cssi/SciSciGPT-SciSciNet huggingface dataset:
On the universality of the nonstationary ideal

Burke \cite{MR1472122} proved that the generalized nonstationary ideal, denoted NS, is universal in the following sense: every normal ideal, and every tower of normal ideals of inaccessible height, is a canonical Rudin-Keisler projection of the restriction of $\text{NS}$ to some stationary set. We investigate how far Burke's theorem can be pushed, by analyzing the universality properties of NS with respect to the wider class of \emph{$\mathcal{C}$-systems of filters} introduced by Audrito-Steila \cite{AudritoSteila}. First we answer a question of \cite{AudritoSteila}, by proving that $\mathcal{C}$-systems of filters do not capture all kinds of set-generic embeddings. We provide a characterization of supercompactness in terms of short extenders and canonical projections of NS, without any reference to the strength of the extenders; as a corollary, NS can consistently fail to canonically project to arbitrarily strong short extenders. We prove that $\omega$-cofinal towers of normal ultrafilters---e.g.\ the kind used to characterize I2 and I3 embeddings---are well-founded if and only if they are canonical projections of NS. Finally, we provide a characterization of "$\aleph_\omega$ is Jonsson" in terms of canonical projections of NS.
Frobenius Manifolds from Yang-Mills Instantons

We present an elementary self-contained account of semisimple Frobenius manifolds in three dimensions, and exhibit a new family of explicit examples. These examples are constructed from Yang-Mills instantons with a certain symmetry.
On the B-canonical splittings of flag varieties

Abstract Let G be a semisimple algebraic group over an algebraically closed field of positive characteristic. In this note, we show that an irreducible closed subvariety of the flag variety of G is compatibly split by the unique canonical Frobenius splitting if and only if it is a Richardson variety, i.e. an intersection of a Schubert and an opposite Schubert variety.
The Cauchy Problem for Wave Maps on Hyperbolic Space in Dimensions $d\geq 4$

We establish global well-posedness and scattering for wave maps from $d$-dimensional hyperbolic space into Riemannian manifolds of bounded geometry for initial data that is small in the critical Sobolev space for $d \geq 4$. The main theorem is proved using the moving frame approach introduced by Shatah and Struwe. However, rather than imposing the Coulomb gauge we formulate the wave maps problem in Tao's caloric gauge, which is constructed using the harmonic map heat flow. In this setting the caloric gauge has the remarkable property that the main `gauged' dynamic equations reduce to a system of nonlinear scalar wave equations on $\mathbb{H}^{d}$ that are amenable to Strichartz estimates rather than tensorial wave equations (which arise in other gauges such as the Coulomb gauge) for which useful dispersive estimates are not known. This last point makes the heat flow approach crucial in the context of wave maps on curved domains.
Generalizing Skills with Semi-Supervised Reinforcement Learning.

Deep reinforcement learning (RL) can acquire complex behaviors from low-level inputs, such as images. However, real-world applications of such methods require generalizing to the vast variability of the real world. Deep networks are known to achieve remarkable generalization when provided with massive amounts of labeled data, but can we provide this breadth of experience to an RL agent, such as a robot? The robot might continuously learn as it explores the world around it, even while deployed. However, this learning requires access to a reward function, which is often hard to measure in real-world domains, where the reward could depend on, for example, unknown positions of objects or the emotional state of the user. Conversely, it is often quite practical to provide the agent with reward functions in a limited set of situations, such as when a human supervisor is present or in a controlled setting. Can we make use of this limited supervision, and still benefit from the breadth of experience an agent might collect on its own? In this paper, we formalize this problem as semisupervised reinforcement learning, where the reward function can only be evaluated in a set of "labeled" MDPs, and the agent must generalize its behavior to the wide range of states it might encounter in a set of "unlabeled" MDPs, by using experience from both settings. Our proposed method infers the task objective in the unlabeled MDPs through an algorithm that resembles inverse RL, using the agent's own prior experience in the labeled MDPs as a kind of demonstration of optimal behavior. We evaluate our method on challenging tasks that require control directly from images, and show that our approach can improve the generalization of a learned deep neural network policy by using experience for which no reward function is available. We also show that our method outperforms direct supervised learning of the reward.
Smoke: fine-grained lineage at interactive speed

Data lineage describes the relationship between individual input and output data items of a workflow and is an integral ingredient for both traditional (e.g., debugging or auditing) and emergent (e.g., explanations or cleaning) applications. The core, long-standing problem that lineage systems need to address---and the main focus of this paper---is to quickly capture lineage across a workflow in order to speed up future queries over lineage. Current lineage systems, however, either incur high lineage capture overheads, high lineage query processing costs, or both. In response, developers resort to manual implementations of applications that, in principal, can be expressed and optimized in lineage terms. This paper describes Smoke, an in-memory database engine that provides both fast lineage capture and lineage query processing. To do so, Smoke tightly integrates the lineage capture logic into physical database operators; stores lineage in efficient lineage representations; and employs optimizations if future lineage queries are known up-front. Our experiments on microbenchmarks and realistic workloads show that Smoke reduces the lineage capture overhead and lineage query costs by multiple orders of magnitude as compared to state-of-the-art alternatives. On real-world applications, we show that Smoke meets the latency requirements of interactive visualizations (e.g.,
On the number of linear hypergraphs of large girth

An $r$-uniform \textit{linear cycle} of length $\ell$, denoted by $C_{\ell}^r$, is an $r$-graph with edges $e_1, \ldots, e_{\ell}$ such that for every $i\in [\ell-1]$, $|e_i\cap e_{i+1}|=1$, $|e_{\ell}\cap e_1|=1$ and $e_i\cap e_j=\emptyset$ for all other pairs $\{i, j\},\ i\neq j$. For every $r\geq 3$ and $\ell\geq 4$, we show that there exists a constant $C$ depending on $r$ and $\ell$ such that the number of linear $r$-graphs of girth $\ell$ is at most $2^{Cn^{1+1/\lfloor \ell/2\rfloor}}$. Furthermore, we extend the result for $\ell=4$, proving that there exists a constant $C$ depending on $r$ such that the number of linear $r$-graphs without $C_{4}^r$ is at most $2^{Cn^{3/2}}$. The idea of the proof is to reduce the hypergraph enumeration problems to some graph enumeration problems, and then apply a variant of the graph container method, which may be of independent interest. We extend a breakthrough result of Kleitman and Winston on the number of $C_4$-free graphs, proving that the number of graphs containing at most $n^2/32\log^6 n$ $C_4$'s is at most $2^{11n^{3/2}}$, for sufficiently large $n$. We further show that for every $r\geq 3$ and $\ell\geq 2$, the number of graphs such that each of its edges is contained in only $O(1)$ cycles of length at most $2\ell$, is bounded by $2^{3(\ell+1)n^{1+1/\ell}}$ asymptotically.
GANs for Semi-Supervised Opinion Spam Detection

Online reviews have become a vital source of information in purchasing a service (product). Opinion spammers manipulate reviews, affecting the overall perception of the service. A key challenge in detecting opinion spam is obtaining ground truth. Though there exists a large set of reviews online, only a few of them have been labeled spam or non-spam. In this paper, we propose spamGAN, a generative adversarial network which relies on limited set of labeled data as well as unlabeled data for opinion spam detection. spamGAN improves the state-of-the-art GAN based techniques for text classification. Experiments on TripAdvisor dataset show that spamGAN outperforms existing spam detection techniques when limited labeled data is used. Apart from detecting spam reviews, spamGAN can also generate reviews with reasonable perplexity.
Do Investors Value Higher Financial Reporting Quality, and Can Expanded Audit Reports Unlock This Value?

ABSTRACT We present new theory and experimental findings indicating that investors ascribe value to firms that use higher financial reporting quality (FRQ), controlling for the influence of higher ...
A Model-Based Cost-Effectiveness Analysis of an Exercise Program for Lung Cancer Survivors After Curative-Intent Treatment.

Objective The cost-effectiveness of exercise interventions in lung cancer survivors is unknown. We performed a model-based cost-effectiveness analysis of an exercise intervention in lung cancer survivors. Design We used Markov modeling to simulate the impact of the Lifestyle Interventions and Independence for Elders exercise intervention compared with usual care for stage I-IIIA lung cancer survivors after curative-intent treatment. We calculated and considered incremental cost-effectiveness ratios of less than US $100,000/quality-adjusted life-year as cost-effective and assessed model uncertainty using sensitivity analyses. Results The base-case model showed that the Lifestyle Interventions and Independence for Elders exercise program would increase overall cost by US $4740 and effectiveness by 0.06 quality-adjusted life-years compared with usual care and have an incremental cost-effectiveness ratio of US $79,504/quality-adjusted life-year. The model was most sensitive to the cost of the exercise program, probability of increasing exercise, and utility benefit related to exercise. At a willingness-to-pay threshold of US $100,000/quality-adjusted life-year, Lifestyle Interventions and Independence for Elders had a 71% probability of being cost-effective compared with 27% for usual care. When we included opportunity costs, Lifestyle Interventions and Independence for Elders had an incremental cost-effectiveness ratio of US $179,774/quality-adjusted life-year, exceeding the cost-effectiveness threshold. Conclusions A simulation of the Lifestyle Interventions and Independence for Elders exercise intervention in lung cancer survivors demonstrates cost-effectiveness from an organization but not societal perspective. A similar exercise program for lung cancer survivors may be cost-effective.
Are Budget Rigidities a Source of Fiscal Distress and a Constraint for Fiscal Consolidation

This paper studies whether budget rigidities affect the probability of countries getting into fiscal distress and reduce the likelihood of governments performing fiscal adjustments. Budget rigidities are constraints that limit the ability of the government to change the size and structure of the public budget in the short term. Budget rigidities stem from different institutional arrangements and therefore can take different forms. To build an indicator of rigid spending that is comparable across a large set of countries, this paper employs a simple definition based on budget components that are naturally inflexible: the sum of public wages, pensions, and debt service. It decomposes this measure into a structural component and a nonstructural component. Then, the paper applies a linear probability model to a panel of 182 advanced and developing countries. A key finding is that relatively high shares of rigid (observed) components of public spending contribute to countries getting into fiscal distress and are a constraint for fiscal consolidation. The paper finds evidence that a relatively high share of nonstructural rigid spending contributes to the probability of fiscal distress and reduces the probability of fiscal consolidation. Moreover, the effect of rigid expenditure seems to be more relevant for economies with high inequality, governments with lower margins of majority, and countries with lower institutional quality. In addition, when looking at the composition of the measure of rigid expenditure, there is also some evidence that higher expenditure on pensions reduces the probability of fiscal adjustment more robustly than higher expenditure on wages.
Multivariate Distributionally Robust Convex Regression under Absolute Error Loss

This paper proposes a novel non-parametric multidimensional convex regression estimator which is designed to be robust to adversarial perturbations in the empirical measure. We minimize over convex functions the maximum (over Wasserstein perturbations of the empirical measure) of the absolute regression errors. The inner maximization is solved in closed form resulting in a regularization penalty involves the norm of the gradient. We show consistency of our estimator and a rate of convergence of order $ \widetilde{O}\left( n^{-1/d}\right) $, matching the bounds of alternative estimators based on square-loss minimization. Contrary to all of the existing results, our convergence rates hold without imposing compactness on the underlying domain and with no a priori bounds on the underlying convex function or its gradient norm.
Policy Learning for Fairness in Ranking

Conventional Learning-to-Rank (LTR) methods optimize the utility of the rankings to the users, but they are oblivious to their impact on the ranked items. However, there has been a growing understanding that the latter is important to consider for a wide range of ranking applications (e.g. online marketplaces, job placement, admissions). To address this need, we propose a general LTR framework that can optimize a wide range of utility metrics (e.g. NDCG) while satisfying fairness of exposure constraints with respect to the items. This framework expands the class of learnable ranking functions to stochastic ranking policies, which provides a language for rigorously expressing fairness specifications. Furthermore, we provide a new LTR algorithm called Fair-PG-Rank for directly searching the space of fair ranking policies via a policy-gradient approach. Beyond the theoretical evidence in deriving the framework and the algorithm, we provide empirical results on simulated and real-world datasets verifying the effectiveness of the approach in individual and group-fairness settings.
Coded Elastic Computing

Cloud providers have recently introduced new offerings whereby spare computing resources are accessible at discounts compared to on-demand computing. Exploiting such opportunity is challenging inasmuch as such resources are accessed with low-priority and therefore can elastically leave (through preemption) and join the computation at any time. In this paper, we design a new technique called coded elastic computing enabling distributed computations over elastic resources. The proposed technique allows machines to leave the computation without sacrificing the algorithm-level performance, and, at the same time, flexibly reduce the workload at existing machines when new ones join the computation. Leveraging coded redundancy, our approach is able to achieve similar computational cost as the original (uncoded) method when all machines are present; the cost gracefully increases when machines are preempted and reduces when machines join. The performance of the proposed technique is evaluated on matrix-vector multiplication and linear regression tasks, and shows improvements over existing techniques.
Exponents for the equidistribution of shears and applications

Abstract In [KK18] , the authors introduced “soft” methods to prove the effective (i.e. with power savings error) equidistribution of “shears” in cusped hyperbolic surfaces. In this paper, we study the same problem but now allow full use of the spectral theory of automorphic forms to produce explicit exponents, and uniformity in parameters. We give applications to counting square values of quadratic forms.
Thank you for being a friend: The roles of strong and weak social network ties in attracting backers to crowdfunded campaigns

Abstract This paper uses daily panel data to study the effects that entrepreneurs’ social networks have on the success of their projects seeking capital from a potentially large group of individual investors (i.e. crowdfunding). Much of the literature to date demonstrates both theoretically and empirically that the benefit of large social networks accrues at the beginning of the crowdfunding campaign and are commonly the initial contributions that the project receives. We find this is consistent with unsuccessful campaigns, however, among successful campaigns many of the benefits of large online social networks occur only after the project has met its funding goal. In particular, we find that entrepreneurs with relatively large online social networks receive a statistically significantly larger number of backers only after the project is successfully funded. It is hypothesized this result is due to the composition of strong and weak ties in the entrepreneur’s social network. Importantly, when a project reaches its funding goal a positive signal of its quality is sent to those in the entrepreneur’s social network and motivates the relatively large group of weak ties in it to contribute. As a result, it puts into question the value that strong ties can have in aiding entrepreneurs in reaching their funding goal.
Infinite All-Layers Simple Foldability

We study the problem of deciding whether a crease pattern can be folded by simple folds (folding along one line at a time) under the infinite all-layers model introduced by Akitaya et al. (J Inform Process 25:582–589, 2017), in which each simple fold is defined by an infinite line and must fold all layers of paper that intersect this line. This model is motivated by folding in manufacturing such as sheet-metal bending. We improve on Arkin et al. (Comput Geom Theory Appl 29(1):23–46, 2014) by giving a deterministic O(n)-time algorithm to decide simple foldability of 1D crease patterns in the all-layers model. Then we extend this 1D result to 2D, showing that simple foldability in the infinite all-layers model can be decided in linear time for both unassigned and assigned axis-aligned orthogonal crease patterns on axis-aligned 2D orthogonal paper. On the other hand, we show that simple foldability is strongly NP-complete if a subset of the creases have a mountain–valley assignment, even for axis-aligned rectangular paper.
Incorporating equity into the school bus scheduling problem

Abstract We consider the school bus scheduling problem (SBSP) which simultaneously determines school bell times and route schedules. Often, the goal of the SBSP is to minimize the number of buses required by a school district. We extend a time-indexed integer programming model to incorporate additional considerations related to equity and efficiency. We seek to equitably reduce the disutilities associated with changing school start times via a minimax model, then propose a lexicographic minimax approach to improve minimax solutions. We apply our models to randomized instances based on a moderately-sized public school district to show the impact of incorporating equity.
Effects of the shift to English-only instruction on college outcomes: Evidence from Central Asia

AbstractEnglish-only college education in non-English speaking countries is a rapidly growing phenomenon that has been dubbed as the most important trend in higher education internationalization. D...
How to Create Objects With Your Mind: From Object-Based Attention to Attention-Based Objects:

When staring at a blank grid, one can readily "see" simple shapes-a peculiar experience that does not occur when viewing an empty background. But just what does this "seeing" entail? Previous work has explored many cues to object-based attention (e.g., involving continuity and closure), but here we asked whether attention can be object based even when there are no cues to objecthood. Observers viewed simple grids and attended to particular squares until they could effectively "see" shapes such as a capital H or I. During this scaffolded attention, two probes appeared, and observers reported whether they were the same or different. Remarkably, this produced a traditional same-object advantage: In several experiments (including high-powered direct replications), performance was enhanced for probes presented on the same (purely imagined) object, compared with equidistant probes presented on different objects. We conclude that attention not only operates over objects but also can effectively create object representations.
Lithium pellet injector development for NSTX

A pellet injector suitable for the injection of lithium and other low-Z pellets of varying mass into plasmas at precise velocities from 5 to 500 m/s is being developed for use on NSTX. The ability to inject low-Z impurities will significantly expand NSTX experimental capability for a broad range of diagnostic and operational applications. The architecture employs a pellet-carrying cartridge propelled through a guide tube by deuterium gas. Abrupt deceleration of the cartridge at the end of the guide tube results in the pellet continuing along its intended path, thereby giving controlled reproducible velocities for a variety of pellets materials and a reduced gas load to the torus. The planned injector assembly has four hundred guide tubes contained in a rotating magazine with eight tubes provided for injection into plasmas. A PC-based control system is being developed as well and will be described elsewhere in these Proceedings. The development path and mechanical performance of the injector will be described.
Synthesis of activated carbon of lote wood and study its physical properties

The paper focuses on studying activated carbon and its uses then producing activated carbon using lote wood that is available in Iraq through the process of carbonization. Also, the paper defines the best temperature to produce huge size of coal. Then use the process of carbon activation through Physical activation. The latter process can be done through steam heating or oxygen for 1000 C°. After that, several measurements have been done to measure the efficiency of activated carbon, and other physical checks related to carbon like humidity and percentage of ash. .
Robust Bayesian Approaches in Growth Curve Modeling: Using Student’s t Distributions versus a Semiparametric Method

Despite broad applications of growth curve models, few studies have dealt with a practical issue – nonnormality of data. Previous studies have used Student’s t distributions to remedy the nonnormal...
To stay discovered: On tournament mean score sequences and the Bradley–Terry model

Abstract On being told that a piece of work he thought was his discovery had duplicated an earlier mathematician’s work, Larry Shepp once replied “Yes, but when I discovered it, it stayed discovered.” In this spirit we give discussion and probabilistic proofs of two related known results (Moon 1963, Joe 1988) on random tournaments which seem surprisingly unknown to modern probabilists. In particular, our proof of Moon’s theorem on mean score sequences seems more constructive than previous proofs. This provides a comparatively concrete introduction to a longstanding mystery, the lack of a canonical construction for a joint distribution in the representation theorem for convex order.
Bordered theory for pillowcase homology

We construct an algebraic version of Lagrangian Floer homology for immersed curves inside the pillowcase. We first associate to the pillowcase an algebra A. Then to an immersed curve L inside the pillowcase we associate an A infinity module M(L) over A. Then we prove that Lagrangian Floer homology HF(L,L') is isomorphic to a suitable algebraic pairing of modules M(L) and M(L'). This extends the pillowcase homology construction - given a 2-stranded tangle inside a 3-ball, if one obtains an immersed unobstructed Lagrangian inside the pillowcase, one can further associate an A infinity module to that Lagrangian.
An Appreciative Inquiry Approach to the Core Competencies: Taking it From Theory to Practice.

Objective To operationalize the surgical core competencies by using a qualitative inquiry strategy to explore how surgical competence is behaviorally demonstrated by faculty. Design Categorical general and vascular surgery residents completed a survey soliciting opinions regarding which faculty were deemed most representative of each core competency. The surveys served as a theoretical sample, as surgeons selected were then interviewed, and interviews transcribed. A qualitative research approach using grounded theory coding methods was used for transcript analysis. Iterative coding was performed, and emergent themes were then extracted from transcript analysis. Setting Southern Illinois University School of Medicine, Department of Surgery in Springfield, IL, a tertiary academic center. Participants Fourteen of 19 residents completed the survey (74% response rate). Two surgeons were selected for each competency. A total of 7 interviews were performed, with 4 surgeons being chosen for 2 competencies. Results Emergent themes revealed that competent surgeons shared qualities that drove their development and execution of each competency. These qualities included self-awareness, a selfless character, responsibility and ownership, context awareness, reliance on relationships and community, and a pattern of habit formation and discipline. Additionally, the competencies were noted to be pursued in an interrelated and interdependent fashion. Conclusions Surgeons deemed competent in any core domain shared common qualities. Further study exploring how each of these is identified, developed and taught is warranted. The competencies are an inter-related matrix whose development and execution correlates with foundational personal disciplines.
A Chance-Constrained Stochastic Electricity Market

Efficiently accommodating uncertain renewable resources in wholesale electricity markets is among the foremost priorities of market regulators in the US, UK and EU nations. However, existing deterministic market designs fail to internalize the uncertainty and their scenario-based stochastic extensions are limited in their ability to simultaneously maximize social welfare and guarantee non-confiscatory market outcomes in expectation and per each scenario. This article proposes a chance-constrained stochastic market design, which is capable of producing a robust competitive equilibrium and internalizing uncertainty of the renewable resources in the price formation process. The equilibrium and resulting prices are obtained for different uncertainty assumptions, which requires using either linear (restrictive assumptions) or second-order conic (more general assumptions) duality in the price formation process. The usefulness of the proposed stochastic market design is demonstrated via the case study carried out on the 8-zone ISO New England testbed.
Tameness from two successive good frames

We show, assuming a mild set-theoretic hypothesis, that if an abstract elementary class (AEC) has a superstable-like forking notion for models of cardinality λ and a superstable-like forking notion for models of cardinality λ+, then orbital types over models of cardinality λ+ are determined by their restrictions to submodels of cardinality λ. By a superstable-like forking notion, we mean here a good frame, a central concept of Shelah’s book on AECs. It is known that locality of orbital types together with the existence of a superstable-like notion for models of cardinality λ implies the existence of a superstable-like notion for models of cardinality λ+, and here we prove the converse. An immediate consequence is that forking in λ+ can be described in terms of forking in λ.
Dual-mode dynamic window approach to robot navigation with convergence guarantees

In this paper, a novel, dual-mode model predictive control framework is introduced that combines the dynamic window approach to navigation with generic path planning techniques through a dual-mode ...
Validity of a Special Education Teacher Observation System

This manuscript describes the comprehensive validation work undertaken to develop the Recognizing Effective Special Education Teachers (RESET) observation system, which was designed to provide eval...
Counting 3-stack-sortable permutations

Abstract We prove a “decomposition lemma” that allows us to count preimages of certain sets of permutations under West's stack-sorting map s. As a first application, we give a new proof of Zeilberger's formula for the number W 2 ( n ) of 2-stack-sortable permutations in S n . Our proof generalizes, allowing us to find an algebraic equation satisfied by the generating function that counts 2-stack-sortable permutations according to length, number of descents, and number of peaks. This is also the first proof of this formula that generalizes to the setting of 3-stack-sortable permutations. Indeed, the same method allows us to obtain a recurrence relation for W 3 ( n ) , the number of 3-stack-sortable permutations in S n . Hence, we obtain the first polynomial-time algorithm for computing these numbers. We compute W 3 ( n ) for n ≤ 174 , vastly extending the 13 terms of this sequence that were known before. We also prove the first nontrivial lower bound for lim n → ∞ ⁡ W 3 ( n ) 1 / n , showing that it is at least 8.659702. Invoking a result of Kremer, we also prove that lim n → ∞ ⁡ W t ( n ) 1 / n ≥ ( t + 1 ) 2 for all t ≥ 1 , which we use to improve a result of Smith concerning a variant of the stack-sorting procedure. Our computations allow us to disprove a conjecture of Bona, although we do not yet know for sure which one. In fact, we can refine our methods to obtain a recurrence for W 3 ( n , k , p ) , the number of 3-stack-sortable permutations in S n with k descents and p peaks. This allows us to gain a large amount of evidence supporting a real-rootedness conjecture of Bona. Using part of the theory of valid hook configurations, we give a new proof of a γ-nonnegativity result of Branden, which in turn implies an older result of Bona. We then answer a question of the current author by producing a set A ⊆ S 11 such that ∑ σ ∈ s − 1 ( A ) x des ( σ ) has nonreal roots. We interpret this as partial evidence against the same real-rootedness conjecture of Bona that we found evidence supporting. Examining the parities of the numbers W 3 ( n ) , we obtain strong evidence against yet another conjecture of Bona. We end with some conjectures of our own.
A Model-Predictive Control Method for Coordinating Virtual Power Plants and Packetized Resources, with Hardware-in-the-Loop Validation

In this paper, we employ a bi-level control system to react to disturbances and balance power mismatch by coordinating distributed energy resources (DERs) under packetized energy management. Packetized energy management (PEM) is a novel bottom-up asynchronous and randomizing coordination paradigm for DERs that guarantees quality of service, autonomy, and privacy to the end-user. A hardware-in-the-loop (HIL) simulation of a cyber-physical system consisting of PEM enabled DERs, flexible virtual power plants (VPPs) and transmission grid is developed in this work. A predictive, energy-constrained dispatch of aggregated PEM-enabled DERs is formulated, implemented, and validated on the HIL cyber-physical platform. The energy state of VPPs, composed of a fleet of diverse DERs distributed in the grid, depend upon the distinct real-time usage of these devices. The experimental results demonstrate that the existing control schemes, such as AGC, dispatch VPPs without regard to their energy state, which leads to unexpected capacity saturation. By accounting for the energy states of VPPs, model-predictive control (MPC) can optimally dispatch conventional generators and VPPs to overcome disturbances while avoiding undesired capacity saturation. The results show the improvement in dynamics by using MPC over conventional AGC and droop for a system with energy-constrained resources.
Thermodynamic Limit for Polydisperse Fluids

We examine the thermodynamic limit of fluids of hard core particles that are polydisperse in size and shape. In addition, particles may interact magnetically. Free energy of such systems is a random variable because it depends on the choice of particles. We prove that the thermodynamic limit exists with probability 1, and is independent of the choice of particles. Our proof applies to polydisperse hard-sphere fluids, colloids and ferrofluids. The existence of a thermodynamic limit implies system shape and size independence of thermodynamic properties of a system.
Foreclosed American Dream? Parental Foreclosure and Young Adult Children’s Homeownership

In this study, I investigated the homeownership decisions of young adult children who experienced parental foreclosure. Results from a linear probability model using data from the Panel Study of Income Dynamics showed that young adults were less likely to become homeowners following parental foreclosure and that foreclosures between 2009 and 2011 had the strongest negative effects. Young adults who lived in low-foreclosure states, who lived outside their parents’ county, and who were more financially prepared were affected more. This evidence suggests that the parental foreclosure effect was unlikely to operate through common economic shocks at the state or county level or through parental financial transfers, implying potential psychological effects of parental foreclosure. These findings reveal an intergenerational correlation of negative housing experiences and highlight the importance of designing and providing counseling services not only for owners of foreclosed homes but also for their family members.
cRacle: R tools for estimating climate from vegetation

Premise The Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE) method utilizes a robust set of modeling tools for estimating climate and paleoclimate from vegetation using large repositories of biodiversity data and open access R software. Methods Here, we implement a new R package for the estimation of climate from extant and fossil vegetation. The 'cRacle' package implements functions for data access, aggregation, and modeling to estimate climate from plant community compositions. 'cRacle' is modular and includes many best-practice features. Results Performance tests using modern vegetation survey data from North and South America shows that CRACLE outperforms alternative methods. CRACLE estimates of mean annual temperature are usually within 1°C of the actual values when optimal model parameters are used. Generalized boosted regression (GBR) model correction improves CRACLE estimates by reducing bias. Discussion CRACLE provides accurate estimates of climate based on the composition of modern plant communities. Non-parametric CRACLE modeling coupled with GBR model correction produces the most accurate results to date. The 'cRacle' R package streamlines the estimation of climate from plant community data, which will make this modeling more accessible to a wider range of users.
Complete families of immersed curves

We extend results of Chang and Ran regarding large dimensional families of immersed curves of positive genus in projective space in two directions. In one direction, we prove a sharp bound for the dimension of a complete family of smooth rational curves immersed into projective space, completing the picture in projective space. In another direction, we isolate the necessary positivity condition on the tangent bundle of projective space used to run the argument, which allows us to rule out large dimensional families of immersed curves of positive genus in generalized flag varieties.
School connectedness and child anxiety

Poor school connectedness (SC), defined as students’ feelings of belonging, safety, and fairness at school, is a risk factor for negative psychosocial outcomes. Few studies have examined the specific relationship between SC and anxiety. This study examined the relation between SC and anxiety within a group of 114 clinically anxious youth (mean age = 10.82; SD = 2.93; 48.2% female; 70.2% White, non-Hispanic); age differences were also examined. Results indicated that SC was significantly negatively associated with age but unrelated to gender, race/ethnicity, socio-economic status, parent education, or presence of a comorbid disorder. Findings generally revealed that low SC was associated with greater total and domain specific anxiety. SC may play a unique role in the maintenance of global and domain specific anxiety symptoms.
Detectability of Intermittent Zero-Dynamics Attack in Networked Control Systems

This paper analyzes stealthy attacks, particularly the zero-dynamics attack (ZDA) in networked control systems. ZDA hides the attack signal in the null-space of the state-space representation of the control system and hence it cannot be detected via conventional detection methods. A natural defense strategy builds on changing the null-space via switching through a set of topologies. In this paper, we propose a realistic ZDA variation where the attacker is aware of this topology-switching strategy, and hence employs the policy to avoid detection: "pause (update and resume) attack" before (after) topology switching to evade detection. We first systematically study the proposed ZDA variation, and then develop defense strategies under the realistic assumptions. Particularly, we characterize conditions for detectability of the proposed ZDA variation, in terms of the network topologies to be maintained, the set of agents to be monitored, and the measurements of the monitored agents that should be extracted. We provide numerical results that demonstrate our theoretical findings.
Joint Access and Backhaul Resource Management in Satellite-Drone Networks: A Competitive Market Approach

In this paper, the problem of user association and resource allocation is studied for an integrated satellite-drone network (ISDN). In the considered model, drone base stations (DBSs) provide downlink connectivity to ground users whose demand cannot be satisfied by terrestrial small cell base stations (SBSs). Meanwhile, a satellite system and a set of terrestrial macrocell base stations (MBSs) are used to provide resources for backhaul connectivity for both DBSs and SBSs. For this scenario, one must jointly consider resource management over satellite-DBS/SBS backhaul links, MBS-DBS/SBS terrestrial backhaul links, and DBS/SBS-user radio access links as well as user association with DBSs and SBSs. This joint user association and resource allocation problem is modeled using a competitive market setting in which the transmission data is considered as a good that is being exchanged between users, DBSs, and SBSs that act as “buyers”, and DBSs, SBSs, MBSs, and the satellite that act as “sellers”. In this market, the quality-of-service (QoS) is used to capture the quality of the data transmission (defined as good), while the energy consumption the buyers use for data transmission is the cost of exchanging a good. According to the quality of goods, sellers in the market propose quotations to the buyers to sell their goods, while the buyers purchase the goods based on the quotation. The buyers profit from the difference between the earned QoS and the charged price, while the sellers profit from the difference between earned price and the energy spent for data transmission. The buyers and sellers in the market seek to reach a Walrasian equilibrium, at which all the goods are sold, and each of the devices’ profit is maximized. A heavy ball based iterative algorithm is proposed to compute the Walrasian equilibrium of the formulated market. Analytical results show that, with well-defined update step sizes, the proposed algorithm is guaranteed to reach one Walrasian equilibrium. Simulation results show that, at the achieved Walrasian equilibrium solution, the proposed algorithm can yield a two-fold gain in terms of the number of radio access links with a data rate of over 40 Mbps, and a three-fold gain in terms of the number of backhaul links with a data rate greater than 1.6 Gbps.
2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans: A report of the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology.

The Society of Cardiovascular Computed Tomography (SCCT) and the Society of Thoracic Radiology (STR) have jointly produced this document. Experts in this subject have been selected from both organizations to examine subject-specifc data and write this guideline in partnership. A formal literature review, weighing the strength of evidence has been performed. When available, information from studies on cost was considered. Computed tomography (CT) acquisition, CAC scoring methodologies and clinical outcomes are the primary basis for the recommendations in this guideline. This guideline is intended to assist healthcare providers in clinical decision making. The recommendations refect a consensus after a thorough review of the best available current scientifc evidence and practice patterns of experts in the feld and are intended to improve patient care while acknowledging that situations arise where additional information may be needed to better inform patient care.
Twofold π-Extension of Polyarenes via Double and Triple Radical Alkyne peri-Annulations: Radical Cascades Converging on the Same Aromatic Core.

A versatile synthetic route to distannyl-substituted polyarenes was developed via double radical peri-annulations. The cyclization precursors were equipped with propargylic OMe traceless directing ...
Golgi Outposts Locally Regulate Microtubule Orientation in Neurons but Are Not Required for the Overall Polarity of the Dendritic Cytoskeleton.

Golgi are emerging as key regulators of acentrosomal microtubule networks. In neurons, the role of dendrite-specific Golgi outposts in creating or maintaining the unique organization of the dendritic cytoskeleton is an open question... Microtubule-organizing centers often play a central role in organizing the cellular microtubule networks that underlie cell function. In neurons, microtubules in axons and dendrites have distinct polarities. Dendrite-specific Golgi "outposts," in particular multicompartment outposts, have emerged as regulators of acentrosomal microtubule growth, raising the question of whether outposts contribute to establishing or maintaining the overall polarity of the dendritic microtubule cytoskeleton. Using a combination of genetic approaches and live imaging in a Drosophila model, we found that dendritic microtubule polarity is unaffected by eliminating known regulators of Golgi-dependent microtubule organization including the cis-Golgi matrix protein GM130, the fly AKAP450 ortholog pericentrin-like protein, and centrosomin. This indicates that Golgi outposts are not essential for the formation or maintenance of a dendrite-specific cytoskeleton. However, the overexpression of GM130, which promotes the formation of ectopic multicompartment units, is sufficient to alter dendritic microtubule polarity. Axonal microtubule polarity is similarly disrupted by the presence of ectopic multicompartment Golgi outposts. Notably, multicompartment outposts alter microtubule polarity independently of microtubule nucleation mediated by the γ-tubulin ring complex. Thus, although Golgi outposts are not essential to dendritic microtubule polarity, altering their organization correlates with changes to microtubule polarity. Based on these data, we propose that the organization of Golgi outposts is carefully regulated to ensure proper dendritic microtubule polarity.
End-To-End Non-Negative Autoencoders for Sound Source Separation

Discriminative models for source separation have recently been shown to produce impressive results. However, when operating on sources outside of the training set, these models can not perform as well and are cumbersome to update. Classical methods like Nonnegative Matrix Factorization (NMF) provide modular approaches to source separation that can be easily updated to adapt to new mixture scenarios. In this paper, we generalize NMF to develop end-to-end non-negative auto-encoders and demonstrate how they can be used for source separation. Our experiments indicate that these models deliver comparable separation performance to discriminative approaches, while retaining the modularity of NMF and the modeling flexibility of neural networks.
Large sample properties of the regression depth induced median

Abstract Notions of depth in regression have been introduced and studied in the literature. Regression depth (RD) of Rousseeuw and Hubert (1999), the most famous one, is a direct extension of Tukey location depth (Tukey, 1975) to regression. Like its location counterpart, the most remarkable advantage of the notion of depth in regression is to directly introduce the maximum (or deepest) regression depth estimator (aka depth induced median) for regression parameters in a multi-dimensional setting. Classical questions for the regression depth induced median include (i) is it a consistent estimator (or rather under what sufficient conditions, it is consistent)? and (ii) is there any limiting distribution? Bai and He (1999) (BH99) pioneered an attempt to answer these questions. Under some stringent conditions on (i) the design points, (ii) the conditional distributions of y given x i , and (iii) the error distributions, BH99 proved the strong consistency of the depth induced median. Under another set of conditions, BH99 showed the existence of the limiting distribution of the estimator. This article establishes the strong consistency of the depth induced median without any of the stringent conditions in BH99, and proves the existence of the limiting distribution of the estimator by sufficient conditions and an approach different from BH99.
Wind drives temporal variation in pollinator visitation in a fragmented tropical forest

Wind is a critical factor in the ecology of pollinating insects such as bees. However, the role of wind in determining patterns of bee abundance and floral visitation rates across space and time is...
The trajectory of gait development in mice

Objective Gait irregularities are prevalent in neurodevelopmental disorders (NDDs). However, there is a paucity of information on gait phenotypes in NDD experimental models. This is in part due to the lack of understanding of the normal developmental trajectory of gait maturation in the mouse. Materials and methods Using the DigiGait system, we have developed a quantitative, standardized, and reproducible assay of developmental gait metrics in commonly used mouse strains that can be added to the battery of mouse model phenotyping. With this assay, we characterized the trajectory of gait in the developing C57BL/6J and FVB/AntJ mouse lines. Results In both lines, a mature stride consisted of 40% swing and 60% stance in the forelimbs, which mirrors the mature human stride. In C57BL/6J mice, developmental trajectories were observed for stance width, paw overlap distance, braking and propulsion time, rate of stance loading, peak paw area, and metrics of intraindividual variability. In FVB/AntJ mice, developmental trajectories were observed for percent shared stance, paw overlap distance, rate of stance loading, and peak paw area, although in different directions than C57 mice. By accounting for the impact of body length on stride measurements, we demonstrate the importance of considering body length when interpreting gait metrics. Conclusion Overall, our results show that aspects of mouse gait development parallel a timeline of normal human gait development, such as the percent of stride that is stance phase and swing phase. This study may be used as a standard reference for developmental gait phenotyping of murine models, such as models of neurodevelopmental disease.