influenced the organization of our academic communities and knowledge production. The impact of the divide expressed itself in the distribution of research among methodologies in terms of relative quantity and impact. Less obviously and yet more importantly, the divide influenced the distribution of quantitative research among different institution types, across fields and journals, and with respect to policy engagement. Using the TRIP database of 7792 IR articles in 12 top journals from 1980 to 2014, I classify journal articles into three categories-–quantitative-only, qualitative-only, and mixed-methods–-and categorize author institutions into similar types–-publishing quantitative research only, producing non-quantitative work only, and publishing various proportions of quantitative research. Notably, qualitative and quantitative works switched positions over time in terms of relative quantity and impact, with quantitative research more likely published but only slightly more cited in the recent decade. More importantly, the divide produced other less obvious but more serious outcomes. Among 1111 institutions that ever published IR research in 12 top journals over 35 years, two-thirds published non-quantitative research only; 53 institutions published more than half of all quantitative articles; institutions publishing quantitative-only or non-quantitative-only research constituted two modal categories. Political science journals published more quantitative research, persistently and with growing convergence; IR journals also evolved toward publishing more quantitative research, though with persistent divergence and forming two clusters. Quantitative articles and political science journals were significantly less engaged in providing policy prescriptions than qualitative articles and IR journals. To overcome this lasting and self-perpetuating divide, we must better understand its impact, learn to appreciate alternative approaches, and change the way we train future scholars.
Dynamic and integrative capabilities for profiting from innovation in digital platform-based ecosystems

Abstract For firms at the center of platform-based ecosystems, Teece (2018) argues that dynamic capabilities can enable the firms to create and capture value by building ecosystems and designing appropriate business models. In line with the original Profiting From Innovation (PFI) framework, Teece (2018) also argues that complementary asset providers may be able to capture substantial value. Here we provide a theoretical analysis that explains the ways in which dynamic capabilities underpin not only value creation but also value capture by platform leaders. We propose that three types of dynamic capabilities at a minimum are critical for platform leaders: innovation capabilities, environmental scanning and sensing capabilities, and integrative capabilities for ecosystem orchestration. We further argue that integrative capabilities play a key role in improving the ability of platform leaders to capture value.
A unifying framework for joint trait analysis under a non-infinitesimal model.

Motivation A large proportion of risk regions identified by genome-wide association studies (GWAS) are shared across multiple diseases and traits. Understanding whether this clustering is due to sharing of causal variants or chance colocalization can provide insights into shared etiology of complex traits and diseases. Results In this work, we propose a flexible, unifying framework to quantify the overlap between a pair of traits called UNITY (Unifying Non-Infinitesimal Trait analYsis). We formulate a Bayesian generative model that relates the overlap between pairs of traits to GWAS summary statistic data under a non-infinitesimal genetic architecture underlying each trait. We propose a Metropolis-Hastings sampler to compute the posterior density of the genetic overlap parameters in this model. We validate our method through comprehensive simulations and analyze summary statistics from height and body mass index GWAS to show that it produces estimates consistent with the known genetic makeup of both traits. Availability and implementation The UNITY software is made freely available to the research community at: https://github.com/bogdanlab/UNITY. Supplementary information Supplementary data are available at Bioinformatics online.
Technology and skill: Twin engines of growth

Abstract A model is developed in which two complementary forms of investment contribute to growth—technology and skill acquisition, and growth takes two forms—TFP and variety growth. The rate of TFP growth depends more heavily on the parameters governing skill accumulation, while variety growth depends, roughly, on the difference between the parameters governing technology and skill accumulation. Conditions for the existence of a BGP are established, and the effects of various parameters are characterized. In an example, subsidies to skill acquisition (technology acquisition) are powerful tools for stimulating TFP growth (variety growth). Investment incentives off the BGP are also explored.
Microcellular PET foams produced by the solid-state process

Publisher Summary The basic procedure to produce microcellular foam is a two stage process. In the first stage, a polymer sample is placed in a high pressure, nonreactive gas environment at a temperature below the glass transition temperature and allowed to absorb gas. In the second stage, the pressure is released, forming a supersaturated solution of gas and polymer. The specimen is then heated to or above the glass transition temperature of the original polymer. This causes bubbles to nucleate and grow. The majority of work on microcellular foams to date has been conducted on the polystyrene-nitrogen system. This chapter studies the resultant foam parameters (density, average cell diameter, and cell nucleation density) in terms of process control parameters (saturation pressure (PSAT), saturation time (tSAT), saturation temperature (TSAT), foaming pressure (PF), foaming time (tF), and foaming temperature (TF). Additionally, the role of crystallinity is studied. Crystallinity is important to the microcellular process because crystallites provide nucleation sites for bubble growth. Crystallization increases in PET during the sorption of CO2 but the two processes are not coupled. The carbon dioxide-induced crystallinity is the dominant factor affecting bubble nucleation and growth in PET foams produced by the solid state process. The crystallized PET, when foamed, shows the highest bubble nucleation densities achieved in this system. High-nucleation densities are usually coupled with small bubble sizes. Thus the carbon dioxide induced crystallization can be employed to obtain smaller bubbles than are seen in low crystallinity or amorphous PET foams.
Banker my neighbour: matching and financial intermediation in savings groups

Abstract Efforts to promote financial inclusion have largely focused on microcredit and micro-savings separately, less so on promoting financial intermediation across poor borrowers and savers. Village Savings and Loan Associations (VSLAs) may enable borrowers and savers to meet each others' needs, by combining a borrowing and a commitment savings technology. On the other hand, frictions such as imperfect information and enforcement may limit VSLAs’ ability to attract both borrowers and savers into the same group. To investigate whether VSLAs provide effective financial intermediation, we use a large-scale survey of mature VSLA groups in rural Malawi. We find that VSLAs mobilize large quantities of savings that are then lent to individual members at high interest rates, yielding savers a large return on their savings. We examine whether this process is assisted by the sorting of members across VSLAs. We find that present-biased individuals tend to group with time-consistent members, consistent with the hypothesis that the former gain a commitment savings technology by lending to the latter. In contrast, members of the same occupation sort into groups together, indicating unrealised intermediation possibilities between farming and non-farming households. This has implications for the design of such groups.
Best-Choice Edge Grafting for Efficient Structure Learning of Markov Random Fields

Incremental methods for structure learning of pairwise Markov random fields (MRFs), such as grafting, improve scalability by avoiding inference over the entire feature space in each optimization step. Instead, inference is performed over an incrementally grown active set of features. In this paper, we address key computational bottlenecks that current incremental techniques still suffer by introducing best-choice edge grafting, an incremental, structured method that activates edges as groups of features in a streaming setting. The method uses a reservoir of edges that satisfy an activation condition, approximating the search for the optimal edge to activate. It also reorganizes the search space using search-history and structure heuristics. Experiments show a significant speedup for structure learning and a controllable trade-off between the speed and quality of learning.
Addressing Recognition Gaps: Destigmatization and the Reduction of Inequality:

This Presidential Address offers elements for a systematic and cumulative study of destigmatization, or the process by which low-status groups gain recognition and worth. Contemporary sociologists tend to focus on inequality in the distribution of resources, such as occupations, education, and wealth. Complementing this research, this address draws attention to “recognition gaps,” defined as disparities in worth and cultural membership between groups in a society. I first describe how neoliberalism promotes growing recognition gaps. Then, drawing on research on stigmatized groups across several societies, I analyze how experiences of stigma and destigmatization are enabled and constrained by various contextual factors and actors, including institutions, cultural repertoires, knowledge workers, and social movement activists. I conclude by proposing a research agenda for the sociology of recognition and destigmatization, and by sketching how social scientists, policymakers, organizations, and citizens can c...
Investors’ Uncertainty and Stock Market Risk

The authors propose a novel approach to model investors' uncertainty using the conditional volatility of investors' sentiment. Working with weekly data on investor sentiment, 6 major U.S. stock ind...
Wireless Channel Dynamics and Robustness for Ultra-Reliable Low-Latency Communications

Interactive, immersive, and other timing-critical applications demand ultra-reliable low-latency communication (URLLC). To build wireless communication systems that can support these applications, understanding the relevant characteristics of the wireless medium is paramount. Although wireless channel characteristics and dynamics have been extensively studied, it is important to revisit these concepts in the context of the strict demands of low-latency and ultra-high reliability. In this paper, we bring a modeling approach from robust control to wireless communication—the wireless channel characteristics are given a nominal model around which we allow for some quantified uncertainty. We propose certain key URLLC-relevant parameters along which the model uncertainty is to be bounded. To validate the nominal model of the spatially independent quasi-static Rayleigh fading, we take an in-depth look at the spatial and temporal correlations based on Jakes’ model. We find that although the Rayleigh fading process is band-limited, the quasi-static assumption is not safe for relay selection even well within a single coherence time. We also find that under reasonable conditions, the spatial correlation of channels provide a fading distribution that is not too far off from an independent spatial fading model. In addition, we look at the impact of these channel models on cooperative communication-based systems. We find that while spatial-diversity-based techniques are necessary to combat the adverse effects of fading, time-diversity-based techniques are necessary to be robust against unmodeled errors. Robust URLLC systems need to operate with both an adequate SNR margin and a time margin through repetitions.
Logical Entropy: Introduction to Classical and Quantum Logical Information Theory

Logical information theory is the quantitative version of the logic of partitions just as logical probability theory is the quantitative version of the dual Boolean logic of subsets. The resulting notion of information is about distinctions, differences and distinguishability and is formalized using the distinctions (“dits”) of a partition (a pair of points distinguished by the partition). All the definitions of simple, joint, conditional and mutual entropy of Shannon information theory are derived by a uniform transformation from the corresponding definitions at the logical level. The purpose of this paper is to give the direct generalization to quantum logical information theory that similarly focuses on the pairs of eigenstates distinguished by an observable, i.e., qudits of an observable. The fundamental theorem for quantum logical entropy and measurement establishes a direct quantitative connection between the increase in quantum logical entropy due to a projective measurement and the eigenstates (cohered together in the pure superposition state being measured) that are distinguished by the measurement (decohered in the post-measurement mixed state). Both the classical and quantum versions of logical entropy have simple interpretations as “two-draw” probabilities for distinctions. The conclusion is that quantum logical entropy is the simple and natural notion of information for quantum information theory focusing on the distinguishing of quantum states.
Pro bono as a human capital learning and screening mechanism: Evidence from law firms

Research Summary: Inquiry into CSR as a human capital management tool has suggested that firms benefit from such activities because employees value the meaningfulness of these activities, which influences motivation and retention. We propose an alternate avenue through which firms can benefit from an important type of socially responsible activity—pro bono services—that does not require that employees derive utility from the meaningfulness of the activity. We propose that pro bono activities can benefit firms through human capital learning and screening mechanisms, given the stretch roles that pro bono engagements allow. We formalize this argument in the legal services industry, where we provide primary evidence, a formal model, and empirical results using a panel dataset of the top 200 law firms to support this argument. Managerial Summary: We examine a type of CSR activity, pro bono engagements, in the context of the top 200 law firms in the United States. We show that firms can benefit from these engagements through human capital learning and screening mechanisms, due to the stretch roles that pro bono engagements allow junior lawyers. Our findings suggest that firms in which pro bono engagements provide stretch roles for junior employees can benefit from pro bono activities regardless of whether their employees value the meaningfulness or social impact of the pro bono work.
Fair redistricting is hard

Abstract Gerrymandering is a long-standing issue within the U.S. political system, and it has received scrutiny recently by the U.S. Supreme Court. In this note, we prove that deciding whether there exists a fair redistricting among legal maps is NP -hard. To make this precise, we use simplified notions of “legal” and “fair” that account for desirable traits such as geographic compactness of districts and sufficient representation of voters. The proof of our result is inspired by the work of Mahanjan, Minbhorkar and Varadarajan that proves that planar k-means is NP -hard.
“Life never matters in the DEMOCRATS MIND”: Examining strategies of retweeted social bots during a mass shooting event

This exploratory study examines the strategies of social bots on Twitter that were retweeted following a mass shooting event. Using a case study method to frame our work, we collected over seven million tweets during a one-month period following a mass shooting in Parkland, Florida. From this dataset, we selected retweets of content generated by over 400 social bot accounts to determine what strategies these bots were using and the effectiveness of these strategies as indicated by the number of retweets. We employed qualitative and quantitative methods to capture both macro- and micro-level perspectives. Our findings suggest that bots engage in more diverse strategies than solely waging disinformation campaigns, including baiting and sharing information. Further, we found that while bots amplify conversation about mass shootings, humans were primarily responsible for disseminating bot-generated content. These findings add depth to the current understanding of bot strategies and their effectiveness. Understanding these strategies can inform efforts to combat dubious information as well as more insidious disinformation campaigns.
Anisotropy-driven collisional separation of impurities in magnetized compressing and expanding cylindrical plasmas

When a cylindrically symmetric magnetized plasma compresses or expands, velocity-space anisotropy is naturally generated as a result of the different adiabatic conservation laws parallel and perpendicular to the magnetic field. When the compression timescale is comparable to the collision timescale, and both are much longer than the gyroperiod, this pressure anisotropy can become significant. We show that this naturally generated anisotropy can dramatically affect the transport of impurities in the compressing plasma, even in the absence of scalar temperature or density gradients, by modifying the azimuthal frictions that give rise to radial particle transport. Although the impurity transport direction depends only on the sign of the pressure anisotropy, the anisotropy itself depends on the pitch magnitude of the magnetic field and the sign of the radial velocity. Thus, pressure anisotropy effects can drive impurities either towards or away from the plasma core. These anisotropy-dependent terms represent a qualitatively new effect, influencing transport particularly in the sparse edge regions of dynamically compressing screw pinch plasmas. Such plasmas are used for both X-ray generation and magneto-inertial fusion, applications which are sensitive to impurity concentrations.When a cylindrically symmetric magnetized plasma compresses or expands, velocity-space anisotropy is naturally generated as a result of the different adiabatic conservation laws parallel and perpendicular to the magnetic field. When the compression timescale is comparable to the collision timescale, and both are much longer than the gyroperiod, this pressure anisotropy can become significant. We show that this naturally generated anisotropy can dramatically affect the transport of impurities in the compressing plasma, even in the absence of scalar temperature or density gradients, by modifying the azimuthal frictions that give rise to radial particle transport. Although the impurity transport direction depends only on the sign of the pressure anisotropy, the anisotropy itself depends on the pitch magnitude of the magnetic field and the sign of the radial velocity. Thus, pressure anisotropy effects can drive impurities either towards or away from the plasma core. These anisotropy-dependent terms represent ...
Distinguishing the roles of dorsolateral and anterior PFC in visual metacognition

Visual metacognition depends on regions within the prefrontal cortex (PFC). Two areas in particular have been implicated repeatedly: the dorsolateral PFC (DLPFC) and the anterior PFC (aPFC). However, it is still unclear what the function of each of these areas is and how they differ from each other. To establish the specific roles of DLPFC and aPFC in metacognition, we used online transcranial magnetic stimulation (TMS) to interfere causally with their functioning during confidence generation. Human subjects from both sexes performed a perceptual decision making and provided confidence ratings. We found a clear dissociation between the two areas: DLPFC TMS lowered confidence ratings, whereas aPFC TMS increased metacognitive ability, but only for the second half of the experimental blocks. These results support a functional architecture in which DLPFC reads out the strength of the sensory evidence and relays it to aPFC, which makes the confidence judgment by potentially incorporating additional, nonperceptual information. Indeed, simulations from a model that incorporates these putative DLPFC and aPFC functions reproduced our behavioral results. These findings establish DLPFC and aPFC as distinct nodes in a metacognitive network and suggest specific contributions from each of these regions to confidence generation.SIGNIFICANCE STATEMENT The prefrontal cortex (PFC) is known to be critical for metacognition. Two of its subregions, the dorsolateral PFC (DLPFC) and the anterior PFC (aPFC), have been specifically implicated in confidence generation. However, it is unclear whether these regions have distinct functions related to the underlying metacognitive computation. Using a causal intervention with transcranial magnetic stimulation, we demonstrate that DLPFC and aPFC have dissociable contributions: targeting DLPFC decreased average confidence ratings, whereas targeting aPFC affected metacognitive scores specifically. Based on these results, we postulated specific functions for DLPFC and aPFC in metacognitive computation and corroborated them using a computational model that reproduced our results. Our causal results reveal the existence of a specialized modular organization in PFC for confidence generation.
Decision Level Fusion: An Event Driven Approach

This paper presents a technique that combines the occurrence of certain events, as observed by different sensors, in order to detect and classify objects. This technique explores the extent of dependence between features being observed by the sensors, and generates more informed probability distributions over the events. Provided some additional information about the features of the object, this fusion technique can outperform other existing decision level fusion approaches that may not take into account the relationship between different features.
Issues in the Sociology and Psychology of Religious Conversion

Religious conversion is the process by which a person commits to the beliefs of a new religious tradition and shifts away from their previously held religious beliefs (Stark and Finke 2000). Religious conversion and its mechanisms have been studied for millennia (Zinnbauer and Pargament in Journal for the Scientific Study of Religion, 37(1), 161–180, 1998) and were among the first phenomena to be studied by psychology (Paloutzian et al. in Journal of Personality, 67(6), 1047–1079, 1999). This review of conversion begins with a discussion of diverse conceptualizations, and hence multiple definitions, of conversion. Next, recurring components of major psychological and sociological conversion theories are explored—those consistently recognized as important for understanding and explaining the large amount of variance across conversions. Such components include the convert’s agency, the convert’s social integration, the temporal span of conversion, the nature of conversion’s consequences, and the roles that crisis, emotion, religion, and identity play in conversion. Identifying which components of conversion, and the issues that surround them, are consistently of significance to scholars provides future researchers practical starting points for accurately measuring the conversion process.
Demonstration of End-to-End Automation of DNA Data Storage

Synthetic DNA has emerged as a novel substrate to encode computer data with the potential to be orders of magnitude denser than contemporary cutting edge techniques. However, even with the help of automated synthesis and sequencing devices, many intermediate steps still require expert laboratory technicians to execute. We have developed an automated end-to-end DNA data storage device to explore the challenges of automation within the constraints of this unique application. Our device encodes data into a DNA sequence, which is then written to a DNA oligonucleotide using a custom DNA synthesizer, pooled for liquid storage, and read using a nanopore sequencer and a novel, minimal preparation protocol. We demonstrate an automated 5-byte write, store, and read cycle with a modular design enabling expansion as new technology becomes available.
Concept embedding-based weighting scheme for biomedical text clustering and visualization

Biomedical text clustering is a text mining technique used to provide better document search, browsing, and retrieval in biomedical and clinical text collections. In this research, the document representation based on the concept embedding along with the proposed weighting scheme is explored. The concept embedding is learned through the neural networks to capture the associations between the concepts. The proposed weighting scheme makes use of the concept associations to build document vectors for clustering. We evaluate two types of concept embedding and new weighting scheme for text clustering and visualization on two different biomedical text collections. The returned results demonstrate that the concept embedding along with the new weighting scheme performs better than the baseline tf–idf for clustering and visualization. Based on the internal clustering evaluation metric-Davies–Bouldin index and the visualization, the concept embedding generated from aggregated word embedding can form well-separated clusters, whereas the intact concept embedding can better identify more clusters of specific diseases and gain better F-measure.
To Share or Not to Share? Capacity Reservation in a Shared Supplier

When a supplier serves multiple buyers, the buyers often reserve the supplier's capacity in advance to secure the supply to fulfill their demand. In this paper, we analyze two common types of capacity reservation: exclusive and first-priority reservations. Both reservations give a buyer first access to its reserved capacity, but the reservations differ in how the leftovers (if any) are used. In most cases, as long as the buyer gets to use the reserved capacity first, it does not pay attention to how the leftover capacity is utilized, leaving that to the supplier's discretion (first-priority). However, in a number of cases, buyers prohibit discretionary use of the reserved capacity ("no one touches my leftovers") and implement the restriction by placing an employee at the supplier or installing monitoring devices (exclusive). One potential benefit of first-priority capacity is resource pooling: allowing access to one another's leftovers can reduce the amount of capacity reserved by the buyers while enabling the supplier to satisfy buyers' orders better in some cases. The Operations Management literature suggests that the benefit of resource pooling is greater when the demand correlation is negative and smaller when the correlation is positive. We investigate the capacity reservation type and level that each buyer chooses facing uncertain (and correlated) demand. We investigate how the reservation price and demand correlation affect the equilibrium outcome. We also examine the supplier's decision to set the optimal reservation prices. We find that at least one firm reserves first-priority capacity in equilibrium as long as the supplier offers a discount for first-priority capacity (or charges a premium for exclusive capacity). Depending on the reservation price difference and demand correlation, we find that the equilibrium outcome is inefficient (i.e., not Pareto optimal) for the buyers when they settle in a free-rider or a prisoner's dilemma equilibrium. We show that the supplier always induces both buyers to reserve a large amount of exclusive capacity so that the supplier can make profits from both capacity reservation and production. While this seems like the best scenario for the supplier, we show that, allowing bilateral capacity transfer (e.g., the buyers trading their reserved capacity) can improve not only the buyers' profits but also the supplier's profit.
Memoria de intemacionalistas chilenos. Entramado conceptual y recuperación histórica. Apuntes para el debate

espanolResumen: El presente articulo, rescata la memoria de cuatro chilenos, que se vincularon con organizaciones revolucionarias en el extranjero y que desarrollaron un trabajo politico bajo la vision del Internacionalismo militante. El testimonio de los entrevistados, es la puerta de entrada que nos permite deambular por los margenes de un fenomeno amplio y de largo alcance como lo es el Internacionalismo. Una vez alli, pretendemos identificar los componentes teoricos que lo entrelazan, y evidenciar la existencia de otras experiencias internacionalistas que van mas alla de las estudiadas por la historiografia reciente, a saber, el derrotero de chilenos comunistas entrenados en Cuba y que participaron en la guerrilla sandinista. Nuestro foco estuvo direccionado en la historia de miristas, socialistas y mapucistas, que practicaron el internacionalismo en Bolivia, Peru, Nicaragua y Argentina. EnglishAbstract: This article rescues the memory of four Chileans, who were linked to revolutionary organizations abroad and who developed a political work under the vision of militant Internationalism. The testimony of the interviewees is the gateway that allows us to wander the margins of a broad and far-reaching phenomenon such as Internationalism. Once there, we try to identify the theoretical components that interweave it, and to show the existence of other internationalist experiences that go beyond those studied by recent historiography, namely, the course of Communist Chileans trained in Cuba and who participated in the guerrilla Sandinista. Our focus was on the history of miristas, socialists and mapucistas, who practiced internationalism in Bolivia, Peru, Nicaragua and Argentina.
A Quantum Query Complexity Trichotomy for Regular Languages

We present a trichotomy theorem for the quantum query complexity of regular languages. Every regular language has quantum query complexity Θ(1), ~Θ(√ n), or Θ(n). The extreme uniformity of regular languages prevents them from taking any other asymptotic complexity. This is in contrast to even the context-free languages, which we show can have query complexity Θ(n^c) for all computable c [1/2,1]. Our result implies an equivalent trichotomy for the approximate degree of regular languages, and a dichotomy--either Θ(1) or Θ(n)--for sensitivity, block sensitivity, certificate complexity, deterministic query complexity, and randomized query complexity. The heart of the classification theorem is an explicit quantum algorithm which decides membership in any star-free language in ~O(√ n) time. This well-studied family of the regular languages admits many interesting characterizations, for instance, as those languages expressible as sentences in first-order logic over the natural numbers with the less-than relation. Therefore, not only do the star-free languages capture functions such as OR, they can also express functions such as "there exist a pair of 2's such that everything between them is a 0." Thus, we view the algorithm for star-free languages as a nontrivial generalization of Grover's algorithm which extends the quantum quadratic speedup to a much wider range of string-processing algorithms than was previously known. We show a variety of applications--new quantum algorithms for dynamic constant-depth Boolean formulas, balanced parentheses nested constantly many levels deep, binary addition, a restricted word break problem, and path-discovery in narrow grids--all obtained as immediate consequences of our classification theorem.
Deposit Spreads and the Welfare Cost of Inflation

Abstract High nominal interest rates are associated with high deposit spreads, which is consistent with a model where banks have monopoly power and currency and deposits are substitutes. Therefore, higher interest rates raise the implicit price of banking services, increase bank profits and attract entry into the banking sector. Taking these effects into account, a one percentage point increase in inflation has a welfare cost of 0.083% of GDP, 6.7 times higher than traditional estimates.
Local demand-pull policy and energy innovation: Evidence from the solar photovoltaic market in China

Abstract Market demand is an important driver for inducing innovation, with many empirical studies supporting the demand-induced innovation hypothesis. Critiques of such studies, however, emphasize that new empirical evidence that can address existing empirical challenges is needed. Furthermore, existing literature disagrees about whether the locus of demand-pull policy matters. In this paper, we use empirical evidence from the distributed solar photovoltaic (PV) market in China to address the following questions: (1) Is there evidence of demand-induced innovation? (2) Does the effect of local demand-pull policy differ from the effect of non-local demand-pull policy on demand-induced innovation? To address these questions, we develop and analyze an original database of PV balance-of-system (BOS) patents in the distributed PV market filed between 2005 and 2014 in China. Our results support the demand-induced innovation hypothesis and suggest that only local demand significantly induces PV BOS innovations in the distributed PV market in China. The different effects of local demand and non-local demand emphasize the importance of local markets and local policies, lending some support to bottom-up approaches to clean energy governance.
Drivers of Spain’s Export Performance and the Role of the Labor Market Reforms

Spain’s export performance strengthened after the global financial crisis, and exports now represent more than a third of GDP. This paper argues that several factors contributed to that achievement: external demand, supported by greater diversification of destination markets; enhanced export orientation of Spanish firms, partly as a response to lower domestic demand after the crisis; and competitiveness gains, reflecting in part changes in the labor market following structural reforms adopted in 2010 and 2012. Based on cross-country panel regressions linking real export growth to employment protection indicators, those labor market reforms are estimated to account for nearly one-tenth to above one-quarter of Spain’s total export growth rate from 2010 to 2013.
Tax Policy and Local Labor Market Behavior

Since 2002, the US government has encouraged business investment using accelerated depreciation policies that significantly reduce investment costs. We provide the first in-depth analysis of this stimulus on employment and earnings. Our local labor markets approach exploits cross-industry variation in policy generosity interacted with county-level industry location data. This strategy identifies the partial equilibrium effects of accelerated depreciation. Places that experience larger decreases in investment costs see an increase in employment and earnings. In contrast, the policy does not have positive effects on earnings-per-worker. Overall, our findings suggest federal corporate tax policy has large effects on local labor markets.
Baseball and Softball Pitchers are Distinct Within-Subject Controlled Models for Exploring Proximal Femur Adaptation to Physical Activity.

Within-subject controlled models in individuals who preferentially load one side of the body enable efficient exploration of the skeletal benefits of physical activity. There is no established model of physical activity-induced side-to-side differences (i.e., asymmetry) at the proximal femur. Proximal femur asymmetry was assessed via dual-energy X-ray absorptiometry in male jumping athletes (JMP, n = 16), male baseball pitchers (BB, n = 21), female fast-pitch softball pitchers (SB, n = 22), and controls (CON, n = 42). The jumping leg was the dominant leg in JMP, whereas in BB, SB and CON the dominant leg was contralateral to the dominant/throwing arm. BB and SB had 5.5% (95% CI 3.9–7.0%) and 6.5% (95% CI 4.8–8.2%) dominant-to-nondominant leg differences for total hip areal bone mineral density (aBMD), with the asymmetry being greater than both CON and JMP (p 8%) dominant-to-nondominant leg differences in cross-sectional area, cross-sectional moment of inertia and section modulus, which were larger than any other group (p ≤ 0.02). Male baseball and female softball pitchers are distinct within-subject controlled models for exploring adaptation of the proximal femur to physical activity. They exhibit adaptation in their dominant/landing leg (i.e., leg contralateral to the throwing arm), but the pattern differs with softball pitchers exhibiting greater femoral neck adaptation.
Association of Pancreatic Steatosis With Chronic Pancreatitis, Obesity, and Type 2 Diabetes Mellitus.

ObjectiveThe aim of this study was to determine the association of the pancreatic steatosis with obesity, chronic pancreatitis (CP), and type 2 diabetes mellitus.MethodsPatients (n = 118) were retrospectively identified and categorized into no CP (n = 60), mild (n = 21), moderate (n = 27), and sever
Linear-Complexity Exponentially-Consistent Tests for Universal Outlying Sequence Detection

The problem of universal outlying sequence detection is studied, where the goal is to detect outlying sequences among $M$ sequences of samples. A sequence is considered as outlying if the observations therein are generated by a distribution different from those generating the observations in the majority of the sequences. In the universal setting, we are interested in identifying all the outlying sequences without knowing the underlying generating distributions. We consider the outlying sequence detection problem in three different scenarios: first, known number of outlying sequences; second, unknown number of identical outlying sequences; and finally, typical and outlying distributions forming clusters. In this paper, a class of tests based on distribution clustering is proposed. These tests are shown to be exponentially consistent with linear time complexity in $M$. Numerical results demonstrate that our clustering-based tests achieve similar performance to existing tests, while being considerably more computationally efficient.
How Widely Can Prediction Models Be Generalized? Performance Prediction in Blended Courses

Blended courses that mix in-person instruction with online platforms are increasingly common in secondary education. These platforms record a rich amount of data on students’ study habits and social interactions. Prior research has shown that these metrics are correlated with students performance in face-to-face classes. However, predictive models for blended courses are still limited and have not yet succeeded at early prediction or cross-class predictions, even for repeated offerings of the same course. In this paper, we use data from two offerings of two different undergraduate courses to train and evaluate predictive models of student performance based on persistent student characteristics including study habits and social interactions. We analyze the performance of these models on the same offering, on different offerings of the same course, and across courses to see how well they generalize. We also evaluate the models on different segments of the courses to determine how early reliable predictions can be made. This paper tells us in part how much data is required to make robust predictions and how cross-class data may be used, or not, to boost model performance. The results of this study will help us better understand how similar the study habits, social activities, and the teamwork styles are across semesters for students in each performance category. These trained models also provide an avenue to improve our existing support platforms to better support struggling students early in the semester with the goal of providing timely intervention.
Renal Denervation for Resistant Hypertension in the contemporary era: A Systematic Review and Meta-analysis

Renal denervation (RDN) is a catheter-based ablation procedure designed to treat resistant hypertension (RH). The objective of our study is to determine the effect of RDN on blood pressure and renal function in patients with RH in comparison to medical therapy alone. We performed an extensive literature search for randomized control trials (RCT) reporting office and 24 hr. blood pressure changes and estimated glomerular filtration rate (eGFR) at baseline and 6 months. We calculated a weighted standardized mean difference of blood pressure and renal outcomes between RDN and control groups using random effects models. Our search yielded 608 studies of which we included 15 studies for the final analysis. A total of 857 patients were treated with RDN and 616 patients treated with medical therapy ± sham procedure. Only 5 studies were double-blinded RCT with sham control. The adjusted standardized mean difference in the change in office based systolic and diastolic pressures (p = 0.18; p = 0.14); 24 hr. systolic and diastolic pressures (p = 0.20; p = 0.18); and eGFR (p = 0.20) from baseline to 6 months is statistically insignificant with significant heterogeneity. Subgroup analysis showed that among sham controlled trials, 24 hr. systolic blood pressure showed a modest but statistically significant benefit favoring renal denervation in patients with RH. Our meta-analysis of 15 RCTs showed no significant benefit of RDN on blood pressure control in patients with resistant hypertension. Subgroup analysis of sham control studies showed a modest benefit in 24 hr. systolic blood pressure at 6 months with RDN.
Deriving an affinity for collective leadership: below the surface of action learning

Is there a viable pedagogical method to prepare people, as they engage together in their practice, for the assumption of collective leadership? In this article the author makes the case that such a...
Do dividends convey information about future earnings

Abstract Yes. We show that dividend changes contain information about highly persistent changes in future economic income. Three methodological differences lead us to different conclusions from the extant literature: (i) we use an “event window approach” to cleanly delineate earnings after dividend changes from those before, (ii) we use alternative earnings measures to control for endogenous investment and asset write-downs surrounding dividend changes, and (iii) we control for the nonlinear relation between dividend changes and market reactions. Our results suggest dividend announcement returns reflect information about the level of permanent earnings, though the timing of the information content is difficult to reconcile with traditional signaling models.
Automated gaze-based mind wandering detection during computerized learning in classrooms

We investigate the use of commercial off-the-shelf (COTS) eye-trackers to automatically detect mind wandering—a phenomenon involving a shift in attention from task-related to task-unrelated thoughts—during computerized learning. Study 1 (N = 135 high-school students) tested the feasibility of COTS eye tracking while students learn biology with an intelligent tutoring system called GuruTutor in their classroom. We could successfully track eye gaze in 75% (both eyes tracked) and 95% (one eye tracked) of the cases for 85% of the sessions where gaze was successfully recorded. In Study 2, we used this data to build automated student-independent detectors of mind wandering, obtaining accuracies (mind wandering F1 = 0.59) substantially better than chance (F1 = 0.24). Study 3 investigated context-generalizability of mind wandering detectors, finding that models trained on data collected in a controlled laboratory more successfully generalized to the classroom than the reverse. Study 4 investigated gaze- and video- based mind wandering detection, finding that gaze-based detection was superior and multimodal detection yielded an improvement in limited circumstances. We tested live mind wandering detection on a new sample of 39 students in Study 5 and found that detection accuracy (mind wandering F1 = 0.40) was considerably above chance (F1 = 0.24), albeit lower than offline detection accuracy from Study 1 (F1 = 0.59), a finding attributable to handling of missing data. We discuss our next steps towards developing gaze-based attention-aware learning technologies to increase engagement and learning by combating mind wandering in classroom contexts.