cssi/SciSciGPT-SciSciNet huggingface dataset:
Design of an entrustable professional activity for adult extracorporeal membrane oxygenation.

Abstract Background Extracorporeal membrane oxygenation supports severe cardiac or pulmonary failure. There are currently no competency-based standards for extracorporeal membrane oxygenation training. Methods Extracorporeal membrane oxygenation experts were interviewed using a structured interview. Responses were audio recorded, transcribed, and validated by respondents. Interviews were coded using grounded theory with a constant comparison method. Themes were developed and used to construct the entrustable professional activity, which was reviewed by the extracorporeal membrane oxygenation experts. Results Nine experts were interviewed; all had experience with trainees. Interview themes identified include patient selection, circuit and medical management, multidisciplinary communication, problem-based learning and simulation, and entrustment decisions. Essential functions of the entrustable professional activity were patient selection, circuit management, cannula selection, responding to circuit emergencies/complications, anticoagulation management, weaning, and family/team communication. Conclusions Essential functions of an extracorporeal membrane oxygenation entrustable professional activity were defined using data from structured interviews. The resultant entrustable professional activity could be implemented by critical-care programs as a scaffolding for competency-based fellow training.
Aggregation-diffusion to constrained interaction: Minimizers & gradient flows in the slow diffusion limit

Abstract Inspired by recent work on minimizers and gradient flows of constrained interaction energies, we prove that these energies arise as the slow diffusion limit of well-known aggregation-diffusion energies. We show that minimizers of aggregation-diffusion energies converge to a minimizer of the constrained interaction energy and gradient flows converge to a gradient flow. Our results apply to a range of interaction potentials, including singular attractive and repulsive-attractive power-law potentials. In the process of obtaining the slow diffusion limit, we also extend the well-posedness theory for aggregation-diffusion equations and Wasserstein gradient flows to admit a wide range of nonconvex interaction potentials. We conclude by applying our results to develop a numerical method for constrained interaction energies, which we use to investigate open questions on set valued minimizers.
Promises and Pitfalls of In Vivo Evolution to Improve Phage Therapy

Phage therapy is the use of bacterial viruses (phages) to treat bacterial infections, a medical intervention long abandoned in the West but now experiencing a revival. Currently, therapeutic phages are often chosen based on limited criteria, sometimes merely an ability to plate on the pathogenic bacterium. Better treatment might result from an informed choice of phages. Here we consider whether phages used to treat the bacterial infection in a patient may specifically evolve to improve treatment on that patient or benefit subsequent patients. With mathematical and computational models, we explore in vivo evolution for four phage properties expected to influence therapeutic success: generalized phage growth, phage decay rate, excreted enzymes to degrade protective bacterial layers, and growth on resistant bacteria. Within-host phage evolution is strongly aligned with treatment success for phage decay rate but only partially aligned for phage growth rate and growth on resistant bacteria. Excreted enzymes are mostly not selected for treatment success. Even when evolution and treatment success are aligned, evolution may not be rapid enough to keep pace with bacterial evolution for maximum benefit. An informed use of phages is invariably superior to naive reliance on within-host evolution.
Timely Cloud Computing: Preemption and Waiting

The notion of timely status updating is investigated in the context of cloud computing. Measurements of a time-varying process of interest are acquired by a sensor node, and uploaded to a cloud server to undergo some required computations. These computations have random service times that are independent and identically distributed across different uploads. After the computations are done, the results are delivered to a monitor, constituting an update. The goal is to keep the monitor continuously fed with fresh updates over time, which is assessed by an age-of-information(AoI) metric. A scheduler is employed to optimize the measurement acquisition times. Following an update, an idle waiting period may be imposed by the scheduler before acquiring a new measurement. The scheduler also has the capability to preempt a measurement in progress if its service time grows above a certain cutoff time, and upload a fresher measurement in its place. Focusing on stationary deterministic policies, in which waiting times are deterministic functions of the instantaneous AoI and the cutoff time is fixed for all uploads, it is shown that the optimal waiting policy that minimizes the long term average AoI has a threshold structure, in which a new measurement is uploaded following an update only if the AoI grows above a certain threshold that is a function of the service time distribution and the cutoff time. The optimal cutoff is then found for standard and shifted exponential service times. While it has been previously reported that waiting before updating can be beneficial for AoI, it is shown in this work that preemption of late updates can be even more beneficial.
Improving Voltage Profile of the Nigerian Power Grid

Extreme voltages at the system nodes are one of the primary causes for total and partial collapse of the Nigerian grid. In this paper, we develop a framework to re-dispatch the voltage set-points of committed generators in the grid to improve the voltage profile of the system nodes thus lowering the likelihood of a grid collapse. This framework is an extension of circuit-theoretic formulation that can robustly solve general-purpose grid optimization problems. In the results section, we re-dispatch the voltage setpoints for committed generators in real-life Nigerian grid operation and planning test cases to improve the overall voltage profile of the grid. We further demonstrate that the re-dispatched grid is more resilient and secure than the base case through running contingency analyses.
Telomere length associations with cognition depend on Alzheimer's disease biomarkers

Abstract Introduction While telomere shortening, a marker of cellular aging, may impact the progression of age-related neurodegenerative diseases, its association with cognition is unclear, particularly in the context of Alzheimer's disease (AD) pathology. Methods Telomere, cognitive, and CSF data from 482 participants in the AD Neuroimaging Initiative (148 cognitively normal, 283 mild cognitive impairment, 51 AD) was leveraged to assess telomere length associations with cognition (measured by memory and executive function) and interactions with CSF amyloid-β, tau, and APOE-e4. Secondary analyses assessed brain volume and thickness outcomes. Results Longer telomeres at baseline were associated with faster executive function decline. Amyloid-β and tau interacted with telomere length on cognition, with longer telomeres related to faster decline among biomarker-positive individuals. Discussion Telomere associations with cognition shift with AD progression, with longer telomeres related to worse outcomes as pathology increases, highlighting the need for further investigation of telomere length along the AD neuropathological cascade.
Mortgage Pricing Implications of Prepayment: Separating Pecuniary and Non-pecuniary Prepayment

In the study of mortgage loan pricing, prepayment and default hazards are considered. While default results in loss of initial capital, prepayment is the more frequent termination event. This study makes a distinction between pecuniary and non-pecuniary prepayments in the mortgage pricing model. Pecuniary/non-pecuniary prepayments are distinguished from each other based on whether the market interest rate at prepayment is below/above the rate at origination, and thus whether mortgage lenders/investors can reinvest the proceeds at a lower/higher interest rate using the proceeds from a prepaid loan. Using a sample of 30-year fixed-rate mortgage loans for home purchase, this study finds that pecuniary and non-pecuniary prepayments are affected differently by certain overlapping factors and are driven by some unique factors. The results also show that combining these two types of prepayments into a single prepayment measure may yield inaccurate predictions of loan termination probabilities. The results from the mortgage pricing model indicate that pecuniary and non-pecuniary prepayment risks, together with default risk, contribute separately to the pricing of a loan.
Preschoolers’ broad mathematics experiences with parents during play

Abstract The current study broadens our understanding of preschoolers’ early math experiences with parents, recognizing that math knowledge and experiences are inclusive of numeracy as well as non-numeracy domains. Parents and preschoolers (N = 45) were observed exploring three domains of early mathematics knowledge (i.e., number, space, and pattern) during play in three activities (playing cards, building with blocks, and stringing beads, all with activity suggestions). Children were administered a broad math and numeracy measure and individual measures of spatial and patterning skills concurrently and 7 months later. Dyads explored math broadly across most activities but emphasized number more than space or patterning. In addition, there was more overall math exploration during card and bead play than during block play, with the greatest parent support during card play. Parent support was not linked to children’s skills, although children’s exploration of space and patterns related moderately to their concurrent spatial and pattern skills. Overall, parents and young children explored a variety of early math domains in guided play contexts, with an emphasis on numeracy. Future work should aim to increase the breadth and rigor of individual concepts that parents and preschoolers explore during play.
Bayesian task embedding for few-shot Bayesian optimization

We describe a method for Bayesian optimization by which one may incorporate data from multiple systems whose quantitative interrelationships are unknown a priori. All general (nonreal-valued) features of the systems are associated with continuous latent variables that enter as inputs into a single metamodel that simultaneously learns the response surfaces of all of the systems. Bayesian inference is used to determine appropriate beliefs regarding the latent variables. We explain how the resulting probabilistic metamodel may be used for Bayesian optimization tasks and demonstrate its implementation on a variety of synthetic and real-world examples, comparing its performance under zero-, one-, and few-shot settings against traditional Bayesian optimization, which usually requires substantially more data from the system of interest.
Dual selection games

Abstract Often, a given selection game studied in the literature has a known dual game. In dual games, a winning strategy for a player in either game may be used to create a winning strategy for the opponent in the dual. For example, the Rothberger selection game involving open covers is dual to the point-open game. This extends to a general theorem: if { range ( f ) : f ∈ C ( R ) } is coinitial in A with respect to ⊆, where C ( R ) = { f ∈ ( ⋃ R ) R : R ∈ R ⇒ f ( R ) ∈ R } collects the choice functions on the set R , then G 1 ( A , B ) and G 1 ( R , ¬ B ) are dual selection games.
Singlet Fission in Quaterrylenediimide Thin Films

Singlet fission (SF) creates two triplet excitons following absorption of a photon by two electronically interacting chromophores. Quaterrylene-3,4:13,14-bis(dicarboximide) (QDI) is a strongly absorbing chromophore that readily fulfills the energetic requirements for SF, E(S1) > 2E(T1), and thus should undergo rapid and efficient SF. SF was studied in thin films of the QDI derivative N,N-bis(2,6-diisopropylphenyl)-QDI (ArQDI), which undergoes SF in <300 fs to form the correlated triplet pair state, 1(T1T1), which dissociates with a (7.3 ± 1.2 ns)−1 rate constant. The observed triplet yield for a thin film that has been solvent-vapor annealed with CH2Cl2 is 135 ± 20% instead of 200%, which is typically expected of chromophores that undergo ultrafast formation of the 1(T1T1) state. The lower SF yield in ArQDI results from the failure of the 1(T1T1) state to dissociate before returning to the ground state. In contrast to other molecules, like hexacene, which have low triplet energies, the SF rate in ArQDI is...
Peremptory Norms of General International Law (Jus Cogens) and Other Topics: The Seventy- First Session of the International Law Commission

This essay analyzes the outcome of the International Law Commission (ILC)’s seventy- first session, held from April 29 to June 7 and from July 8 to August 9, 2019 in Geneva, under the chairmanship of Pavel Sturma (Czech Republic). Notably, the Commission completed the first reading of its topic on peremptory norms of general international law (jus cogens). The Commission also completed the first reading of its topic on protection of the environment in relation to armed conflict and completed the second reading of its topic on crimes against humanity. Progress was also made in developing draft articles on succession of states with respect to state responsibility, draft articles on immunity of state officials from foreign criminal jurisdiction, and draft conclusions on general principles of law. Additionally, the Commission held informal consultations concerning model clauses for its topic on provisional application of treaties, the first reading of which was completed in the seventieth session and the second reading of which is expected during the seventy-second session in 2020. The Commission added to its agenda a topic on sea-level rise in relation to international law, which is being addressed in the context of a study group rather than by use of a special rapporteur. It also added two new topics to its long-term work program: (1) reparation to individuals for gross violations of international human rights law and serious violations of international humanitarian law; and (2) prevention and repression of piracy and armed robbery at sea.
The Case for Raabe’s Test

SummaryAmong the techniques for determining the convergence of a series, Raabe’s test remains relatively unfamiliar to most mathematicians. We present several results relating to Raabe’s test that ...
Twisted composite structures made by 4D printing method

Abstract This paper presents the determination of the configurations of twisted laminates made by 4D printing of composites (4DPC) method. Flat stacks of composite prepregs are laid onto a flat mold. Upon curing and cooling to room temperature, the flat stack becomes curved and twisted. The configurations of the twisted laminate are determined using both calculated method (FEM) and experimental measurement. Reasonable agreement is obtained.
Procrastination at the Patent Office

Abstract Pointing to a limited set of statistics suggesting that examiners turn in much of their work product at the end of quota periods, the Commerce Department has recently raised concerns over examiner procrastination and its consequences for examination quality. End-loading of review completions alone, however, is not dispositive evidence of procrastination. In this paper, we confirm that examiners complete a substantial percentage of reviews at the end of both bi-weekly and quarterly quotas and then proceed to test for additional markers that may separate a procrastination explanation for these findings from a range of alternative theories. Among other tests explored in this regard, we predict and find evidence of an immediate spike in end-loading upon the onset of examiner telecommuting, a change in work environments that likely exacerbates self-control problems. Our findings support a procrastination interpretation for at least some portion of the observed end-loading of reviews, with our outcomes analysis suggesting that the predominant consequence of this behavior for examination quality is an increase in examination durations.
\(\ell _1\)-sparsity Approximation Bounds for Packing Integer Programs

We consider approximation algorithms for packing integer programs (PIPs) of the form \(\max \{\langle c, x\rangle : Ax \le b, x \in \{0,1\}^n\}\) where c, A, and b are nonnegative. We let \(W = \min _{i,j} b_i / A_{i,j}\) denote the width of A which is at least 1. Previous work by Bansal et al. [1] obtained an \(\varOmega (\frac{1}{\varDelta _0^{1/\lfloor W \rfloor }})\)-approximation ratio where \(\varDelta _0\) is the maximum number of nonzeroes in any column of A (in other words the \(\ell _0\)-column sparsity of A). They raised the question of obtaining approximation ratios based on the \(\ell _1\)-column sparsity of A (denoted by \(\varDelta _1\)) which can be much smaller than \(\varDelta _0\). Motivated by recent work on covering integer programs (CIPs) [4, 7] we show that simple algorithms based on randomized rounding followed by alteration, similar to those of Bansal et al. [1] (but with a twist), yield approximation ratios for PIPs based on \(\varDelta _1\). First, following an integrality gap example from [1], we observe that the case of \(W=1\) is as hard as maximum independent set even when \(\varDelta _1 \le 2\). In sharp contrast to this negative result, as soon as width is strictly larger than one, we obtain positive results via the natural LP relaxation. For PIPs with width \(W = 1 + \epsilon \) where \(\epsilon \in (0,1]\), we obtain an \(\varOmega (\epsilon ^2/\varDelta _1)\)-approximation. In the large width regime, when \(W \ge 2\), we obtain an \(\varOmega ((\frac{1}{1 + \varDelta _1/W})^{1/(W-1)})\)-approximation. We also obtain a \((1-\epsilon )\)-approximation when \(W = \varOmega (\frac{\log (\varDelta _1/\epsilon )}{\epsilon ^2})\).
On the Upload versus Download Cost for Secure and Private Matrix Multiplication

In this paper, we study the problem of secure and private distributed matrix multiplication. Specifically, we focus on a scenario where a user wants to compute the product of a confidential matrix A, with a matrix $B_{\theta}$, where $\theta \in$ {1, …, M}. The set of candidate matrices {B 1 , …, B M } are public, and available at all the N servers. The goal of the user is to distributedly compute $AB_{\theta}$, such that (a) no information is leaked about the matrix A to any server; and (b) the index $\theta$ is kept private from each server. Our goal is to understand the fundamental tradeoff between the upload vs download cost for this problem. Our main contribution is to show that the lower convex hull of following (upload, download) pairs: (U,D) = (N/(K − 1), (K/(K − 1)) (1 + (K/N) + ··· + (K/N)M−1)) for K = 2, …, N is achievable. The scheme improves upon state-of-the-art existing schemes for this problem, and leverages ideas from secret sharing and coded private information retrieval.
FAIRVIS: Visual Analytics for Discovering Intersectional Bias in Machine Learning

The growing capability and accessibility of machine learning has led to its application to many real-world domains and data about people. Despite the benefits algorithmic systems may bring, models can reflect, inject, or exacerbate implicit and explicit societal biases into their outputs, disadvantaging certain demographic subgroups. Discovering which biases a machine learning model has introduced is a great challenge, due to the numerous definitions of fairness and the large number of potentially impacted subgroups. We present FAIRVIS, a mixed-initiative visual analytics system that integrates a novel subgroup discovery technique for users to audit the fairness of machine learning models. Through FAIRVIS, users can apply domain knowledge to generate and investigate known subgroups, and explore suggested and similar subgroups. FAIRVIS's coordinated views enable users to explore a high-level overview of subgroup performance and subsequently drill down into detailed investigation of specific subgroups. We show how FAIRVIS helps to discover biases in two real datasets used in predicting income and recidivism. As a visual analytics system devoted to discovering bias in machine learning, FAIRVIS demonstrates how interactive visualization may help data scientists and the general public understand and create more equitable algorithmic systems.
Diagnosing the sensitivity of grounding-line flux to changes in sub-ice-shelf melting

Abstract. We seek to understand causal connections between changes in sub-ice shelf melting, ice shelf buttressing, and grounding-line flux. Using a numerical ice flow model, we study changes in ice shelf buttressing and grounding line flux due to localized ice thickness perturbations – a proxy for changes in sub-ice shelf melting – applied to idealized (MISMIP+) and realistic (Larsen C) domains. From our experiments, we identify a correlation between a locally derived buttressing number on the ice shelf, based on the first principal stress, and changes in the integrated grounding line flux. The origin of this correlation, however, remains elusive from a physical perspective; while local thickness perturbations on the ice shelf (thinning) generally correspond to local increases in buttressing, their integrated impact on changes at the grounding line are exactly the opposite (buttressing at the grounding line decreases and ice flux at the grounding line increases). This and additional complications encountered when examining realistic domains motivates us to seek an alternative approach, an adjoint-based method for calculating the sensitivity of the integrated grounding line flux to local changes in ice shelf geometry. We show that the adjoint-based sensitivity is identical to that deduced from pointwise, diagnostic model perturbation experiments. Based on its much wider applicability and the significant computational savings, we propose that the adjoint-based method is ideally suited for assessing grounding line flux sensitivity to changes in sub-ice shelf melting.
Non-CPAs and Office Audit Quality

During the time surrounding the Sarbanes-Oxley Act of 2002, the Big 4 firms either spun-off or downsized their consulting practices. However, in recent years, consulting service lines of the large ...
Indefinite Stein fillings and Pin(2)-monopole Floer homology

We introduce techniques to study the topology of Stein fillings of a given contact three-manifold (Y,ξ) which are not negative definite. For example, given a spinc rational homology sphere (Y,s) with s self-conjugate such that the reduced monopole Floer homology group HM∙(Y,s) has dimension one, we show that any Stein filling which is not negative definite has b+2=1 or 2, and b−2 is determined in terms of the Froyshov invariant. The proof of this uses Pin(2)-monopole Floer homology. More generally, we prove that analogous statements hold under certain assumptions on the contact invariant of ξ and its interaction with Pin(2)-symmetry. We also discuss consequences for finiteness questions about Stein fillings.
Global Prompt Proton Sensor Network: Monitoring Solar Energetic Protons Based on GPS Satellite Constellation

Energetic particle instruments on board GPS satellites form a powerful global prompt proton sensor network (GPPSn) that provides an unprecedented opportunity to monitor and characterize solar energetic protons targeting the Earth. The medium-Earth-orbits of the GPS constellation have the unique advantage of allowing solar energetic protons to be simultaneously measured from multiple points in both open- and closed-field line regions. Examining two example intervals of solar proton events, we showcase in this study how GPS proton data are prepared, calibrated and utilized to reveal important features of solar protons, including their source, acceleration/scattering by interplanetary shocks, the relative position of Earth when impinged by these shocks, the shape of solar particle fronts, the access of solar protons inside the dynamic geomagnetic field, as well temporally-varying proton distributions in both energy and space. By comparing to Van Allen Probes data, GPS proton observations are further demonstrated not only to be useful for qualitatively monitoring the dynamics of solar protons, but also for quantitative scientific research including determining cutoff L-shells. Our results establish that this GPPSn can join forces with other existing solar proton monitors and contribute to observing, warning, understanding and ultimately forecasting the incoming solar energetic proton events.
Two-Step Modification of Phonon Mean Free Paths for Thermal Conductivity Predictions of Thin-Film-Based Nanostructures

Abstract As one simple metamaterial, nanopatterns are often fabricated across a thin film so that the thermal transport can be manipulated. The etched sidewalls for these nanostructures are usually rough due to surface defects introduced during the nanofabrication, whereas the top and bottom film surfaces are smoother. In existing analytical models, the contrast between these surfaces has not been addressed and all boundaries are assumed to be diffusive for phonon reflection. In this paper, a new two-step approach to address this issue is proposed for phonon transport modeling of general thin-film-based structures. In this approach, the effective in-plane phonon mean free paths (ΛFilm) are first modified from the bulk phonon MFPs to account for the influence of the top/bottom film surfaces, with possibly enhanced probability of specular phonon reflection at cryogenic temperatures. This ΛFilm is further modified to include the scattering by etched sidewalls with almost completely diffusive phonon scattering. Such a two-step phonon mean free path modification yields almost identical results as frequency-dependent phonon Monte Carlo simulations for etched nanowires and representative nanoporous thin films. This simple yet accurate analytical model can be applied to general thin-film-based nanostructures to combine the phonon size effects along orthogonal directions.
Torsion points and Galois representations on CM elliptic curves

We prove several results on torsion points and Galois representations for complex multiplication (CM) elliptic curves over a number field containing the CM field. One result computes the degree in which such an elliptic curve has a rational point of order $N$, refining results of Silverberg. Another result bounds the size of the torsion subgroup of an elliptic curve with CM by a nonmaximal order in terms of the torsion subgroup of an elliptic curve with CM by the maximal order. Our techniques also yield a complete classification of both the possible torsion subgroups and the rational cyclic isogenies of a $K$-CM elliptic curve $E$ defined over $K(j(E))$.
Hilbert-Type Dimension Polynomials of Intermediate Difference-Differential Field Extensions

Let K be an inversive difference-differential field and L a (not necessarily inversive) finitely generated difference-differential field extension of K. We consider the natural filtration of the extension L/K associated with a finite system \(\eta \) of its difference-differential generators and prove that for any intermediate difference-differential field F, the transcendence degrees of the components of the induced filtration of F are expressed by a certain numerical polynomial \(\chi _{K, F,\eta }(t)\). This polynomial is closely connected with the dimension Hilbert-type polynomial of a submodule of the module of Kahler differentials \(\varOmega _{L^{*}|K}\) where \(L^{*}\) is the inversive closure of L. We prove some properties of polynomials \(\chi _{K, F,\eta }(t)\) and use them for the study of the Krull-type dimension of the extension L/K. In the last part of the paper, we present a generalization of the obtained results to multidimensional filtrations of L/K associated with partitions of the sets of basic derivations and translations.
Adaptive Causal Network Coding With Feedback

We propose a novel adaptive and causal random linear network coding (AC-RLNC) algorithm with forward error correction (FEC) for a point-to-point communication channel with delayed feedback. AC-RLNC is adaptive to the channel condition, that the algorithm estimates, and is causal, as coding depends on the particular erasure realizations, as reflected in the feedback acknowledgments. Specifically, the proposed model can learn the erasure pattern of the channel via feedback acknowledgments, and adaptively adjust its retransmission rates using a priori and posteriori algorithms. By those adjustments, AC-RLNC achieves the desired delay and throughput, and enables transmission with zero error probability. We upper bound the throughput and the mean and maximum in order delivery delay of AC-RLNC, and prove that for the point to point communication channel in the non-asymptotic regime the proposed code may achieve more than 90% of the channel capacity. To upper bound the throughput we utilize the minimum Bhattacharyya distance for the AC-RLNC code. We validate those results via simulations. We contrast the performance of AC-RLNC with the one of selective repeat (SR)-ARQ, which is causal but not adaptive, and is a posteriori. Via a study on experimentally obtained commercial traces, we demonstrate that a protocol based on AC-RLNC can, vis-a-vis SR-ARQ, double the throughput gains, and triple the gain in terms of mean in order delivery delay when the channel is bursty. Furthermore, the difference between the maximum and mean in order delivery delay is much smaller than that of SR-ARQ. Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications (URLLC) applications.
Stochastic model predictive control for central HVAC plants

Abstract We present a stochastic model predictive control (MPC) framework for central heating, ventilation, and air conditioning (HVAC) plants. The framework uses real data to forecast and quantify uncertainty of disturbances affecting the system over multiple timescales (electrical loads, heating/cooling loads, and energy prices). We conduct detailed closed-loop simulations and systematic benchmarks for the central HVAC plant of a typical university campus. Results demonstrate that deterministic MPC fails to properly capture disturbances and that this translates into economic penalties associated with peak demand charges and constraint violations in thermal storage capacity (overflow and/or depletion). Our results also demonstrate that stochastic MPC provides a more systematic approach to mitigate uncertainties and that this ultimately leads to cost savings of up to 7.5% and the mitigation of storage constraint violations. Benchmark results also indicate that these savings are close to ideal savings (9.6%) obtained under MPC with perfect information.
Spatial encoding strategy theory: the relationship between spatial skill and STEM achievement

Learners' spatial skill is a reliable and significant predictor of achievement in STEM, including computing, education. Spatial skill is also malleable, meaning it can be improved through training. Most cognitive skill training improves performance on only a narrow set of similar tasks, but researchers have found ample evidence that spatial training can broadly improve STEM achievement. We do not yet know the cognitive mechanisms that make spatial skill training broadly transferable when other cognitive training is not, but understanding these mechanisms is important for developing training and instruction that consistently benefits learners, especially those starting with low spatial skill. This paper proposes the spatial encoding strategy (SpES) theory to explain the cognitive mechanisms connecting spatial skill and STEM achievement. To motivate SpES theory, the paper reviews research from STEM education, learning sciences, and psychology. SpES theory provides compelling post hoc explanations for the findings from this literature and aligns with neuroscience models about the functions of brain structures. The paper concludes with a plan for testing the theory's validity and using it to inform future research and instruction. The paper focuses on implications for computing education, but the transferability of spatial skill to STEM performance makes the proposed theory relevant to many education communities.
Chapter 5 – Derivation of Element Matrices and Vectors

Three methods can be used to derive the element matrices and vectors: the direct method, the variational method, and the weighted residual method. Since the direct method is not used commonly, the variational and weighted residual methods are presented. For any physical problem that can be formulated as a variational problem, the application of the conditions for the stationary value of the functional yields the governing differential equation and the natural and geometric boundary conditions. The derivations and solutions of equilibrium, eigenvalue, and propagation problems using the variational method, also known as the Rayleigh–Ritz method, are presented. The weighted residual approach, which does not require a functional, is considered to derive the finite element equations. The point collocation, subdomain collocation, Galerkin, and least squares methods are outlined along with illustrative examples. The application of the weighted residual method for the solution of eigenvalue and propagation problems is also indicated. The derivations of finite element equations using the Galerkin and least squares methods are given along with numerical examples. The strong and weak form formulations of the finite element equations are discussed and the advantages of the weak form formulations are indicated.
CHAPTER 7 – The Approximation Theorem

Publisher Summary This chapter provides an overview of the approximation theorem. The approximation theorem says that an integral current, T, can be approximated by a slight diffeomorphism of a polyhedral chain, P, or, equivalently, that a slight diffeomorphism f#T of T can be approximated By P itself. The approximation P actually coincides with f#T except for an error term, E, of small mass. The chapter also presents the proof of the approximation theorem.
Macroeconomic News and Stock Returns in the United States and Germany

. Using daily data for the January 1997 to June 2002 period, we analyze similarities and differences in the impact of macroeconomic news on stock returns in the United States and Germany. We consider 27 different types of news for the United States and 12 different types of news for Germany. For the United States, we present evidence for asymmetric reactions of stock prices to news. In a boom (recession) period, bad (good) news on GDP growth and unemployment or lower (higher) than expected interest rates may be good news for stock prices. In the period under consideration there is little evidence for asymmetric effects in Germany. However, in the case of Germany, international news appears at least as important as domestic news. There is no evidence that US stock prices are influenced by German news. The analysis of bi-hourly data for Germany confirms these results.
Chapter 6 – Bioenergetics

Publisher Summary This chapter discusses the production and the use of various energy currencies in biological systems. The two energy “currencies” produced in chloroplasts following the trapping of radiant energy are ATP and NADPH. These substances represent the two main classes of energy-storage compounds associated with the electron transfer pathways of photosynthesis and respiration. This chapter examines energy storage in terms of the chemical potential changes accompanying the conversion of a set of reactants into their products. This consideration of the Gibbs free energy helps determine the amount of chemical energy that a particular reaction can store or release. The energy-carrying capacity of ATP in terms of the energetics of its formation and hydrolysis is evaluated. NADPH can be regarded as possessing electrical energy, with the particular amount depending on the oxidation–reduction potential of the system with which it interacts. After considering ATP and NADPH as individual molecules, the chapter places them in their biological context—namely, as part of the bioenergetic scheme of chloroplasts and mitochondria. Such organelle reactions are part of the overall flow of energy from the sun that goes through the biosphere, leading to the nonequilibrium condition that is characteristic of life.
Public and private expenditures on health in a growth model

Abstract This paper introduces endogenous longevity into an otherwise standard overlapping generations model with capital. In the model, a young agent may increase the length of her old age by incurring investments in health. Such private health investments are assumed to be more ‘productive’ if accompanied by complementary tax-financed public health programs. The presence of the public input in private longevity is shown to expose the economy to aggregate endogenous fluctuations and even chaos, and such volatility is impossible in its absence. The model is capable of generating dramatic reversals in life expectancy as has been observed in many countries.
Navigating Around Convex Sets

We review some basic results of convex analysis and geometry in Rn in the context of formulating a differential equation to track the distance between an observer flying outside a convex set K and ...
Opportunities for Enhancing Access and Efficacy of Peer Sponsorship in Substance Use Disorder Recovery

Substance use disorders (SUDs) are characterized by an inability to decrease a substance use (e.g., alcohol or opioids) despite negative repercussions. SUDs are clinically diagnosable, hazardous, and considered a public health issue. Sponsorship, a specialized type of peer mentorship, is vital in the recovery process and originates from 12-step fellowship programs such as Alcoholics Anonymous (AA) and Narcotics Anonymous (NA). To investigate sponsorship relationship practices and to identify design opportunities for digitally-mediated peer support, we conducted 27 in-depth interviews with members of AA and NA. We identified five key sponsorship relationship practices relevant for designing social computing tools to support sponsorship and recovery: 1) assessing dyadic compatibility, 2) managing sponsorship with or without technology, 3) establishing boundaries, 4) building a peer support network, and 5) managing anonymity. We identify social computing and digitally-mediated design opportunities and implications.
The Role of the Medial Prefrontal Cortex in Spatial Margin of Safety Calculations

Humans, like many other animals, pre-empt danger by moving to locations that maximize their success at escaping future threats. We test the idea that spatial margin of safety (MOS) decisions, a form of pre-emptive avoidance, results in participants placing themselves closer to safer locations when facing more unpredictable threats. Using multivariate pattern analysis on fMRI data collected while subjects engaged in MOS decisions with varying attack location predictability, we show that while the hippocampus encodes MOS decisions across all types of threat, a vmPFC anterior-posterior gradient tracked threat predictability. The posterior vmPFC encoded for more unpredictable threat and showed functional coupling with the amygdala and hippocampus. Conversely, the anterior vmPFC was more active for the more predictable attacks and showed coupling with the striatum. Our findings suggest that when pre-empting danger, the anterior vmPFC may provide a safety signal, possibly via predictable positive outcomes, while the posterior vmPFC drives prospective danger signals.
Augmenting Colonoscopy Using Extended and Directional CycleGAN for Lossy Image Translation

Colorectal cancer screening modalities, such as optical colonoscopy (OC) and virtual colonoscopy (VC), are critical for diagnosing and ultimately removing polyps (precursors for colon cancer). The non-invasive VC is normally used to inspect a 3D reconstructed colon (from computed tomography scans) for polyps and if found, the OC procedure is performed to physically traverse the colon via endoscope and remove these polyps. In this paper, we present a deep learning framework, Extended and Directional CycleGAN, for lossy unpaired image-to-image translation between OC and VC to augment OC video sequences with scale-consistent depth information from VC and VC with patient-specific textures, color and specular highlights from OC (e.g. for realistic polyp synthesis). Both OC and VC contain structural information, but it is obscured in OC by additional patient-specific texture and specular highlights, hence making the translation from OC to VC lossy. The existing CycleGAN approaches do not handle lossy transformations. To address this shortcoming, we introduce an extended cycle consistency loss, which compares the geometric structures from OC in the VC domain. This loss removes the need for the CycleGAN to embed OC information in the VC domain. To handle a stronger removal of the textures and lighting, a Directional Discriminator is introduced to differentiate the direction of translation (by creating paired information for the discriminator), as opposed to the standard CycleGAN which is direction-agnostic. Combining the extended cycle consistency loss and the Directional Discriminator, we show state-of-the-art results on scale-consistent depth inference for phantom, textured VC and for real polyp and normal colon video sequences. We also present results for realistic pendunculated and flat polyp synthesis from bumps introduced in 3D VC models.
Computer-Based and Paper-and-Pencil Tests: A Study in Calculus for STEM Majors:

Computer-based testing is an expanding use of technology offering advantages to teachers and students. We studied Calculus II classes for science, technology, engineering, and mathematics majors us...
Diagram Image Retrieval Using Sketch-Based Deep Learning and Transfer Learning

Resolution of the complex problem of image retrieval for diagram images has yet to be reached. Deep learning methods continue to excel in the fields of object detection and image classification applied to natural imagery. However, the application of such methodologies applied to binary imagery remains limited due to lack of crucial features such as textures,color and intensity information. This paper presents a deep learning based method for image-based search for binary patent images by taking advantage of existing large natural image repositories for image search and sketch-based methods (Sketches are not identical to diagrams, but they do share some characteristics; for example, both imagery types are gray scale (binary), composed of contours, and are lacking in texture). We begin by using deep learning to generate sketches from natural images for image retrieval and then train a second deep learning model on the sketches. We then use our small set of manually labeled patent diagram images via transfer learning to adapt the image search from sketches of natural images to diagrams. Our experiment results show the effectiveness of deep learning with transfer learning for detecting near-identical copies in patent images and querying similar images based on content.
On holomorphic mappings between almost Hermitian manifolds

Our goal is to combine the techniques of Xiaokui Yang, Valentino Tosatti, and others to establish a Liouville-type result for almost complex manifolds. The transition to the non-integrable setting is delicate, so we will devote a section to discuss the key differences, and another to introduce the tools we will be using. Afterwards, we present a proof of our main theorem.
Cost of Living Inequality During the Great Recession

Using detailed barcode level data, we construct income-group specific price indices for the period of 2004 to 2010. We find substantial differences across income groups arising mainly during the Great Recession. The annual cost of living inflation of the highest quartile has been on average 0.7 percentage points lower than that of the lowest quartile of the income distribution. The difference can be explained by the way consumers adjusted their shopping behavior to mitigate the crisis. We find that product quality substitution, a margin mostly available to richer households, is the main mechanism explaining the differences in cost of living inflation. Our evidence suggests that not accounting for these differences during economic downturns could lead to significant biases in the calculation of inequality and poverty measures.
Plug-n-Play Alternating Projection Algorithm for Large-scale Security Constraint Optimal Power Flow

In this paper, we present an optimization algorithm based on an alternating projection method to solve the large-scale security constraint optimal power flow (SCOPF) problem in power systems. Power systems are first partitioned into sub-problems, which share common coupling power components. The proposed SCOPF algorithm is fundamentally a distributed computing algorithm, which optimizes power flow in each electrical bus. The output of the local optimization problem will be exchanged among neighboring buses for the overall solution for the whole power system. We performed the algorithm against a modified 14-bus power system and demonstrated that the method is competitive against the commercial products regarding the CPU computation time.
FastMulRFS: fast and accurate species tree estimation under generic gene duplication and loss models.

Motivation Species tree estimation is a basic part of biological research but can be challenging because of gene duplication and loss (GDL), which results in genes that can appear more than once in a given genome. All common approaches in phylogenomic studies either reduce available data or are error-prone, and thus, scalable methods that do not discard data and have high accuracy on large heterogeneous datasets are needed. Results We present FastMulRFS, a polynomial-time method for estimating species trees without knowledge of orthology. We prove that FastMulRFS is statistically consistent under a generic model of GDL when adversarial GDL does not occur. Our extensive simulation study shows that FastMulRFS matches the accuracy of MulRF (which tries to solve the same optimization problem) and has better accuracy than prior methods, including ASTRAL-multi (the only method to date that has been proven statistically consistent under GDL), while being much faster than both methods. Availability and impementation FastMulRFS is available on Github (https://github.com/ekmolloy/fastmulrfs). Supplementary information Supplementary data are available at Bioinformatics online.
Ubiquitin Proteasome System Activity is Suppressed by Curcumin following Exercise-Induced Muscle Damage in Human Skeletal Muscle.

Curcumin is a polyphenolic compound that is suggested to dysregulate the ubiquitin-proteasome system (UPS). This study investigated the effects of curcumin supplementation on markers of UPS activit...