cssi/SciSciGPT-SciSciNet huggingface dataset:
The Collective Benefits of Feeling Good and Letting Go: Positive Emotion and (dis) Inhibition Interact to Predict Cooperative Behavior

Cooperation is central to human existence, forming the bedrock of everyday social relationships and larger societal structures. Thus, understanding the psychological underpinnings of cooperation is of both scientific and practical importance. Recent work using a dual-process framework suggests that intuitive processing can promote cooperation while deliberative processing can undermine it. Here we add to this line of research by more specifically identifying deliberative and intuitive processes that affect cooperation. To do so, we applied automated text analysis using the Linguistic Inquiry and Word Count (LIWC) software to investigate the association between behavior in one-shot anonymous economic cooperation games and the presence inhibition (a deliberative process) and positive emotion (an intuitive process) in free-response narratives written after (Study 1, N = 4,218) or during (Study 2, N = 236) the decision-making process. Consistent with previous results, across both studies inhibition predicted reduced cooperation while positive emotion predicted increased cooperation (even when controlling for negative emotion). Importantly, there was a significant interaction between positive emotion and inhibition, such that the most cooperative individuals had high positive emotion and low inhibition. This suggests that inhibition (i.e., reflective or deliberative processing) may undermine cooperative behavior by suppressing the prosocial effects of positive emotion.
Liability Concentration and Systemic Losses in Financial Networks.

The objective of this study is to develop a majorization-based tool to compare financial networks with a focus on the implications of liability concentration. Specifically, we quantify liability concentration by applying the majorization order to the liability matrix that captures the interconnectedness of banks in a financial network. We develop notions of balancing and unbalancing networks to bring out the qualitatively different implications of liability concentration on the system’s loss profile. We illustrate how to identify networks that are balancing or unbalancing, and we make connections to interbank structures identified by empirical research, such as perfect and imperfect tiering schemes. An empirical analysis of the network formed by the banking sectors of eight representative European countries suggests that the system is either unbalancing or close to it, persistently over time. This empirical finding, along with the majorization results, supports regulatory policies aiming at limiting the s...
The design of enforcement: Collective action and the enforcement of international law:

International organizations (IOs) play a vital role in enforcing international law. I argue that collective-action problems and the design of legal-standing rules drive decisions about whether to e...
Research note: Hypotheses about political terrorism during the gulf conflict, 1990–1991

Based on a review of the literature and a logical deductive approach, the author develops 12 testable research hypotheses in connection with the possibility of oppositional political terrorism during the 1990–91 Gulf Crisis and War. The article represents the foundation of future research on one of most important anomalies of this political crisis.
Bones of Contention: The Political Economy of Height Inequality

Human osteological data provide a rich, still-to-be-mined source of information about the distribution of nutrition and, by extension, the distribution of political power and economic wealth in societies of long ago. On the basis of data we have collected and analyzed on societies ranging from foraging communities to the ancient Egyptian and modern European monarchies, we find that the shift from hunting and gathering to complex fishing techniques and to labor-intensive agriculture opened up inequalities that had discernible effects on human health and stature. But we also find that political institutions intervened decisively in the distribution of resources within societies. Political institutions appear to be shaped not only by economic factors but also by military technology and vulnerability to invasion.
The Role of Public Discourse in European Social Democratic Reform Projects

Public discourse, understood both as ideas about public action and interactive processes that serve to 'coordinate' the construction of those ideas and to 'communicate' them to the public, has been central to the success (or failure) of the reform projects of social democratic parties. Certain background factors, including countries' policy legacies, problems, preferences, and capacity set the stage for reform while good ideas which are cognitively sound and normatively appropriate as well as relevant, coherent, and consistent contribute to reform success. But institutional context also matters with regard to how ideas are conveyed to whom, with 'simple' polities emphasizing the 'communicative' discourse to the general public and more 'compound' polities the 'coordinative' discourse among policy actors. This is demonstrated with examples from Germany, France, Britain, Italy, the Netherlands, Denmark, and Sweden. Kurzfassung Offentlicher Diskurs, verstanden sowohl als Ideen uber offentliches Handeln als auch als interaktive Prozesse, die dazu dienen, die Konstruktion dieser Ideen zu "koordinieren" und diese an die Offentlichkeit zu "kommunizieren", hat sich als zentral fur den Erfolg (oder Misserfolg) von Reformprojekten sozialdemokratischer Parteien erwiesen. Gewisse Hintergrundfaktoren, einschlieslich der politischen Vermachtnisse von Landern, ihrer Probleme, Praferenzen und Kapazitaten, schaffen die Voraussetzung fur Reformen, wahrend gute Ideen, kognitiv einwandfrei und normativ sowohl adaquat als auch relevant, koharent und konsistent, zu Reformerfolgen beitragen. Aber der institutionelle Kontext ist ebenso von Bedeutung, im Hinblick darauf, wie Ideen an wen vermittelt werden, wobei "einfachen" politische Systeme den "kommunikativen" Diskurs mit der generellen Offentlichkeit betonen und "zusammengesetzte" politische Systeme den "koordinierenden" Diskurs unter den politischen Akteuren. Dies wird anhand von Beispielen aus Deutschland, Frankreich, Grosbritannien, Italien, den Niederlanden, Danemark und Schweden dargestellt. The author
The Location of Overseas Production and Production for Export by U.S. Multinational Firms

Abstract The location of overseas manufacturing production is influenced by common factors that operate in all industries: notably proximity to the United States and to other markets. Within industries, ‘opposites attract’: low-wage and low-capital-intensity parents choose high-wage countries. Production for export is attracted by large internal markets in host countries. Economies of scale in production presumably make large markets economical as export bases. Another factor is high trade propensities of host countries. U.S. firms tend to export from high-wage countries but labor cost is not in general a major influence on the location of export production.
Income shocks, contraceptive use, and timing of fertility

Abstract This paper examines the relationship between income shocks and fertility decisions. Using panel data from Tanzania, we estimate the impact of agricultural shocks on pregnancies, births, and contraception use. The likelihood of pregnancies and childbirth are significantly lower for households that experience a crop shock. Furthermore, women have significantly higher contraception use after crop losses. The increase in contraceptive use comes almost entirely from traditional contraceptive methods, such as abstinence and the rhythm method. We argue that these changes in behavior are the result of deliberate decisions of the households rather than the shocks' effects on other factors that influence fertility, such as women's health status, the absence or migration of a spouse, the dissolution of partnerships, or the number of hours worked. We also show that, although traditional contraceptives have low overall efficacy, households with a strong incentive to postpone fertility are very effective at using them.
Idealizing Reduction: The Microfoundations of Macroeconomics

The dominant view among macroeconomists is that macroeconomics reduces to microeconomics, both in the sense that all macroeconomic phenomena arise out of microeconomic phenomena and in the sense that macroeconomic theory—to the extent that it is correct—can be derived from microeconomic theory. More than that, the dominant view believes that macroeconomics should in practice use the reduced microeconomic theory: this is the program of microfoundations for macroeconomics to which the vast majority of macroeconomists adhere. The “microfoundational” models that they actually employ are, however, characterized by another feature: they are highly idealized, even when they are applied as direct characterizations of actual data, which itself consists of macroeconomic aggregates. This paper explores the interrelationship between reductionism and idealization in the microfoundational program and the role of idealization in empirical modeling.
Keeping Track of Conservation

Throughout the world, governments require land protection in exchange for development permits. Unfortunately, oftentimes scant attention has been paid to these land protection programs after development. Agencies and permit applicants agree on mitigation rules, but there appears to be little follow-up. When we do not know where conservation is occurring and cannot determine the rules of mitigation projects, the likelihood that they will be successful or enforced diminishes. I journeyed to California in search of answers by tracing four mitigation plans associated with the Federal Endangered Species Act. While I anticipated some difficulties, the tale is more alarming than expected. The government entities involved struggled to locate and understand the permits themselves, let alone the details of the compensatory mitigation projects. A common land protection tool in this context is the conservation easement. These exacted conservation easements exchange public goods for private gain. Attempting to locate and understand these mitigation easements revealed pervasive problems with tracking mitigation in the United States. The federal agencies had trouble finding and understanding records. The county offices charged with recording property restrictions often had inadequate records of land use restrictions. These challenges exacerbate the accountability and enforceability concerns already associated with mitigation programs. Such uncertainty calls into question this method of environmental conservation. This Article highlights pressing concerns with our current mitigation paradigm and calls for reform of federal programs through promulgating new regulations and updating agency guidance. Furthermore, this project calls upon citizens and researchers to turn their eyes to mitigation programs generally and to question whether such programs truly compensate for the environmental harms they facilitate.
Mortgage Mistakes? Demographic Factors Associated with Problematic Loan Application Behaviors

Using 2005 Home Mortgage Disclosure Act data, this study explores problematic mortgage application behaviors including submitting incomplete paperwork when seeking a mortgage, withdrawing a loan application before the lender makes a credit decision, rejecting a lender approved loan offer and accepting a high interest rate loan. Tract-level college completion rates, homeownership rates, and household age, as well as race, ethnicity, and income are all associated with problematic loan application behaviors, although these relationships vary across behaviors. The results of this analysis may prove useful for targeting financial education and counseling efforts to areas with the greater potential needs.
The Role of Appraisal in Corporate Law

Appraisal statutes give objecting shareholders the option to sell their shares back to the corporations for "fair value" following certain fundamental corporate changes. Although the specifics of appraisal differ from jurisdiction to jurisdiction, most state appraisal statutes share several basic features: they are triggered by fundamental corporate changes, such as mergers and consolidations; they define "fair value" as the value of the objector's shares prior to giving effect to the triggering transaction; and they frequently include a "market out" which withdraws appraisal rights when the objector's shares are publicly traded. Since Bayless Manning's famous critique of the remedy in 1962, commentators have struggled to explain these and other basic features of appraisal, for the most part arguing that the appraisal remedy should be viewed as a check on misconduct by managers and controlling shareholders. This paper sets out a new theory of appraisal. That theory focuses on the effects, on shareholders who lack effective access to capital markets, of transactions that alter the risk of the firm's shares. As the paper explains, when shareholders lack effective access to capital markets, risk-altering transactions can make some shareholders better off while leaving other shareholders worse off. Appraisal rights require the corporation to compensate shareholders who may be harmed by such transactions and place the net costs of providing that compensation on shareholders who otherwise gain. As a result, shareholders who gain from appraisal-triggering transactions will only vote in favor of those transactions if their gains more than offset the net costs of compensating objectors; appraisal rights therefore decrease the probability of risk-altering transactions that result in net losses to shareholders, causing all shares to trade at higher prices ex ante.
Improving schools through school choice: A market design approach

Abstract We study the effect of different centralized public school choice mechanisms on schools' incentives for quality improvement. To do so, we introduce the following criterion: A mechanism respects improvements of school quality if each school becomes weakly better off whenever that school improves, i.e., becomes more preferred by students. We first show that neither any stable mechanism nor mechanism that is Pareto efficient for students (such as the Boston and top trading cycles mechanisms) respects improvements of school quality. Nevertheless, for large school districts, we demonstrate that any stable mechanism approximately respects improvements of school quality; by contrast, the Boston and top trading cycles mechanisms fail to do so. Thus, a stable mechanism may provide better incentives for schools to improve themselves than the Boston and top trading cycles mechanisms.
Covering numbers of commutative rings

Abstract A cover of a unital, associative (not necessarily commutative) ring R is a collection of proper subrings of R whose set-theoretic union equals R. If such a cover exists, then the covering number σ ( R ) of R is the cardinality of a minimal cover, and a ring R is called σ-elementary if σ ( R ) σ ( R / I ) for every nonzero two-sided ideal I of R. In this paper, we show that if R has a finite covering number, then the calculation of σ ( R ) can be reduced to the case where R is a finite ring of characteristic p and the Jacobson radical J of R has nilpotency 2. Our main result is that if R has a finite covering number and R / J is commutative (even if R itself is not), then either σ ( R ) = σ ( R / J ) , or σ ( R ) = p d + 1 for some d ⩾ 1 . As a byproduct, we classify all commutative σ-elementary rings with a finite covering number and characterize the integers that occur as the covering number of a commutative ring.
Spatial regulation of MCAK promotes cell polarization and focal adhesion turnover to drive robust cell migration

The asymmetric distribution of microtubule (MT) dynamics in migrating cells is important for cell polarization, yet the underlying regulatory mechanisms remain underexplored. Here, we addressed this question by studying the role of the MT depolymerase, MCAK (mitotic centromere-associated kinesin), in the highly persistent migration of RPE-1 cells. MCAK knockdown leads to slowed migration and poor directional movement. Fixed and live cell imaging revealed that MCAK knockdown results in excessive membrane ruffling as well as defects in cell polarization and the maintenance of a major protrusive front. Additionally, loss of MCAK increases the lifetime of focal adhesions by decreasing their disassembly rate. These functions correlate with a spatial distribution of MCAK activity, wherein activity is higher in the trailing edge of cells compared with the leading edge. Overexpression of Rac1 has a dominant effect over MCAK activity, placing it downstream of or in a parallel pathway to MCAK function in migration. Together, our data support a model in which the polarized distribution of MCAK activity and subsequent differential regulation of MT dynamics contribute to cell polarity, centrosome positioning, and focal adhesion dynamics, which all help facilitate robust directional migration.
Provably Safe Trajectory Optimization in the Presence of Uncertain Convex Obstacles

Real-world environments are inherently uncertain, and to operate safely in these environments robots must be able to plan around this uncertainty. In the context of motion planning, we desire systems that can maintain an acceptable level of safety as the robot moves, even when the exact locations of nearby obstacles are not known. In this paper, we solve this chance-constrained motion planning problem using a sequential convex optimization framework. To constrain the risk of collision incurred by planned movements, we employ geometric objects called ϵ-shadows to compute upper bounds on the risk of collision between the robot and uncertain obstacles. We use these ϵ-shadow-based estimates as constraints in a nonlinear trajectory optimization problem, which we then solve by iteratively linearizing the non-convex risk constraints. This sequential optimization approach quickly finds trajectories that accomplish the desired motion while maintaining a user-specified limit on collision risk. Our method can be applied to robots and environments with arbitrary convex geometry; even in complex environments, it runs in less than a second and provides provable guarantees on the safety of planned trajectories, enabling fast, reactive, and safe robot motion in realistic environments.
Various characterizations of throttling numbers

Abstract Zero forcing can be described as a graph process that uses a color change rule in which vertices change white vertices to blue. The throttling number of a graph minimizes the sum of the number of vertices initially colored blue and the number of time steps required to color the entire graph. Positive semidefinite (PSD) zero forcing is a commonly studied variant of standard zero forcing that alters the color change rule. This paper introduces a method for extending a graph using a PSD zero forcing process. Using this extension method, graphs with PSD throttling number at most t are characterized as specific minors of the Cartesian product of complete graphs and trees. A similar characterization is obtained for the minor monotone floor of PSD zero forcing. Finally, the set of connected graphs on n vertices with throttling number at least n − k is characterized by forbidding a finite family of induced subgraphs. These forbidden subgraphs are constructed for standard throttling.
A Stationary Drake Equation Distribution as a Balance of Birth-death Processes

Previous critiques of the Drake Equation have highlighted its deterministic nature, implying that the number of civilizations is the same at all times. Here, I build upon earlier work and present a stochastic formulation. The birth of civilizations within the galaxy is modeled as following a uniform rate (Poisson) stochastic process, with a mean rate of λC. Each then experiences a constant hazard rate of collapse, which defines an exponential distribution with rate parameter λL. Thus, the galaxy is viewed as a frothing landscape of civilization birth and collapse. Under these assumptions, I show that N in the Drake Equation must follow another Poisson distribution, with a mean rate (λC/λL). This is used to demonstrate why the Copernican Principle does not allow one to infer N, as well evaluating the algebraic probability of being alone in the galaxy.
Randomized Controlled Trials

In the medical sciences, the ideal experiment is the randomized controlled clinical trial (RCT) in which the subject or patient is randomized to treatment with an experimental agent or control (either placebo or other active treatment), in a double-blind manner. The RCT is the “gold standard” in medical research to establish the efficacy of a new treatment or intervention. The benefits of such an experiment are that any observed differences between the two groups (or more groups) with respect to the outcome can be attributed to the treatment and are without bias. That is, confounding is controlled and selection bias is removed since neither the subject nor the investigator chooses the intervention. In this entry, we review the issues in the design, conduct, analysis, and interpretation of a randomized clinical trial. Keywords: randomized controlled trial; phase III trial; clinical trial; superiority trial; noninferiority trial; randomization; blinding; intention to treat; multicenter trial
The Quantum Supremacy Tsirelson Inequality

A leading proposal for verifying near-term quantum supremacy experiments on noisy random quantum circuits is linear cross-entropy benchmarking. For a quantum circuit C on n qubits and a sample z ∈ {0,1}ⁿ, the benchmark involves computing |⟨z|C|0ⁿ⟩|², i.e. the probability of measuring z from the output distribution of C on the all zeros input. Under a strong conjecture about the classical hardness of estimating output probabilities of quantum circuits, no polynomial-time classical algorithm given C can output a string z such that |⟨z|C|0ⁿ⟩|² is substantially larger than 1/(2ⁿ) (Aaronson and Gunn, 2019). On the other hand, for a random quantum circuit C, sampling z from the output distribution of C achieves |⟨z|C|0ⁿ⟩|² ≈ 2/(2ⁿ) on average (Arute et al., 2019). In analogy with the Tsirelson inequality from quantum nonlocal correlations, we ask: can a polynomial-time quantum algorithm do substantially better than 2/(2ⁿ)? We study this question in the query (or black box) model, where the quantum algorithm is given oracle access to C. We show that, for any e ≥ 1/poly(n), outputting a sample z such that |⟨z|C|0ⁿ⟩|² ≥ (2 + e)/2ⁿ on average requires at least Ω((2^{n/4})/poly(n)) queries to C, but not more than O (2^{n/3}) queries to C, if C is either a Haar-random n-qubit unitary, or a canonical state preparation oracle for a Haar-random n-qubit state. We also show that when C samples from the Fourier distribution of a random Boolean function, the naive algorithm that samples from C is the optimal 1-query algorithm for maximizing |⟨z|C|0ⁿ⟩|² on average.
The Negotiations of the United Nations Code of Conduct on Transnational Corporations: Experience and Lessons Learned

Many of the issues that are today part of the discussions surrounding international investment agreements were first dealt with when governments sought to negotiate a United Nations Code of Conduct on Transnational Corporations (and various related instruments) almost 40 years ago. The Code was meant to establish a multilateral framework to define, in a balanced manner, the rights and responsibilities of transnational corporations and host country governments in their relations with each other. This article looks at the origins of these negotiations, the underlying interest situations of the participating country groups, the experience of related negotiations, the actual negotiations of the Code, the reasons for the failure of the negotiations, the current situation, and factors driving change. The article concludes with lessons learned from the Code and related negotiations. These lessons may be of interest to current efforts to improve the international investment law and policy regime.
What determines Manager and Investor Sentiment

Abstract This work finds that Managerial and Investor Sentiment are determined by differing sets of economic variables, that share some common factors: inflation, liquidity and the term premium. Decomposing the Sentiment Indices, it is found that the Investor Sentiment Model Component and the Managerial Sentiment Residual Component are primarily responsible for the predictive power of predicting cross-sectional stock returns that is much stronger than previous results. Evidence is presented that part of the predictive power is due to the components predicting priced market factors. Overall, there is strong evidence that the predictive power of Managerial Sentiment is driven primarily by private information, while the predictive power of Investor Sentiment is driven by public information.
Probabilistic Universality in Two-Dimensional Dynamics

In this paper we continue to explore infinitely renormalizable Henon maps with small Jacobian. It was shown in a previous paper by the authors, joint with A. de Carvalho, (J Stat Phys 121(5/6):611–669, 2005) that contrary to the one-dimensional intuition, the Cantor attractor of such a map is non-rigid and the conjugacy with the one-dimensional Cantor attractor is at most 1/2-Holder. Another formulation of this phenomenon is that the scaling structure of the Henon Cantor attractor differs from its one-dimensional counterpart. However, in this paper we prove that the unique invariant measure on the attractor assigns a weight to these bad spots which tends to zero on microscopic scales. This phenomenon is called Probabilistic Universality. It implies, in particular, that the Hausdorff dimension of the invariant measure on the attractor is universal. In this way, universality and rigidity phenomena of one-dimensional dynamics assume a probabilistic nature in the two-dimensional world.
What Happens After A Technology Shock? A Bayesian Perspective

This paper investigates the effect of a positive technology shock on per capita hours worked within the class of Bayesian Vector Auto-Regressive [BVAR] models. Such a framework avoids the current debate regarding the specification issue of per capita hours [level versus first-difference stationary]. Six priors are considered and for each, we examine the impulse responses of per capita hours following a positive technology shock. The marginal posteriors of the VAR parameters are generated using the Markov Chain Monte Carlo (MCMC) Gibbs sampler. We find that the estimation of the VAR yields significantly different estimates under competing priors. Using the Francis and Ramey (2004, UCSD working paper) new measure for per capita hours, and after imposing the identifying restrictions (i.e., Blanchard-Quah and sign restrictions), the results show that per capita hours worked rise following a positive technology shock - if one [objectively] assumes a non-informative prior.
Tropical flag varieties

Abstract Flag matroids are combinatorial abstractions of flags of linear subspaces, just as matroids are of linear subspaces. We introduce the flag Dressian as a tropical analogue of the partial flag variety, and prove a correspondence between: (a) points on the flag Dressian, (b) valuated flag matroids, (c) flags of projective tropical linear spaces, and (d) coherent flag matroidal subdivisions. We introduce and characterize projective tropical linear spaces, which serve as a fundamental tool in our proof. We apply the correspondence to prove that all valuated flag matroids on ground set up to size 5 are realizable, and give an example where this fails for a flag matroid on 6 elements.
Information Flow in Credential Systems

This paper proposes a systematic study of information flow in credential-based declarative authorization policies. It argues that a treatment in terms of information flow is needed to adequately describe, analyze and mitigate a class of probing attacks which allow an adversary to infer any confidential fact within a policy. Two information flow properties that have been studied in the context of state transition systems, non-interference and opacity, are reformulated in the current context of policy languages. A comparison between these properties reveals that opacity is the more useful, and more general of the two; indeed, it is shown that non-interference can be stated in terms of opacity. The paper then presents an inference system for non-opacity, or detectability, in Datalog-based policies. Finally, a pragmatic method is presented, based on a mild modification of the mechanics of delegation, for preventing a particularly dangerous kind of probing attack that abuses delegation of authority.
Synthesis of Zn2NbN3 ternary nitride semiconductor with wurtzite-derived crystal structure.

Binary III-N nitride semiconductors with wurtzite crystal structure such as GaN and AlN have been long used in many practical applications ranging from optoelectronics to telecommunication. The structurally related ZnGeN2or ZnSnN2derived from the parent binary compounds by cation mutation (elemental substitution) have recently attracted attention, but such ternary nitride materials are mostly limited to II-IV-N2compositions. This paper demonstrates synthesis and characterization of zinc niobium nitride (Zn2NbN3)-a previously unreported II2-V-N3ternary nitride semiconductor. The Zn2NbN3thin films are synthesized using a one-step adsorption-controlled growth that locks in the targeted stoichiometry, and a two-step deposition/annealing method that suppresses the loss of Zn and N. Measurements indicate that this sputtered Zn2NbN3crystalizes in cation-disordered wurtzite-derived structure, in contrast to chemically related rocksalt-derived Mg2NbN3compound, also synthesized here for comparison using the two-step method. The estimated wurtzite lattice parameter ratio of Zn2NbN3is 1.55, and the optical absorption onset is at 2.1 eV. Both of these values are lower compared to published Zn2NbN3computational values ofc/a= 1.62 andEg= 3.5-3.6 eV. Additional theoretical calculations indicate that this difference is due to cation disorder in experimental samples, suggesting a way to tune the structural parameters and the resulting properties of heterovalent ternary nitride materials. Overall, this work expands the wurtzite family of nitride semiconductors to include Zn2NbN3, and suggests that related II2-V-N3and other ternary nitrides should be possible to synthesize.
LIDAUS: Localization of IoT Device via Anchor UAV SLAM

We introduce LIDAUS (Localization of IoT Device via Anchor UAV SLAM), an infrastructure-free, multi-stage SLAM system that utilizes an Unmanned Aerial Vehicle (UAV) to accurately localize IoT devices in a 3D indoor space where GPS signals are unavailable or weak, e.g., manufacturing factories, disaster sites, or smart buildings. The lack of GPS signals and infrastructure support makes most of the existing indoor localization systems not practical when localizing a large number of wireless IoT devices. In addition, safety concerns, access restriction, and simply the huge amount of IoT devices make it not practical for humans to manually localize and track IoT devices. To address these challenges, the UAV in our LIDAUS system conducts multi-stage 3D SLAM trips to localize devices based only on RSSIs, the most widely available measurement of the signals of almost all commodity IoT devices. The main novelties of the system include a weighted entropy-based clustering algorithm to select high quality RSSI observation locations, a 3D U-SLAM algorithm that is enhanced by deploying anchor beacons along the UAV’s path, and the path planning based on Eulerian cycles on multi-layer grid graphs that model the space in exploring stage and Steiner tree paths in searching stages. Our simulations and experiments of Bluetooth IoT devices have demonstrated that the system can achieve high localization accuracy based only on RSSIs of commodity IoT devices.
Extremely Small BERT Models from Mixed-Vocabulary Training

Pretrained language models like BERT have achieved good results on NLP tasks, but are impractical on resource-limited devices due to memory footprint. A large fraction of this footprint comes from the input embeddings with large input vocabulary and embedding dimensions. Existing knowledge distillation methods used for model compression cannot be directly applied to train student models with reduced vocabulary sizes. To this end, we propose a distillation method to align the teacher and student embeddings via mixed-vocabulary training. Our method compresses BERT-LARGE to a task-agnostic model with smaller vocabulary and hidden dimensions, which is an order of magnitude smaller than other distilled BERT models and offers a better size-accuracy trade-off on language understanding benchmarks as well as a practical dialogue task.
Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation.

PURPOSE Despite the widespread availability of in-treatment room cone beam computed tomography (CBCT) imaging, due to the lack of reliable segmentation methods, CBCT is only used for gross set up corrections in lung radiotherapies. Accurate and reliable auto-segmentation tools could potentiate volumetric response assessment and geometry-guided adaptive radiation therapies. Therefore, we developed a new deep learning CBCT lung tumor segmentation method. METHODS The key idea of our approach called cross-modality educed distillation (CMEDL) is to use magnetic resonance imaging (MRI) to guide a CBCT segmentation network training to extract more informative features during training. We accomplish this by training an end-to-end network comprised of unpaired domain adaptation (UDA) and cross-domain segmentation distillation networks (SDNs) using unpaired CBCT and MRI datasets. UDA approach uses CBCT and MRI that are not aligned and may arise from different sets of patients. The UDA network synthesizes pseudo MRI from CBCT images. The SDN consists of teacher MRI and student CBCT segmentation networks. Feature distillation regularizes the student network to extract CBCT features that match the statistical distribution of MRI features extracted by the teacher network and obtain better differentiation of tumor from background. The UDA network was implemented with a cycleGAN improved with contextual losses separately on Unet and dense fully convolutional segmentation networks (DenseFCN). Performance comparisons were done against CBCT only using 2D and 3D networks. We also compared against an alternative framework that used UDA with MR segmentation network, whereby segmentation was done on the synthesized pseudo MRI representation. All networks were trained with 216 weekly CBCTs and 82 T2-weighted turbo spin echo MRI acquired from different patient cohorts. Validation was done on 20 weekly CBCTs from patients not used in training. Independent testing was done on 38 weekly CBCTs from patients not used in training or validation. Segmentation accuracy was measured using surface Dice similarity coefficient (SDSC) and Hausdroff distance at 95th percentile (HD95) metrics. RESULTS The CMEDL approach significantly improved (p < 0.001) the accuracy of both Unet (SDSC of 0.83 ± 0.08; HD95 of 7.69 ± 7.86 mm) and DenseFCN (SDSC of 0.75 ± 0.13; HD95 of 11.42 ± 9.87 mm) over CBCT only 2DUnet (SDSC of 0.69 ± 0.11; HD95 of 21.70 ± 16.34 mm), 3D Unet (SDSC of 0.72 ± 0.20; HD95 15.01 ± 12.98 mm), and DenseFCN (SDSC of 0.66 ± 0.15; HD95 of 22.15 ± 17.19 mm) networks. The alternate framework using UDA with the MRI network was also more accurate than the CBCT only methods but less accurate the CMEDL approach. CONCLUSIONS Our results demonstrate feasibility of the introduced CMEDL approach to produce reasonably accurate lung cancer segmentation from CBCT images. Further validation on larger datasets is necessary for clinical translation.
Health spending and vaccination coverage in low-income countries.

INTRODUCTION Routine immunisation is a cost-effective way to save lives and protect people from disease. Some low-income countries (LIC) achieved remarkable success in childhood immunisation. Yet, previous studies comparing the relationship between economic growth and health spending with vaccination coverage have been limited. We investigated these relationships among LIC to understand what financial changes lead to childhood immunisation changes. METHODS We identified which financial indicators were significant predictors of vaccination coverage in LIC by fitting regression models for several vaccines, controlling for population density, land area and female years of education. We then identified LIC with high vaccination coverage (LIC+) and compared their economic and health spending trends with other LIC (LIC-) and lower-middle income countries. We used cross-country multi-year regressions with mixed-effects to test financial indicators' rate of change. We conducted statistical tests to verify if financial trends of LIC+ were significantly different from LIC-. RESULTS During 2014-2018, gross domestic product per capita (p=0.67-0.95, range given by tests with different vaccines), total/private health spending per capita (p=0.57-0.97, p=0.32-0.57) and aggregated development assistance for health (DAH) per capita (p=0.38-0.86) were not significant predictors of vaccination coverage in LIC. Government health spending per capita (p=0.022-0.073) and total/government spending per birth on routine immunisation vaccines (p=0.0007-0.029, p=0.016-0.052) were significant positive predictors of vaccination coverage. From 2000 to 2016, LIC+ increased government health spending per capita by US$0.30 per year, while LIC- decreased by US$0.16 (significant difference, p<0.0001). From 2006 to 2017, LIC+ increased government spending per birth on routine immunisation vaccines by US$0.22 per year, while LIC- increased by US$0.10 (p<0.0093). CONCLUSION Vaccination coverage success of some LIC was not explained by economic development, total health spending nor aggregated DAH. Vaccination coverage success of LIC+ was associated with increasing government health spending particularly in routine immunisation vaccines.
Transfer Learning for Input Estimation of Vehicle Systems

This study proposes a learning-based method with domain adaptability for input estimation of vehicle suspension systems. In a crowdsensing setting for bridge health monitoring, vehicles carry sensors to collect samples of the bridge’s dynamic response. The primary challenge is in preprocessing; signals are highly contaminated from road profile roughness and vehicle suspension dynamics. Additionally, signals are collected from a diverse set of vehicles vitiating model-based approaches. In our data-driven approach, two autoencoders for the cabin signal and the tire-level signal are constrained to force the separation of the tire-level input from the suspension system in the latent state representation. From the extracted features, we estimate the tire-level signal and deter-mine the vehicle class with high accuracy (98% classification accuracy). Compared to existing solutions for the vehicle suspension deconvolution problem, we show that the proposed methodology is robust to vehicle dynamic variations and suspension system nonlinearity.
hu.MAP 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies

A general principle of biology is the self-assembly of proteins into functional complexes. Characterizing their composition is, therefore, required for our understanding of cellular functions. Unfortunately, we lack knowledge of the comprehensive set of identities of protein complexes in human cells. To address this gap, we developed a machine learning framework to identify protein complexes in over 15,000 mass spectrometry experiments which resulted in the identification of nearly 7,000 physical assemblies. We show our resource, hu.MAP 2.0, is more accurate and comprehensive than previous state of the art high-throughput protein complex resources and gives rise to many new hypotheses, including for 274 completely uncharacterized proteins. Further, we identify 253 promiscuous proteins that participate in multiple complexes pointing to possible moonlighting roles. We have made hu.MAP 2.0 easily searchable in a web interface (http://humap2.proteincomplexes.org/), which will be a valuable resource for researchers across a broad range of interests including systems biology, structural biology, and molecular explanations of disease.
Songbirds can learn flexible contextual control over syllable sequencing

Human speech and birdsong share numerous parallels. Both humans and birds learn their vocalizations during critical phases early in life, and both learn by imitating adults. Moreover, both humans and songbirds possess specific circuits in the brain that connect the forebrain to midbrain vocal centers. Humans can flexibly control what they say and how by reordering a fixed set of syllables into endless combinations, an ability critical to human speech and language. Birdsongs also vary depending on their context, and melodies to seduce a mate will be different from aggressive songs to warn other males to stay away. However, so far it was unclear whether songbirds are also capable of modifying songs independent of social or other naturally relevant contexts. To test whether birds can control their songs in a purposeful way, Veit et al. trained adult male Bengalese finches to change the sequence of their songs in response to random colored lights that had no natural meaning to the birds. A specific computer program was used to detect different variations on a theme that the bird naturally produced (for example, “ab-c” versus “ab-d”), and rewarded birds for singing one sequence when the light was yellow, and the other when it was green. Gradually, the finches learned to modify their songs and were able to switch between the appropriate sequences as soon as the light cues changed. This ability persisted for days, even without any further training. This suggests that songbirds can learn to flexibly and purposefully modify the way in which they sequence the notes in their songs, in a manner that parallels how humans control syllable sequencing in speech. Moreover, birds can learn to do this ‘on command’ in response to an arbitrarily chosen signal, even if it is not something that would impact their song in nature. Songbirds are an important model to study brain circuits involved in vocal learning. They are one of the few animals that, like humans, learn their vocalizations by imitating conspecifics. The finding that they can also flexibly control vocalizations may help shed light on the interactions between cognitive processing and sophisticated vocal learning abilities.
Dissociating the effect of reward uncertainty and timing uncertainty on neural indices of reward prediction errors: A reward positivity (RewP) event-related potential (ERP) study.

Abstract Accurate reward predictions include forecasting both what a reward will be and when a reward will occur. We tested how variations in the certainty of reward outcome and certainty in timing of feedback presentation modulate neural indices of reward prediction errors using the reward positivity (RewP) component of the scalp-recorded brain event-related potential (ERP). In a within-subjects design, seventy-three healthy individuals completed two versions of a cued doors task; one cued the probability of a reward outcome while the other cued the probability of a delay before feedback. Replicating previous results, RewP amplitude was larger for uncertain feedback compared to certain feedback. Additionally, RewP amplitude was differentially associated with uncertainty of presence/absence of reward, but not uncertainty of feedback timing. Findings suggest a dissociation in that RewP amplitude is modulated by reward prediction certainty but is less affected by certainty surrounding timing of feedback.
Formation of temporally shaped electron bunches for beam-driven collinear wakefield accelerators

Beam-driven collinear wakefield accelerators (CWAs) that operate by using slow-wave structures or plasmas hold great promise toward reducing the size of contemporary accelerators. Sustainable acceleration of charged particles to high energies in the CWA relies on using field-generating relativistic electron bunches with a highly asymmetric current profile and a large energy chirp. A new approach to obtaining such bunches has been proposed and illustrated with the accelerator design supported by particle tracking simulations. It has been shown that the required particle distribution in the longitudinal phase space can be obtained without collimators, giving CWAs an opportunity for employment in applications requiring a high repetition rate of operation.
Hidden talents: Poly (I:C)-induced maternal immune activation improves mouse visual discrimination performance and reversal learning in a sex-dependent manner.

While there is a strong focus on the negative consequences of maternal immune activation (MIA) on developing brains, very little attention is directed towards potential advantages of early life challenges. In this study, we utilized a polyinosine-polycytidylic acid (poly(I:C)) MIA model to test visual pairwise discrimination (PD) and reversal learning (RL) in mice using touchscreen technology. Significant sex differences emerged in that MIA reduced the latency for males to make a correct choice in the PD task while females reached criterion sooner, made fewer errors, and utilized fewer correction trials in RL compared to saline controls. These surprising improvements were accompanied by the sex-specific upregulation of several genes critical to cognitive functioning, indicative of compensatory plasticity in response to MIA. In contrast, when exposed to a 'two-hit' stress model (MIA + loss of the social component of environmental enrichment [EE]), mice did not display anhedonia but required an increased number of PD and RL correction trials. These animals also had significant reductions of CamK2a mRNA in the prefrontal cortex. Appropriate functioning of synaptic plasticity, via mediators such as this protein kinase and others, are critical for behavioral flexibility. Although EE has been implicated in, delaying the appearance of symptoms associated with certain brain disorders, these findings are in line with evidence that it also makes individuals more vulnerable to its loss. Overall, with the right 'dose', early life stress exposure can confer at least some functional advantages, which are lost when the number or magnitude of these exposures become too great.
Offline Contextual Bandits with Overparameterized Models

Recent results in supervised learning suggest that while overparameterized models have the capacity to overfit, they in fact generalize quite well. We ask whether the same phenomenon occurs for offline contextual bandits. Our results are mixed. Value-based algorithms benefit from the same generalization behavior as overparameterized supervised learning, but policy-based algorithms do not. We show that this discrepancy is due to the action-stability of their objectives. An objective is action-stable if there exists a prediction (action-value vector or action distribution) which is optimal no matter which action is observed. While value-based objectives are action-stable, policy-based objectives are unstable. We formally prove upper bounds on the regret of overparameterized value-based learning and lower bounds on the regret for policy-based algorithms. In our experiments with large neural networks, this gap between action-stable value-based objectives and unstable policy-based objectives leads to significant performance differences.