cssi/SciSciGPT-SciSciNet huggingface dataset:
Room-temperature observation and current control of skyrmions in Pt/Co/Os/Pt thin films

We report the observation of room-temperature magnetic skyrmions in Pt/Co/Os/Pt thin-film heterostructures and their response to electric currents. The magnetic properties are extremely sensitive to inserting thin Os layers between the Co-Pt interface, resulting in reduced saturation magnetization, magnetic anisotropy, and Curie temperature. The observed skyrmions exist in a narrow temperature, applied-field and layer-thickness range near the spin-reorientation transition from perpendicular to in-plane magnetic anisotropy. The skyrmions have an average diameter of $2.3\phantom{\rule{0.16em}{0ex}}\ensuremath{\mu}\mathrm{m}$ and transport measurements demonstrate these features can be displaced by means of spin-orbit torques with current densities as low as $J=2\ifmmode\times\else\texttimes\fi{}{10}^{8}\phantom{\rule{0.16em}{0ex}}\mathrm{A}/{\mathrm{m}}^{2}$ and display a skyrmion Hall effect.
On Positivity of Kauffman Bracket Skein Algebras of Surfaces

We show that the Chebyshev polynomials form a basic block of any positive basis of the Kauffman bracket skein algebras of surfaces.
Reflecting on Japan’s contributions to management theory

Although Japanese management’s transformative impact on American managerial practice has long been recognized, its contribution to management theory in a range of fields has been less widely acknowledged. This article looks back on the influence of Japanese management on concepts, frameworks, and theories in four management fields: organization behaviour/organization studies, production and operations management, strategy, and international business. The review reveals three ways in which Japanese management had a significant influence on the development of management theory: legitimating and enriching one position in a contested management field; inspiring novel management concepts and frameworks; and providing rich data for testing and refining hypotheses based on established theory.
Variability in X-ray line ratios in helium-like ions of massive stars: the radiation-driven case

Context. Line ratios in “fir” triplets of helium-like ions have proven to be a powerful diagnostic of conditions in X-ray emitting gas surrounding massive stars. Recent observations indicate that these ratios can be variable with time. Aims. The possibilities for causes of variation in line ratios are limited: changes in the radiation field or changes in density, which would result in radiational or collisional level-pumping, respectively; and changes in mass-loss or geometry, which could cause variations in X-ray absorption effects. In this paper, we explore the first of these potential causes of variability: changes in the radiation field. We therefore explore the conditions necessary to induce variability in the ratio R = f /i via this mechanism. Methods. To isolate the radiative effect, we use a heuristic model of temperature and radius changes in variable stars in the B and O range with low-density, steady-state winds. We then model the changes in emissivity of X-ray emitting gas close to the star due to differences in level-pumping owing to the availability of UV photons at the location of the gas. Results. We find that under these conditions, variability in R is dominated by the stellar temperature. Although the relative amplitude of variability is roughly comparable for most lines at most temperatures, detectable variations are limited to a few lines for each spectral type. We predict that variable values in R due to stellar variability must follow predictable trends found in our simulations. Conclusions. Our heuristic model uses radial pulsations as a mode of stellar variability that maximizes the amplitude of variation in R. This model is robust enough to provide a guide to which ions will provide the best opportunity for observing variability in the f /i ratio at different stellar temperatures, and the correlation of that variability with other observable parameters. In real systems, however, the effects would be more complex than in our model, with differences in phase and suppressed amplitude in the presence of non-radial pulsations. This, combined with the range of amplitudes produced in our simulations, suggests that changes in R across many lines concurrently are not likely to be produced by a variable radiation field.
Patients’ views on variants of uncertain significance across indications

As genomic sequencing expands into more areas of patient care, an increasing number of patients learn of the variants of uncertain significance (VUSs) that they carry. Understanding the potential psychosocial consequences of the disclosure of a VUS can help inform pre- and post-test counseling discussions. Medical uncertainty in general elicits a variety of responses from patients, particularly in the growing field of medical genetics and genomics. It is important to consider patients’ responses to the ambiguous nature of VUSs across different indications and situational contexts. Genetic counselors and other providers ordering genetic testing should be prepared for the possibility of their patients’ misinterpretation of such results. Pre-test counseling should include a discussion of the possibility of VUSs and what it would mean for the patient’s care and its potential psychosocial impacts. When a VUS is found, post-test counseling should include additional education and a discussion of the variant’s implications and medical management recommendations based on the results. These discussions may help temper subjective interpretations, unrealistic views, and decisional regret.
Open Domain Web Keyphrase Extraction Beyond Language Modeling

This paper studies keyphrase extraction in real-world scenarios where documents are from diverse domains and have variant content quality. We curate and release OpenKP, a large scale open domain keyphrase extraction dataset with near one hundred thousand web documents and expert keyphrase annotations. To handle the variations of domain and content quality, we develop BLING-KPE, a neural keyphrase extraction model that goes beyond language understanding using visual presentations of documents and weak supervision from search queries. Experimental results on OpenKP confirm the effectiveness of BLING-KPE and the contributions of its neural architecture, visual features, and search log weak supervision. Zero-shot evaluations on DUC-2001 demonstrate the improved generalization ability of learning from the open domain data compared to a specific domain.
Rate-distortion functions of non-stationary Markoff chains and their block-independent approximations

It is proved that the limit of the normalized rate-distortion functions of block independent approximations of an irreducible, aperiodic Markoff chain is independent of the initial distribution of the Markoff chain and thus, is also equal to the rate-distortion function of the Markoff chain.
Does data cleaning improve brain state classification

Abstract Background Neuroscientists routinely seek to identify and remove noisy or artifactual observations from their data. They do so with the belief that removing such data improves power to detect relations between neural activity and behavior, which are often subtle and can be overwhelmed by noise. Whereas standard methods can exclude certain well-defined noise sources (e.g., 50/60 Hz electrical noise), in many situations there is not a clear difference between noise and signals so it is not obvious how to separate the two. Here we ask whether methods routinely used to “clean” human electrophysiological recordings lead to greater power to detect brain–behavior relations. New method This, to the authors’ knowledge, is the first large-scale simultaneous evaluation of multiple commonly used methods for removing noise from intracranial EEG recordings. Results We find that several commonly used data cleaning methods (automated methods based on statistical signal properties and manual methods based on expert review) do not increase the power to detect univariate and multivariate electrophysiological biomarkers of successful episodic memory encoding, a well-characterized broadband pattern of neural activity observed across the brain. Comparison with existing methods Researchers may be more likely to increase statistical power to detect physiological phenomena of interest by allocating resources away from cleaning noisy data and toward collecting more within-patient observations. Conclusions These findings highlight the challenge of partitioning signal and noise in the analysis of brain-behavior relations, and suggest increasing sample size and numbers of observations, rather than data cleaning, as the best approach to improving statistical power.
A New Design of Private Information Retrieval for Storage Constrained Databases

Private information retrieval (PIR) allows a user to download one of K messages from N databases without revealing to any database which of the K messages is being downloaded. In general, the databases can be storage constrained where each database can only store up to µKL bits where $\frac{1}{N} \leq \mu \leq 1$ and L is the size of each message in bits. Let t = µN, a recent work showed that the capacity of Storage Constrained PIR (SC-PIR) is ${\left( {1 + \frac{1}{t} + \frac{1}{{{t^2}}} + \cdots + \frac{1}{{{t^{K - 1}}}}} \right)^{ - 1}}$, which is achieved by a storage placement scheme inspired by the content placement scheme in the literature of coded caching and the original PIR scheme. Not surprisingly, this achievable scheme requires that each message isbits in length, which can be impractical. In this paper, without trying to make the connection between SC-PIR and coded caching problems, based on a general connection between the Full Storage PIR (FS-PIR) problem (µ = 1) and SC-PIR problem, we propose a new SC-PIR design idea using novel storage placement schemes. The proposed schemes significantly reduce the message size requirement while still meeting the capacity of SC-PIR. In particular, the proposed SC-PIR schemes require the size of each file to be only L = NtK−1 compared to the state-of-the-art $L = \binom {N} {t} {t^K}$.
Monotonicity properties for two-action partially observable Markov decision processes on partially ordered spaces

Abstract This paper investigates monotonicity properties of optimal policies for two-action partially observable Markov decision processes when the underlying (core) state and observation spaces are partially ordered. Motivated by the desirable properties of the monotone likelihood ratio order in imperfect information settings, namely the preservation of belief ordering under conditioning on any new information, we propose a new stochastic order (a generalization of the monotone likelihood ratio order) that is appropriate for when the underlying space is partially ordered. The generalization is non-trivial, requiring one to impose additional conditions on the elements of the beliefs corresponding to incomparable pairs of states. The stricter conditions in the proposed stochastic order reflect a conservation of structure in the problem – the loss of structure from relaxing the total ordering of the state space to a partial order requires stronger conditions with respect to the ordering of beliefs. In addition to the proposed stochastic order, we introduce a class of matrices, termed generalized totally positive of order 2, that are sufficient for preserving the order. Our main result is a set of sufficient conditions that ensures existence of an optimal policy that is monotone on the belief space with respect to the proposed stochastic order.
Quantum matrix diagonalization visualized

We show how to visualize the process of diagonalizing the Hamiltonian matrix to find the energy eigenvalues and eigenvectors of a generic one-dimensional quantum system. Starting in the familiar sine-wave basis of an embedding infinite square well, we display the Hamiltonian matrix graphically with the basis functions alongside. Each step in the diagonalization process consists of selecting a nonzero off-diagonal matrix element and then rotating the two corresponding basis vectors in their own subspace until this element is zero. We provide mathematica code to display the effects of these rotations on both the matrix and the basis functions. As an electronic supplement, we also provide a javascript web app to interactively carry out this process.
Failing Faithful Representations of Financial Statements: Issues in Reporting Financial Instruments

Both the International Financial Reporting Standards (IFRS) and the codified accounting standards (ASC) for the US GAAP categorize hedging relationships as falling into several buckets. The two buckets of relevance in this paper are (i) hedging the volatility of fair values, and (ii) hedging the volatility of future cash flow. In this paper, I argue that at least three accounting treatments of derivatives and hedging lead to creating serious distortion of reporting actual transactions, to combining hard and plastic valuations, and to violating adherence to the principle of 'faithful representation'. The three accounting treatments are as follows: (1) creating the fictional Hypothetical Derivatives Method; (2) allowing for the establishment of purely discretionary valuation adjustments for all over‐the‐counter derivative assets (Credit Valuation Adjustment) and liabilities (Debt Valuation Adjustment) without any guides or constraints; (3) requiring subjective metaphysical separation of embedded derivatives with the main guide being the management's own perception of the instrument's embodiment of unrelated value and risk generators. To remedy the resulting distortion in financial reporting, significant revisions of certain accounting standards are sorely needed. [ABSTRACT FROM AUTHOR]
Skin closure with dye-enhanced laser welding and fibrinogen.

The topical application of wavelength-specific dye and fibrinogen has been used to enhance laser closure of vascular anastomoses. We compared the closure of skin incisions by two different dye-enhanced, fibrinogen-based laser welding systems [argon laser (power density 4.78 W/cm2) with fluorescein i
Tracking Paths in Planar Graphs

We consider the NP-complete problem of tracking paths in a graph, first introduced by Banik et. al. [3]. Given an undirected graph with a source $s$ and a destination $t$, find the smallest subset of vertices whose intersection with any $s-t$ path results in a unique sequence. In this paper, we show that this problem remains NP-complete when the graph is planar and we give a 4-approximation algorithm in this setting. We also show, via Courcelle's theorem, that it can be solved in linear time for graphs of bounded-clique width, when its clique decomposition is given in advance.
Inner And Outer Retinal Mechanisms Engaged By Epiretinal Stimulation In Normal and rd Mice

Retinal prosthetic devices are being developed to bypass degenerated retinal photoreceptors by directly activating retinal neurons with electrical stimulation. However, the retinal circuitry that is activated by epiretinal stimulation is not well characterized. Whole-cell patch clamp recordings were obtained from ganglion cells in normal and rd mice using flat-mount and retinal slice preparations. A stimulating electrode was positioned along the ganglion cell side of the preparation at different distances from the stimulated tissue. Pulses of cathodic current evoked action potentials in ganglion cells and less frequently evoked sustained inward currents that appeared synaptic in origin. Sustained currents reversed around ECl and were inhibited by blockade of α-amino-3-hydroxyl-5-methyl-4-isoxazole-proprionate (AMPA)-type glutamate receptors with 2,3-dihydroxy-6-nitro-sulfamoyl-benzo(f)-quinoxaline-2,3-dione (NBQX), γ aminobutyric acid a/c (GABAa/c) receptors with picrotoxinin, or glycine receptors with strychnine. This suggests that epiretinal stimulation activates glutamate release from bipolar cell terminals, which in turn evokes release of GABA and glycine from amacrine cells. Synaptic current thresholds were lower in ON ganglion cells than OFF cells, but the modest difference did not attain statistical significance. Synaptic currents were rarely observed in rd mice lacking photoreceptors compared to normal retina. In addition, confocal calcium imaging experiments in normal mice retina slices revealed that epiretinal stimulation evoked calcium increases in the outer plexiform layer. These results imply a contribution from photoreceptor inputs to the synaptic currents observed in ganglion cells. The paucity of synaptic responses in rd mice retina slices suggests that it is better to target retinal ganglion cells directly rather than to attempt to engage the inner retinal circuitry.
Chaos in PDEs and Lax Pairs of Euler Equations

Recently, the author and collaborators have developed a systematic program for proving the existence of homoclinic orbits in partial differential equations. Two typical forms of homoclinic orbits thus obtained are: (1) transversal homoclinic orbits, (2) Silnikov homoclinic orbits. Around the transversal homoclinic orbits in infinite-dimensional autonomous systems, the author was able to prove the existence of chaos through a shadowing lemma. Around the Silnikov homoclinic orbits, the author was able to prove the existence of chaos through a horseshoe construction. Very recently, there has been a breakthrough by the author in finding Lax pairs for Euler equations of incompressible inviscid fluids. Further results have been obtained by the author and collaborators.
Quality Education and the Efficiency of Public Expenditure : A Cross-Country Comparative Analysis

Improving access to quality education has been the backbone of several development strategies around the world and considerable public resources have been dedicated to achieving this goal. However, one could wonder whether increasing public education expenditure would drive better access to quality education despite the inefficiencies plaguing public sectors in general. The purpose of this study is to investigate the efficiency with which public education spending is translated into increased access to quality education in the light of the learning-adjusted years of schooling. The results show that education expenditure per school-age individual is positively associated with an increased number of years of quality schooling. However, it is estimated that, on average, 16 percent of the public financial resources dedicated to education in developing countries are wasted because of inefficiencies. Although efficiency greatly varies across countries, low-income countries are overall facing a double issue of low levels of education expenditure and weak efficiency of public expenditure on education. Factors related to governance, labor market conditions, and the type of education aid seem to matter for efficiency.
The computation of directional selectivity in the Drosophila OFF motion pathway

In flies, the direction of moving ON and OFF features is computed separately. T4 (ON) and T5 (OFF) are the first neurons in their respective pathways to extract a directionally selective response from their non-selective inputs. Our recent study of T4 found that the integration of offset depolarizing and hyperpolarizing inputs is critical for the generation of directional selectivity. However, T5s lack small-field inhibitory inputs, suggesting they may use a different mechanism. Here we used whole-cell recordings of T5 neurons and found a similar receptive field structure: fast depolarization and persistent, spatially offset hyperpolarization. By assaying pairwise interactions of local stimulation across the receptive field, we found no amplifying responses, only suppressive responses to the non-preferred motion direction. We then evaluated passive, biophysical models and found that a model using direct inhibition, but not the removal of excitation, can accurately predict T5 responses to a range of moving stimuli.
Stories from North of Main: Neighborhood Heritage Story Mapping

This article discusses the use of ESRI’s ArcGIS Story Map application for heritage place-making in a small, diverse, deindustrialized urban neighborhood in Binghamton, New York. “Stories from North of Main” is a Story Map that weaves together the multiple meanings residents attach to neighborhood places by layering audio, images, and text to create stories of work, home, and community life, past and present. Story Maps make visible and legible the place attachments of newcomers and long-time residents in changing city neighborhoods. These place-based stories can offer an alternative to elite-driven heritage and counter the negative narratives attached to marginalized neighborhoods.
U.S. electricity infrastructure of the future: Generation and transmission pathways through 2050

Abstract The future development of the U.S. electricity sector will be shaped by technological, economic, and policy drivers whose trajectories are highly uncertain. In this article, we develop an optimization model for the integrated generation and transmission system in the continental U.S. and use it to explore electricity infrastructure pathways from the present through 2050. By comparing and contrasting results from numerous scenarios and sensitivity settings, we ultimately affirm five key policy-relevant insights. (1) U.S. electricity can be substantially decarbonized at modest cost, but complete decarbonization is very costly. (2) Significant expansion of solar PV and wind to combine for at least 40% of the generation mix by 2050 is fairly certain, although solar PV and battery storage are more affected by economic and policy assumptions than wind. (3) Investments in long-distance transmission are very limited, while investments in battery storage are much greater, under a wide range of assumptions. (4) Optimal solutions include large investments in natural gas capacity, but gas capacity utilization rates decline steadily and significantly. (5) Cost structures shift away from operating expenditures and toward capital expenditures, especially under climate policy. We conclude our article by discussing the policy implications of these findings.
LIFELONG LEARNING WITH A CHANGING ACTION SET

In many real-world sequential decision making problems, the number of available actions (decisions) can vary over time. While problems like catastrophic forgetting, changing transition dynamics, changing rewards functions, etc. have been well-studied in the lifelong learning literature, the setting where the size of the action set changes remains unaddressed. In this paper, we present first steps towards developing an algorithm that autonomously adapts to an action set whose size changes over time. To tackle this open problem, we break it into two problems that can be solved iteratively: inferring the underlying, unknown, structure in the space of actions and optimizing a policy that leverages this structure. We demonstrate the efficiency of this approach on large-scale real-world lifelong learning problems.
Exact smooth piecewise polynomial sequences on Alfeld splits

We develop exact piecewise polynomial sequences on Alfeld splits in any spatial dimension and any polynomial degree. An Alfeld split of a simplex is obtained by connecting the vertices of an $n$-simplex with its barycenter. We show that, on these triangulations, the kernel of the exterior derivative has enhanced smoothness. Byproducts of this theory include characterizations of discrete divergence-free subspaces for the Stokes problem, commutative projections, and simple formulas for the dimensions of smooth polynomial spaces.
Convergence of DNA Methylation Profiles of the Reef Coral Porites astreoides in a Novel Environment

Phenotypic acclimatization is an organismal response to environmental change that may be rooted in epigenetic mechanisms. In reef building corals, organisms that are severely threatened by environmental change, some evidence suggests that DNA methylation is an environmentally responsive mediator of acclimatization. We investigated changes in DNA methylation of the reef coral Porites astreoides in response to simulated environmental change. Coral colonies were sampled from a variety of habitats on the Belize Barrier Reef and transplanted to a common garden for one year. We used restriction site associated DNA sequencing, including a methylation-sensitive variant, to subsample the genome and assess changes in DNA methylation levels after a year in the common garden. Methylation changes among the 629 CpG loci we recovered were subtle, yet coral methylomes were more similar to each other after a year in the common garden together, indicating convergence of methylation profiles in the common environment. Differentially methylated loci showed matches with both coding and non-coding RNA sequences with putative roles in intracellular signaling, apoptosis, gene regulation, and epigenetic crosstalk. There was a positive and significant relationship between genetic and epigenetic variation, providing evidence of methylation heritability. Altogether, our results suggest that DNA methylation in P. astreoides is at least somewhat responsive to environmental change, reflective of the environment, and heritable, characteristics necessary for methylation to be implicated as part of potential transgenerational acclimatization responses.
Predicting the Physical Dynamics of Unseen 3D Objects

Machines that can predict the effect of physical interactions on the dynamics of previously unseen object instances are important for creating better robots and interactive virtual worlds. In this work, we focus on predicting the dynamics of 3D objects on a plane that have just been subjected to an impulsive force. In particular, we predict the changes in state—3D position, rotation, velocities, and stability. Different from previous work, our approach can generalize dynamics predictions to object shapes and initial conditions that were unseen during training. Our method takes the 3D object’s shape as a point cloud and its initial linear and angular velocities as input. We extract shape features and use a recurrent neural network to predict the full change in state at each time step. Our model can support training with data from both a physics engine or the real world. Experiments show that we can accurately predict the changes in state for unseen object geometries and initial conditions.
Robust biomolecular finite automata

Abstract We present a uniform method for translating an arbitrary nondeterministic finite automaton (NFA) into a deterministic mass action input/output chemical reaction network (I/O CRN) that simulates it. The I/O CRN receives its input as a continuous time signal consisting of concentrations of chemical species that vary to represent the NFA's input string in a natural way. The I/O CRN exploits the inherent parallelism of chemical kinetics to simulate the NFA in real time with a number of chemical species that is linear in the size of the NFA. We prove that the simulation is correct and that it is robust with respect to perturbations of the input signal, the initial concentrations of species, the output (decision), and the rate constants of the reactions of the I/O CRN.
Decadal Attribution of Historic Temperature and Ocean Heat Content Change to Anthropogenic Emissions

We present an alternative method of calculating the historical effective radiative forcing using the observed temperature record and a kernel based on the CMIP5 temperature response. This estimate is the effective radiative forcing time series that the average climate model would need to simulate the observed global mean surface temperature anomalies. We further infer the anthropogenic aerosols radiative forcing as a residual using the better-known greenhouse gas radiative forcing. This allows an independent estimate of anthropogenic aerosol radiative forcing, which suggests a cooling influence due to aerosols in the early part of the 20th century. The temporal kernels are also used to calculate decadal contributions from the dominant forcing agents to present day temperature, ocean heat content, and thermosteric sea level rise. The current global mean temperature anomaly is dominated by emissions in the past two decades, while current ocean heat content is more strongly affected by earlier decades.
Nonlinear mathematical models for the origin of asymmetry in biological molecules

The paper deals with a mathematical model of two separate populations of primeval organisms (or polymers), one based on L- and one on D-amino acids. Possible interactions between those two separate, selfreproducing, and mutually antagonistic populations are discussed. Below we list some of the conclusions.
Optical vortex braiding with Bessel beams.

We propose the braiding of optical vortices in a laser beam with more than $ 2\pi $2π rotation by superposing Bessel modes with a plane wave. We experimentally demonstrate this by using a Bessel–Gaussian beam and a coaxial Gaussian, and we present measurements of three complete braids. The amount of braiding is fundamentally limited only by the numerical aperture of the system, and we discuss how braiding can be controlled experimentally for any number of vortices.
The Efficiency of Real-World Bargaining: Evidence from Wholesale Used-Auto Auctions

This study empirically quantifies the efficiency of a real-world bargaining game with two-sided incomplete information. Myerson and Satterthwaite (1983) and Williams (1987) derived the theoretical ex-ante efficient frontier for bilateral trade under two-sided uncertainty and demonstrated that it falls short of ex-post efficiency, but little is known about how well bargaining performs in practice. Using about 265,000 sequences of a game of alternating-offer bargaining following an ascending auction in the wholesale used-car industry, this study estimates (or bounds) distributions of buyer and seller values and evaluates where realized bargaining outcomes lie relative to efficient outcomes. Results demonstrate that the ex-ante and ex-post efficient outcomes are close to one another, but that the real bargaining falls short of both, suggesting that the bargaining is indeed inefficient but that this inefficiency is not solely due to the information constraints highlighted in Myerson and Satterthwaite (1983). Quantitatively, findings indicate that over one-half of failed negotiations are cases where gains from trade exist, leading an efficiency loss of 12–23% of the available gains from trade.
On Secure Capacity of Multiple Unicast Traffic over Separable Networks

This paper studies the problem of information theoretic secure communication when a source has private messages to transmit to m destinations, in the presence of a passive adversary who eavesdrops an unknown set of k edges. The information theoretic secure capacity is derived over unit-edge capacity separable networks, for the cases when k = 1 and m is arbitrary, or m = 3 and k is arbitrary. This is achieved by first showing that there exists a secure polynomial-time code construction that matches an outer bound over two-layer networks, followed by a deterministic mapping between two-layer and arbitrary separable networks.
Renormalization for Holomorphic Field Theories

We introduce the concept of a holomorphic field theory on any complex manifold in the language of the Batalin–Vilkovisky formalism. When the complex dimension is one, this setting agrees with that of chiral conformal field theory. Our main result concerns the behavior of holomorphic theories under renormalization group flow. Namely, we show that holomorphic theories are one-loop finite. We use this to completely characterize holomorphic anomalies in any dimension. Throughout, we compare our approach to holomorphic field theories to more familiar approaches including that of supersymmetric field theories.
Maximum Marginal Likelihood Estimation of Phase Connections in Power Distribution Systems

Accurate phase connectivity information is essential for advanced monitoring and control applications in power distribution systems. The existing data-driven approaches for phase identification lack precise physical interpretation and theoretical performance guarantee. Their performance generally deteriorates as the complexity of the network, the number of phase connections, and the level of load balance increase. In this paper, by linearizing the three-phase power flow manifold, we develop a physical model, which links the phase connections to the smart meter measurements. The phase identification problem is first formulated as a maximum likelihood estimation problem and then reformulated as a maximum marginal likelihood estimation problem. We prove that the correct phase connection achieves the highest log likelihood values for both problems. An efficient solution method is proposed by decomposing the original problem into subproblems with a binary least-squares formulation. The numerical tests on a comprehensive set of distribution circuits show that our proposed method yields very high accuracy on both radial and meshed distribution circuits with a combination of single-phase, two-phase, and three-phase loads. The proposed algorithm is robust with respect to inaccurate feeder models, incomplete measurements, and bad measurements. It also outperforms the existing methods on complex circuits.
Emergency Evacuation Assistance

There have been more than necessary casualties due to a lack of intelligence in emergency evacuation mechanisms such as exit signs. Although large or complex buildings and facilities have many exit doors, in case of emergency, people may not be able to escape quickly enough due to sudden loss of directions and difficulty in finding safe routes to exit doors. If you were ever in such a situation, you would wish that if there were ever smart escape route assistance mechanisms available or at least smart exit signs available that safely and quickly guide you to a safe haven. It is what we try to make such a wish come true. In this paper, we propose a graph mapping scheme and a new safe evacuation route algorithm for safe emergency evacuation assistance, with the aid of recent technology called Internet of Things (IoT). The gist of our approach is that people are not allowed to pass through or even go towards any area where fire or toxic gas is detected by controlling the direction signals installed on exit signs. The experiments performed with our methodology shows that the proposed technology may be able to save more lives.
Program2Play: Enticing Underrepresented Groups to Program through Gameplay

This paper introduces a new initiative of web-based games that encourages students to experiment with JavaScript instructions in order to play a series of games. This approach to involving students in early stages of programming uses principles of bricolage [2] to appeal to learning styles that traditional computer science curricula often do not appeal to. The fundamental goal is to build confidence and motivation through early programming successes. This initiative can be used in a CS0 course, to remediate programming skills for targeted students, or as a means to interest high school students in programming.
The ACA's Choice Problem

The Affordable Care Act (ACA) is in many ways a success. Millions more Americans now have access to health care, and the ACA catalyzed advances in health care delivery reform. Simultaneously, it has reinforced and bolstered a problem at the heart of American health policy and regulation: a love affair with choice. The ACA's insurance reforms doubled down on the particularly American obsession with choice. This article describes three ways in which that doubling down is problematic for the future of US health policy. First, pragmatically, health policy theory predicts that choice among health plans will produce tangible benefits that it does not actually produce. Most people do not like choosing among health plan options, and many people-even if well educated and knowledgeable-do not make good choices. Second, creating the regulatory structures to support these choices built and reinforced a massive market bureaucracy. Finally, and most important, philosophically and sociologically the ACA reinforces the idea that the goal of health regulation should be to preserve choice, even when that choice is empty. This vicious cycle seems likely to persist based on the lead up to the 2020 presidential election.
Less is More: Real-time Failure Localization in Power Systems

Cascading failures in power systems exhibit nonlocal propagation patterns, which make the analysis and mitigation of failures difficult. In this work, we propose a distributed control framework inspired by the recently proposed concepts of unified controller and network tree-partition that offers strong guarantees in both the mitigation and localization of cascading failures in power systems. In this framework, the transmission network is partitioned into several control areas which are connected in a tree structure, and the unified controller is adopted by generators or controllable loads for fast timescale disturbance response. After an initial failure, the proposed strategy always prevents successive failures from happening, and regulates the system to the desired steady state where the impact of initial failures are localized as much as possible. For extreme failures that cannot be localized, the proposed framework has a configurable design, that progressively involves and coordinates more control areas for failure mitigation and, as a last resort, imposes minimal load shedding. We compare the proposed control framework with Automatic Generation Control (AGC) on the IEEE 118-bus test system. Simulation results show that our novel framework greatly improves the system robustness in terms of the N − 1 security standard, and localizes the impact of initial failures in majority of the load profiles that are examined. Moreover, the proposed framework incurs significantly less load loss, if any, compared to AGC.
Constructing auxiliary dynamics for nonequilibrium stationary states by variance minimization

We present a strategy to construct guiding distribution functions (GDFs) based on variance minimization. Auxiliary dynamics via GDFs mitigates the exponential growth of variance as a function of bias in Monte Carlo estimators of large deviation functions. The variance minimization technique exploits the exact properties of eigenstates of the tilted operator that defines the biased dynamics in the nonequilibrium system. We demonstrate our techniques in two classes of problems. In the continuum, we show that GDFs can be optimized to study the interacting driven diffusive systems where the efficiency is systematically improved by incorporating higher correlations into the GDF. On the lattice, we use a correlator product state ansatz to study the 1D weakly asymmetric simple exclusion process. We show that with modest resources, we can capture the features of the susceptibility in large systems that mark the phase transition from uniform transport to a traveling wave state. Our work extends the repertoire of tools available to study nonequilibrium properties in realistic systems.
Incidence of and Risk Factors for Multiple Readmissions after Kidney Transplantation

Unplanned readmission is often used as a surgical quality metric. A subset of kidney transplant recipients undergos multiple readmissions (MRs), although the incidence and risk factors are not well described. The aim of this study was to evaluate risk factors for MR after deceased donor kidney transplantation. All patients undergoing deceased donor kidney transplantation at a single center over a three-year period were analyzed via retrospective chart review for factors associated with MR. P values <0.05 were considered significant. Of 141 patients, the 30-day readmission rate was 26.2 per cent. MR occurred in 43 (30.5%) patients. Age, race, gender, initial organ function, and dialysis vintage were not associated with MR. Diabetic recipients, those who received basiliximab induction, those with acute rejection, and those with unplanned reoperations were at increased risk for MR. Infection was the most common reason for initial readmission in patients with MR (23.3%). One-year patient survival and death-censored graft survival were reduced for patients with MR. MRs are required for 30 per cent of kidney transplant recipients, primarily because of infection and immunologic causes. Recipients with diabetes and those who have acute rejection are at greatest risk.
Sanctuary Status and Crime in California: What’s the Connection?

In 2017, California officially became a sanctuary state following the passage of Senate Bill 54, which limits state and local police cooperation with federal immigration authorities. Following the ...
Are Aid Agencies Changing their Practices

Using data from 2004 to 2008−2012, we provide the first multi‐year agency monitoring of Development Assistance Committee (DAC), multilateral and United Nations (UN) agencies. Our results suggest that, on average, DAC donor performance has declined while multilateral and UN agency performance has increased. Specifically, multilateral and UN agencies are more transparent and specialized while DAC donors are less specialized and failed to improve in other categories. © 2020 John Wiley & Sons, Ltd.
Changing Social Contexts to Foster Equity in College Science Courses: An Ecological-Belonging Intervention.

In diverse classrooms, stereotypes are often “in the air,” which can interfere with learning and performance among stigmatized students. Two studies designed to foster equity in college science cla...
Robust computation of optical flow in a multi-scale differential framework

We have developed a new algorithm for computing optical flow in a differential framework. The image sequence is first convolved with a set of linear, separable spatiotemporal filter kernels similar to those that have been used in other early vision problems such as texture and stereopsis. The brightness constancy constraint can then be applied to each of the resulting images, giving us, in general, an overdetermined system of equations for the optical flow at each pixel. There are three principal sources of error: (a) stochastic error due to sensor noise (b) systematic errors in the presence of large displacements and (c) errors due to failure of the brightness constancy model. Our analysis of these errors leads us to develop an algorithm based on a robust version of total least squares. Each optical flow vector computed has an associated reliability measure which can be used in subsequent processing. The performance of the algorithm on the data set used by Barron et al. (IJCV 1994) compares favorably with other techniques. In addition to being separable, the filters used are also causal, incorporating only past time frames. The algorithm is fully parallel and has been implemented on a multiple processor machine.
Flux tube models of solar plages

The spectroscopic properties of model solar plages composed of narrow magnetic flux tubes embedded in undisturbed quiet sun are analyzed. The final models are magnetostatic flux tubes for which the level tau5000 = 1 level is 200 km below the same level in the quiet sun; these models are hotter than the quiet sun at all levels and expand by roughly a factor of three between this level and the quiet sun temperature minimum. These models are tested against a wide range of observational constraints. The assumed flux tube diameter is found to be an important parameter for predictions of the center-to-limb variation of the magnetically insensitive lines and of the visible continuum. A diameter of 300 km at tau5000 = 1 is necessary to give qualitative agreement with observations. A model plage consisting of the derived flux tube model embedded in a quiet sun model derived from the Ca II K line wings reproduces this line in plages at the observed value of mu; one of the models also predicts values of disk center plage contrast at 30, 50, 100, and 200 micron wavelength in good agreement with the observations of Jefferies et al. (1982).
4 – UNDERSTANDING INFLATION

Publisher Summary This chapter provides an overview of the understanding inflation of economics. Inflation is a substantial, sustained increase in the general level of prices. Inflation rates have varied widely over the past 20 years, but there has been a general upward trend. Inflation affects the economy in many ways. Inflation affects people living on fixed incomes and those who borrow or lend money. Most inflation in recent years has been unexpected. This surprise inflation benefits borrowers, and hurts savers and lenders. Indexation is one way for the economy to cope with inflation. Indexation cushions inflation's blows but also encourages inflation by making it easier to live with. Many countries that have suffered high inflation have resorted to indexation. The Consumer Price Index (CPI), the Producer Price Index (PPI), and the Gross National Product Index are the main inflation measures in the United States. The PPI is a leading indicator of changes in the CPI.
Risk adjustment of the credit-card augmented Divisia monetary aggregates

While credit cards provide transactions services, as do currency and demand deposits, credit cards have never been included in measures of the money supply. The reason is accounting conventions, which do not permit adding liabilities, such as credit card balances, to assets, such as money. However, economic aggregation theory and index number theory measure service flows and are based on microeconomic theory, not accounting. Barnett, Chauvet, Leiva-Leon, and Su (2016) derived the aggregation and index number theory needed to measure the joint services of credit cards and money. They derived and applied the theory under the assumption of risk neutrality. But since credit card interest rates are high and volatile, risk aversion may not be negligible. We extend the theory by removing the assumption of risk neutrality to permit risk aversion in the decision of the representative consumer.
Time series analysis and prediction using gated experts with application to energy demand forecasts

In the analysis and prediction of real-world systems, two of the key problems are nonstationarity (often in the form ofswitching between regimes) and overfitting (particularly serious for noisy processes). This article addresses these problems using gated experts, consisting of a (nonlinear) gating network and several (also nonlinear) competing experts. Each expert learns to predict the conditional mean and each expert adapts its width to match the noise level in its regime. The gating network learns to predict the probability of each expert, given the input. This article focuses on the case where the gating network bases its decision on information from the inputs. This can be contrasted to hidden Markov models where the decision is based on the previous state(s) (i.e., on the output of the gating network at the previous time step), as well as to averaging over several predictors. In contrast, gated experts soft-partition the input space. This article discusses the underlying statistical assumptions, derives the weight update rules, and compares the performance of gated experts to standard methods on three time series: (1) computer-generated series, obtained by randomly switching between two nonlinear processes, (2) a time series from the Santa Fe Time Series Competition (the light intensity of laser in chaotic state), and (3) the daily electricity demand of France, a real-world multivariate problem with structure on several timescales. The main results are (1) the gating network correctly discovers the different regimes of the process, (2) the widths associated with each expert are important for the segmentation task (and they can be used to characterize the subprocesses), and (3) there is less overfitting compared to single networks (homogeneous multilayer perceptrons), since the experts learn to match their variances to the (local) noise levels. This can be viewed as matching the local complexity of the model to the local complexity of the data.