cssi/SciSciGPT-SciSciNet huggingface dataset:
Opinion: Why institutional review boards should have a role in the open science movement

Open science involves the use of practices across the research life cycle that facilitate the transparency, reproducibility, and availability of scientific products and output. Prominent open science practices include registration of study protocols and preanalysis plans; materials, data, and code sharing; and publication of summary findings in open access outlets (1). To achieve openness as the default approach, initiatives are trying to use a systems approach to engage stakeholders—namely, scientific journals, funding agencies, and professional societies (2, 3). Proponents hope to realign the research enterprise with the values of transparency and reproducibility (4). Institutional review boards are overlooked, yet critical, stakeholders for the promotion of open science initiatives that enhance access to research products. Image credit: David Cutler (artist). Institutional review boards (IRBs) are overlooked, yet critical, stakeholders for proponents to engage in open science initiatives (5). For instance, IRBs can require modifications to and even disapprove data sharing plans based on information in the application, protocol, and informed consent forms investigators submit for IRB review (6). Conversely, IRB workflows can increase if a greater number of submissions require higher levels of IRB review because of data sharing plans that risk disclosure of identifiable private information about living individuals. Practical tutorials on ethical open science primarily focus on educating study investigators about their responsibilities to protect human research subjects. IRBs, in turn, need to be informed about open science practices and the impact of their growth on IRB responsibilities to protect human research subjects. In other words, IRB members and professionals themselves should be part of the movement toward open science. Although IRBs are ethics bodies concerned with moral obligations (7 … [↵][1]1To whom correspondence may be addressed. Email: spgrant{at}iu.edu. [1]: #xref-corresp-1-1
RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant.

This paper presents a library of commonsense knowledge, RestKB, developed in modular action language ALM and containing background knowledge relevant to the understanding of restaurant narratives, including stories that describe exceptions to the normal unfolding of such scenarios. We highlight features that KR languages must possess in order to be able to express pertinent knowledge, and expand action language ALM as needed. We show that encoding the knowledge base in ALM facilitates its piecewise construction and testing, and improves the generality and quality of the captured information, in comparison to an initial ASP encoding. The knowledge base was used in a system for reasoning about stereotypical activities, evaluated on the restaurant domain.
Improving Supervised Phase Identification Through the Theory of Information Losses

This paper considers the problem of Phase Identification in power distribution systems. In particular, it focuses on improving supervised learning accuracies by focusing on exploiting some of the problem’s information theoretic properties. This focus, along with recent advances in Information Theoretic Machine Learning (ITML), helps us to create two new techniques. The first transforms a bound on information losses into a data selection technique. This is important because phase identification data labels are difficult to obtain in practice. The second interprets the properties of distribution systems in the terms of ITML. This allows us to obtain an improvement in the representation learned by any classifier applied to the problem. We tested these two techniques experimentally on real datasets and have found that they yield phenomenal performance in every case. In the most extreme case, they improve phase identification accuracy from 51.7% to 97.3%. Furthermore, since many problems share the physical properties of phase identification exploited in this paper, the techniques can be applied to a wide range of similar problems.
The Impact of Insurance Accounting on Business Reality and Financial Stability

The insurance industry has become more important for systemic financial stability. As a result, the supervision and disclosure of financial risks of insurance companies need to be strengthened. The insurance industry's increasing systemic importance also suggests that there is a need to search for some middle ground in the discussion of fair value accounting to mitigate potentially destabilizing financial volatility.
Recent increases in drought frequency cause observed multi-year drought legacies in the tree rings of semi-arid forests

Recent analyses on the length of drought recovery in forests have shown multi-year legacies, particularly in semi-arid, coniferous ecosystems. Such legacies are usually attributed to ecophysiological memory, although drought frequency itself, and its effect on overlapping recovery times, could also contribute. Here, we describe a multi-decadal study of drought legacies using tree-ring carbon-isotope ratios (δ13C) and ring-width index (RWI) in Pinus ponderosa at 13 montane sites traversing a winter–summer precipitation gradient in the Southwestern U.S. Sites and trees were selected to avoid collection biases that exist in archived tree-ring databanks. The spatial hydroclimate gradient and winter–summer seasonal patterns were well predicted by seasonal and inter-annual correlations between δ13C and atmospheric vapor pressure deficit (VPD). Using VPD, we found that the probability of extreme drought has increased up to 70% in this region during the past two decades. When the recent increase in drought frequency was not considered, multi-year legacies in both δ13C and RWI were observed at most sites. When the increase in drought frequency was detrended from tree-ring chronologies, some sites exhibited short legacies (1–2 years) in both δ13C and RWI, and there was a sight trend for longer legacies in RWI. However, when considered broadly across the region and multiple decades, no significant legacies were observed, which contrasts with past studies. Our results reveal that a contribution to observed multi-year legacies is related to shifts in the climate system itself, an exogenous factor, that must be considered along with physiological memory.
A New Algorithm for Fast Generalized DFTs

We give an new arithmetic algorithm to compute the generalized Discrete Fourier Transform (DFT) over finite groups G. The new algorithm uses O(mGmω /2 + o(1)) operations to compute the generalized DFT over finite groups of Lie type, including the linear, orthogonal, and symplectic families and their variants, as well as all finite simple groups of Lie type. Here ω is the exponent of matrix multiplication, so the exponent ω/2 is optimal if ω = 2.Previously, “exponent one” algorithms were known for supersolvable groups and the symmetric and alternating groups. No exponent one algorithms were known, even under the assumption ω = 2, for families of linear groups of fixed dimension, and indeed the previous best-known algorithm for SL2(Fq) had exponent 4/3 despite being the focus of significant effort. We unconditionally achieve exponent at most 1.19 for this group and exponent one if ω = 2.Our algorithm also yields an improved exponent for computing the generalized DFT over general finite groups G, which beats the longstanding previous best upper bound for any ω. In particular, assuming ω = 2, we achieve exponent √ 2, while the previous best was 3/2.
Educational Intervention Improves Proton Pump Inhibitor Stewardship in Outpatient Gastroenterology Clinics.

Background Improper chronic proton pump inhibitor (PPI) use has risen significantly in the last few decades. In our gastroenterology trainees' clinics, we aimed to optimize PPI usage. Methods We collected baseline data on patients' PPI use for 8 weeks. Based on gastroenterology society guidelines, we determined conditions for appropriate PPI use. If the indication could not be determined, it was categorized as "unknown". Generated from the three most frequent causes for inappropriate PPI use, interventions were developed to correct each issue. Following a brief educational session, trainees implemented these interventions over a subsequent 8-week interval. Results During our pre-intervention period, trainees evaluated 263 patients who were prescribed a PPI. In 49% of the cases, the use of PPI was deemed inappropriate. The most common reasons were: gastroesophageal reflux disease (GERD) which was never titrated to the lowest effective dose, twice daily dosing for Barrett's esophagus (BE) chemoprevention and unknown indication. During our intervention period, trainees evaluated 145 patients prescribed a PPI for GERD with well-controlled symptoms in 101 cases. PPI had not been titrated to lowest effective dose in 37 cases prompting intervention which was successful in 23 cases. PPI indication was unknown in 17 cases prompting a message to the prescribing provider to review appropriateness. Two cases of BE chemoprevention with twice daily dosing were appropriately reduced to daily dosing. Ultimately, after intervention, PPI use was deemed appropriate after intervention in 172 (77%) cases. Conclusions Improper chronic PPI use was significant. Focusing intervention efforts on PPI use for GERD, BE and unknown indications substantially increased appropriateness of PPI use.
Characterizing Distances of Networks on the Tensor Manifold

At the core of understanding dynamical systems is the ability to maintain and control the systems behavior that includes notions of robustness, heterogeneity, and/or regime-shift detection. Recently, to explore such functional properties, a convenient representation has been to model such dynamical systems as a weighted graph consisting of a finite, but very large number of interacting agents. This said, there exists very limited relevant statistical theory that is able cope with real-life data, i.e., how does perform analysis and/or statistics over a “family” of networks as opposed to a specific network or network-to-network variation. Here, we are interested in the analysis of network families whereby each network represents a “point” on an underlying statistical manifold. To do so, we explore the Riemannian structure of the tensor manifold developed by Pennec previously applied to Diffusion Tensor Imaging (DTI) towards the problem of network analysis. In particular, while this note focuses on Pennec definition of “geodesics” amongst a family of networks, we show how it lays the foundation for future work for developing measures of network robustness for regime-shift detection. We conclude with experiments highlighting the proposed distance on synthetic networks and an application towards biological (stem-cell) systems.
Emerging strategies in peripheral T-cell lymphoma

Peripheral T-cell lymphomas (PTCLs) are a heterogenous group of aggressive non-Hodgkin lymphomas that are less chemosensitive than their B-cell counterparts. Until recently, standard therapy did not distinguish between subtypes, and deeper understanding of the biology of these diseases was lacking. The availability of targeted therapy and more sophisticated subtype classification has translated into the development of novel treatment options for these rare diseases. This includes the development of a brentuximab vedotin-based upfront chemotherapy regimen that confers an overall survival benefit for a subset of patients. Clinical trials of targeted agents, as well as development of better preclinical models of PTCL, are leading to therapeutic advances in the field, including the development of phosphoinositide-3-kinase inhibitors, histone deacetylase inhibitor-based strategies, CD30-directed strategies, Janus kinase inhibitors, and spleen-associated tyrosine kinase inhibitors. Better understanding of the biology of these diseases based on gene expression profiling, minimal residual disease evaluation, and modeling in patient-derived xenografts should help define mechanisms of response and resistance to therapy. Given the complex biology of these heterogeneous lymphomas, well-tolerated combination strategies targeted toward specific subtypes of PTCL can lead to advances in the field. Similar to the story of brentuximab vedotin, development of effective therapies in the salvage setting will likely lead to improved upfront strategies in PTCLs, and ultimately a more personalized approach.
Depletion of microbiome-derived molecules in the host using Clostridium genetics

The gut microbiota produce hundreds of molecules that are present at high concentrations in the host circulation. Unraveling the contribution of each molecule to host biology remains difficult. We developed a system for constructing clean deletions in Clostridium spp., the source of many molecules from the gut microbiome. By applying this method to the model commensal organism Clostridium sporogenes, we knocked out genes for 10 C. sporogenes-derived molecules that accumulate in host tissues. In mice colonized by a C. sporogenes for which the production of branched short-chain fatty acids was knocked out, we discovered that these microbial products have immunoglobulin A-modulatory activity.
Explorations in Teaching the Phenomenological Method: Challenging Psychology Students to «Grasp at Meaning» in Human Science Research

In order to fulfill our collective calling to understand and to heal human persons, psychologists need to be taught ways of listening, observing, and knowing others that respect and preserve the richness of human experience as it is lived. This article serves to introduce current and future researchers of the human condition to a perspective that values what is meaningful in human life. This paper is devoted to two goals: (a) to present pedagogical strategies for the teaching of phenomenological method to psychology students; and (b) to present an introduction to the methodology of phenomenological research. What are we actually doing when attempting to conduct this kind of «scientific» research? More importantly, how do we teach others to do what it has taken our whole career to learn? The history of the development of phenomenological method in psychology is traced from its roots at Duquesne in the early 1970s to its further implementation at the University of Dallas over the past 45 years. The «workshop» approach to teaching qualitative inquiry is explored, along with the phenomenological and hermeneutic principles underlying the analysis of verbal self-report data. Formulating a research question, distinguishing the research phenomenon from the situation interrogated, engaging in direct «intuitive contact» with the phenomenon, reflexivity with respect to one’s biases and presuppositions, the carrying-out of intentional analyses, and «deep listening» to the testimonies of others will be presented and illustrated with examples taken from research workshops over the past three decades.
True Nonlinear Dynamics from Incomplete Networks

We study nonlinear dynamics on complex networks. Each vertex i has a state xi which evolves according to a networked dynamics to a steady-state xi*. We develop fundamental tools to learn the true steady-state of a small part of the network, without knowing the full network. A naive approach and the current state-of-the-art is to follow the dynamics of the observed partial network to local equilibrium. This dramatically fails to extract the true steady state. We use a mean-field approach to map the dynamics of the unseen part of the network to a single node, which allows us to recover accurate estimates of steady-state on as few as 5 observed vertices in domains ranging from ecology to social networks to gene regulation. Incomplete networks are the norm in practice, and we offer new ways to think about nonlinear dynamics when only sparse information is available.
Parallel 1024-ch Cyclic Voltammetry on Monolithic CMOS Electrochemical Detector Array

Large-scale microelectrode arrays offers enhanced spatiotemporal resolution in electrophysiology studies. In this paper, we discuss the design and performance of an electrochemical detector array which is capable of 1024-ch parallel cyclic voltammetry. The electrochemical detector is fabricated using a custom-designed CMOS chip, which integrates both the circuity and on-chip microelectrode array, to operate the array and record electrochemical signals. For parallel 1024-ch recordings, 1024 capacitor-based integrating transimpedance amplifiers are designed. The amplifier design features bipolar capabilities for measuring both negative and positive electrochemical currents due to reduction and oxidation reactions. The cyclic voltammetry functionality was validated by measuring the double-layer capacitance of the on-chip electrode array. Cyclic voltammetry can be used to examine the quality of electrochemical electrodes by measuring the double-layer capacitance that forms at the electrode-electrolyte interface. Double-layer capacitance is a function of the effective area of the electrode. A contaminated electrode can have smaller effective area resulting in smaller double-layer capacitance. Using the parallel cyclic voltammetry capability of the monolithic CMOS device, the double layer capacitance of all 1024 electrodes can be simultaneously measured to examine the status of the electrode array in real time. The initial measurement of the electrode array showed a mean capacitance of 0.47 nF. After plasma treatment to remove contamination on the electrode’s surface, the increased capacitance was 1.36 nF nearly tripling the effective surface area. This method can accelerate the characterization of an electrode array before analytical experiments to provide well-controlled electrochemical electrodes, which are crucial in conducting reliable electrochemical measurements.
Motion-Tolerant Beamforming with Deformable Microphone Arrays

Microphone arrays are usually assumed to have rigid geometries: the microphones may move with respect to the sound field but remain fixed relative to each other. However, many useful arrays, such as those in wearable devices, have sensors that can move relative to each other. We compare two approaches to beamforming with deformable microphone arrays: first, by explicitly tracking the geometry of the array as it changes over time, and second, by designing a time-invariant beamformer based on the second-order statistics of the moving array. The time-invariant approach is shown to be appropriate when the motion of the array is small relative to the acoustic wavelengths of interest. The performance of the proposed beamforming system is demonstrated using a wearable microphone array on a moving human listener in a cocktail-party scenario.
Electromagnetically induced transparency (EIT) amplitude noise spectroscopy

Intensity noise cross-correlation of the polarization eigenstates of light emerging from an atomic vapor cell in the Hanle EIT configuration results in high resolution spectroscopy even with free-running semiconductor lasers. We show that the character of the observed intensity noise in any output polarization basis can be modeled as a Markov process in the input light fields’ amplitudes that excite the response of a three-level medium. This method has promise as an inexpensive and simpler approach to vector magnetometry and has applications in timekeeping and as a probe of dynamics of atomic coherence in warm vapor cells.
Prevention of oxidative stress-induced metabolic aberrations in the neural retina by caffeine

Oxyradical-induced damage to the retina has been implicated as one of the contributing factors in the pathogenesis of vision-impairing diseases such as diabetic retinopathy (DR) and age-related macular degeneration (AMD). It is hypothesized that caffeine, a nutraceutical antioxidant, will be effective in preventing metabolic aberrations in the neural retina exposed to oxygen radicals. This hypothesis is based on our previous studies demonstrating its effectiveness in preventing oxidative damage to the lens, and in protecting the neural retina against UV-A- and peroxide-induced biochemical damage. Bovine neural retinas were incubated in medium 199 at 37°C for 6 hours. Xanthine (XA)-xanthine oxidase (XO) were used to generate reactive oxygen species (ROS). Incubations were conducted in 3 groups- control, experimental (with XA+XO), and caffeine group (XA + XO+ 5mM caffeine). Retinas were then processed for determining protein, lactate and pyruvate concentrations. Lactate concentration in the controls was 2.62±0.43mM/mg protein, decreasing to 1.04±0.3 mM/mg protein in the presence of XA+XO. Its level in the caffeine group was significantly higher, 2.44±0.65 mM/mg protein, close to the controls. Pyruvate concentration in the controls was 0.16±0.05mM/mg protein, which declined significantly with XA+XO to 0.066±0.02 mM/mg protein. Such decrease was substantially prevented in the caffeine group, wherein its concentration was 0.156±0.03mM/mg protein. Caffeine was thus found to be highly effective in preventing metabolic aberrations, due to its ability to scavenge oxyradicals and thereby possibly prevent inactivation of key enzymes. Such effect of caffeine in maintaining metabolism of the neural retina exposed to ROS has been shown for the first time.
Measurements of the viscosity of compressed gaseous and liquid fluorine

Abstract A torsionally oscillating quartz crystal has been used to make absolute measurements of the coefficient of shear viscosity for compressed fluid fluorine at temperatures from 90 to 300 K, at pressures up to 20 MPa; and for saturated liquid fluorine at temperatures from 70 to 144 K. Special features of the viscometer, necessary to provide an instrument suitable for measurements on an extremely reactive fluid such as fluorine, are described. The accuracy of the results is estimated to be of the order of 2% with the precision somewhat better, approximately 0.5%. The dependence of the viscosity on density has been investigated by representing the gaseous data along isotherms in power-series expansions. Dilute-gas viscosities were subsequently derived from this analysis. An equation has been developed that can be used to calculate the viscosity of fluorine over the range of the present measurements. Comparisons with experimental data and theoretical predictions are presented for the few measurements and calculations previously attempted for fluorine.
Real-Time Quad-Rotor Path Planning Using Convex Optimization and Compound State-Triggered Constraints

The contribution of this paper is the application of compound state-triggered constraints (STCs) to real-time quadrotor path planning. Originally developed for rocket landing applications, STCs are made up of a trigger condition and a constraint condition that are arranged such that satisfaction of the former implies satisfaction of the latter. Compound STCs go a step further by allowing multiple trigger and constraint conditions to be combined via Boolean “and” or “or” operations. The logical implications embodied by STCs can be formulated using continuous variables, and thus enable the incorporation of discrete decision making into a continuous optimization framework. In this paper, compound STCs are used to solve quad-rotor path planning problems that would typically require the use of computationally expensive mixed-integer programming techniques. Two scenarios are considered: (1) a quad-rotor flying through a hoop, and (2) a pair of quadrotors carrying a beam-like payload through an obstacle course. Successive convexification is used to solve the resulting non-convex optimization problem. Monte-Carlo simulation results show that our approach can reliably generate trajectories at rates upwards of 3 and 1.5 Hz for the first and second scenarios, respectively.
Oct4-Mediated Inhibition of Lsd1 Activity Promotes the Active and Primed State of Pluripotency Enhancers.

Summary An aberrant increase in pluripotency gene (PpG) expression due to enhancer reactivation could induce stemness and enhance the tumorigenicity of cancer stem cells. Silencing of PpG enhancers (PpGe) during embryonic stem cell differentiation involves Lsd1-mediated H3K4me1 demethylation and DNA methylation. Here, we observed retention of H3K4me1 and DNA hypomethylation at PpGe associated with a partial repression of PpGs in F9 embryonal carcinoma cells (ECCs) post-differentiation. H3K4me1 demethylation in F9 ECCs could not be rescued by Lsd1 overexpression. Given our observation that H3K4me1 demethylation is accompanied by strong Oct4 repression in P19 ECCs, we tested if Oct4 interaction with Lsd1 affects its catalytic activity. Our data show a dose-dependent inhibition of Lsd1 activity by Oct4 and retention of H3K4me1 at PpGe in Oct4-overexpressing P19 ECCs. These data suggest that Lsd1-Oct4 interaction in cancer stem cells could establish a “primed” enhancer state that is susceptible to reactivation, leading to aberrant PpG expression.
Solid-state dewetting instability in thermally-stable nanocrystalline binary alloys

Abstract Practical applications of nanocrystalline metallic thin films are often limited by instabilities. In addition to grain growth, the thin film itself can become unstable and collapse into islands through solid-state dewetting. Selective alloying can improve nanocrystalline stability, but the impact of this approach on dewetting is not clear. In this study, two alloys that exhibit nanocrystalline thermal stability as ball milled powders are evaluated as thin films. While both alloys demonstrated dewetting behavior following annealing, the severity decreased in more dilute compositions. Ultimately, a balance may be struck between nanocrystalline stability and thin film structural stability by tuning dopant concentration.
Distinct Symptom-Specific Treatment Targets for Circuit-Based Neuromodulation.

Objective:Treatment of different depression symptoms may require different brain stimulation targets with different underlying brain circuits. The authors sought to identify such targets, which cou...
Detecting Safety and Security Faults in PLC Systems with Data Provenance

Programmable Logic Controllers are an integral component for managing many different industrial processes (e.g., smart building management, power generation, water and wastewater management, and traffic control systems), and manufacturing and control industries (e.g., oil and natural gas, chemical, pharmaceutical, pulp and paper, food and beverage, automotive, and aerospace). Despite being used widely in many critical infrastructures, PLCs use protocols which make these control systems vulnerable to many common attacks, including man-in-the-middle attacks, denial of service attacks, and memory corruption attacks (e.g., array, stack, and heap overflows, integer overflows, and pointer corruption). In this paper, we propose PLC–PROV, a system for tracking the inputs and outputs of the control system to detect violations in the safety and security policies of the system. We consider a smart building as an example of a PLC-based system and show how PLC–PROV can be applied to ensure that the inputs and outputs are consistent with the intended safety and security policies.
Neural Bases of Phonological and Semantic Processing in Early Childhood.

During the early period of reading development, children gain phonological (letter-to-sound mapping) and semantic knowledge (storage and retrieval of word meaning). Their reading ability changes ra...
Modeling Physical Processes at Galactic Scales and Above

We start with modeling the IGM (in particular, Lyman-\(\alpha \) forest). For that purpose, we will review some of the basic physics of low-density photo-ionized gas and its observational diagnostics. We will explore how thermal pressure makes gas distribution deviate from the dark matter, how the gas temperature evolves in time under the effect of cosmic ionizing background, and how observed spectra emerge from the interplay of density, temperature, and velocity. We will briefly review most important observations of the IGM and will end up with a mystery. After IGM, we continue our journey (together with cosmic gas) through the dense filaments of large-scale structure to galactic halos. We will explore various ways the gas takes to accrete onto halos, and how hot gas in the halo uses radiative cooling to continue its journey to the galactic disk, becoming the ISM of galaxies. On our way we meet wonderful “cool streams”, explore various ways to account for cooling and heating in the gas, and will end up with another mystery story of high velocity clouds. After a brief refresher on galaxy formation, we explore the structure and stability of galactic disks, going well beyond standard Toomre criterion. We then focus our attention to gas, and after a brief overview of atomic and ionized gas dive even deeper into the molecular ISM. We will explore the atomic-to-molecular transition in exquisite detail, before committing a grave mistake of opening a cosmic Pandora box of the X factor, inside which, as in a Russian Matrioshka doll, we find another Pandora box, and then another, until in total desperation we give up and ready ourselves to jumping into the Holy Grail of all of astronomy-star formation. That subject is so huge, that we will only touch it gently, at the largest scales, and will not go much beyond the canonical Kennicutt-Schmidt relation. We will, though, think about it in 2D, realizing that the spatial scale is as an important physical parameter as the density of the molecular gas itself. We will theorize about how the 2D scale/density plane can be charted by star formation rate, but will not arrive at an answer. At the end, we will briefly get familiar with a novel idea of using the Excursion Set formalism as a theory of star formation and, very briefly, familiarize ourselves with numerous ways in which stars affect their environments, collectively known under a buzzname of “stellar feedback”.
A bi-polar theory of nominal and clause structure and function

A bi-polar theory of the structure and function of nominals and clauses is presented in which a specifier, functioning as a referential pole, and a head, functioning as a relational pole, combine to form a referring expression. The theory applies to both object referring expressions, in the case of nominals, and situation referring expressions, in the case of clauses. The bi-polar theory is contrasted with X-Bar Theory — a uni-polar theory in which the head uniquely determines the type of the larger expression in which it occurs. Uni-polar theories adopt a strong notion of endocentricity, which is rejected in the bi-polar theory, where both the specifier and the head make significant and meaningful contributions to the larger expressions in which they occur. The bi-polar theory is also contrasted with Langacker’s conception of the basic structure and function of nominals and clauses.
Curve Fitting and Editing via Interactive Graphics

The system described here allows a user to enter a curve into an IBM 360/40 computer via a RAND tablet [1], and interactively to specify various ways of fitting, editing and displaying the curve on an IBM 2250 scope (see Fig. 1). It was developed primarily as a tool to extend the analysis of multivariate function representation (described by Boehm [2]) from tabular methods to polynomial methods. We decided to use an interactive graphics approach for three main reasons:1. Experience has shown that much time is spent visually editing curves for input errors; this used to be done on an SC-4020 with one-day turn-around.2. We wanted to experiment rapidly with choice of form, as multivariate functions are hard to classify in terms of representability.3. The facility was available, along with a basic software support package.
Using action research to improve learning and formative assessment to conduct research

The paper reports on how educational research informed and supported both the process of refinement of introductory physics laboratory instruction and student development of scientific abilities. In particular we focus on how the action research approach paradigm combined with instructional approaches such as scaffolding and formative assessment can be used to design the learning environment, investigate student learning, revise curriculum materials, and conduct subsequent assessment. As the result of the above efforts we found improvement in students' scientific abilities over the course of three years. We suggest that the process used to improve the curriculum under study can be extended to many instructional innovations.
Reduced-rank regression: A useful determinant identity

We formulate an identity for the determinant of a product involving rectangular matrices. The identity can be used to derive the maximum likelihood estimator in reduced-rank regressions with Gaussian innovations. Furthermore, the identity sheds light on the structure of the estimation problem that arises when the reduced-rank parameters are subject to additional constraints.
Spatial Regression Models Using Inter-Region Distances in a Non-Random Context

This article considers spatial data z( s 1), z( s 2),…, z( s n ) collected at n locations, with the objective of predicting z( s 0) at another location. The usual method of analysis for this problem is kriging, but here we introduce a new signal-plus-noise model whose essential feature is the identification of hot spots. The signal decays in relation to distance from hot spots. We show that hot spots can be located with high accuracy and that the decay parameter can be estimated accurately. This new model compares well to kriging in simulations.
Making the transition: How asset building services can promote positive adult outcomes for foster youth

Abstract Foster youth in the U.S. often face a multitude of adverse outcomes, including low educational attainment, elevated rates of adult poverty, and disproportionately high levels of adult homelessness. One newer area of social policy research and advocacy, asset building, may help explain some of these disparities. Foster youth face several barriers to asset building. For example, many youth have several placements during their stay in care, resulting in youth receiving inconsistent schooling, mentoring, and support, and facing limited opportunities to work, save money, or build academic and professional networks. This paper examines the frequency with which transition-age foster youth receive asset building services and whether the youth who receive services experience improved outcomes compared to those who do not. Analyzing data from the National Youth in Transition Database and using a Propensity Score Matching methodology, this study finds that youth receiving Budgeting and Financial Education Services and Post-Secondary Education Services experience significantly improved outcomes, including reduced likelihood of homelessness and increased likelihood of employment and educational enrollment. However, only 29% of youth receive Budgeting and Financial Education Services, and only 19% of youth receive Post-Secondary Education Services. Service receipt also covaries with demographics, including race/ethnicity and education level. These findings have noteworthy implications for both policy and practice as asset building for foster youth is a potentially promising realm for public service expansion.
Cigarette Taxes and Smoking in the Long Run

Researchers have focused on the contemporaneous relationship between cigarette taxes and smoking, while the longer-run effects of cigarette taxes have received little attention. Using individual-level panel data from 1970-2017, we estimate the effects of cigarette taxes experienced as a teenager on smoking later in life. We find that a one-dollar increase in the cigarette tax experienced between the ages of 12 and 17 is associated with substantial reductions in smoking participation and intensity among adults in their 20s through mid-60s. Among first-time mothers, it is associated with a reduction in the likelihood of smoking the year of giving birth.
Schemes Supported on the Singular Locus of a Hyperplane Arrangement in $\mathbb P^n$

We introduce the use of liaison addition to the study of hyperplane arrangements. For an arrangement, $\mathcal A$, of hyperplanes in $\mathbb P^n$, $\mathcal A$ is free if $R/J$ is Cohen-Macaulay, where $J$ is the Jacobian ideal of $\mathcal A$. Terao's conjecture says that freeness of $\mathcal A$ is determined by the combinatorics of the intersection lattice of $\mathcal A$. We study the Cohen-Macaulayness of three other ideals, all unmixed, that are closely related to $\mathcal A$. Let $\overline J = \mathfrak q_1 \cap \dots \cap \mathfrak q_s$ be the intersection of height two primary components of $J$ and $\sqrt{J} = \mathfrak p_1 \cap \dots \cap \mathfrak p_s$ be the radical of $J$. Our third ideal is $\mathfrak p_1^{b_1} \cap \dots \cap \mathfrak p_s^{b_s}$ for suitable $b_1,\dots, b_s$. With a mild hypothesis we use liaison addition to show that all of these ideals are Cohen-Macaulay. When our hypothesis does not hold, we show that these ideals are not necessarily Cohen-Macaulay, and that Cohen-Macaulayness of any of these ideals does not imply Cohen-Macaulayness of any of the others. While we do not study the freeness of $\mathcal A$, we show by example that the Betti diagrams can vary even for arrangements with the same combinatorics. We then study the situation when the hypothesis does not hold. For equidimensional curves in $\mathbb P^3$, the Hartshorne-Rao module from liaison theory measures the failure of an ideal to be Cohen-Macaulay, degree by degree, and also determines the even liaison class of such a curve. We show that for any positive integer $r$ there is an arrangement $\mathcal A$ for which $R/\overline J$ fails to be Cohen-Macaulay in only one degree, and this failure is by $r$; we also give an analogous result for $\sqrt{J}$. We draw consequences for the corresponding even liaison class of the curve defined by $\overline J$ or by $\sqrt{J}$.
Tetra-Tagging: Word-Synchronous Parsing with Linear-Time Inference

We present a constituency parsing algorithm that, like a supertagger, works by assigning labels to each word in a sentence. In order to maximally leverage current neural architectures, the model scores each word’s tags in parallel, with minimal task-specific structure. After scoring, a left-to-right reconciliation phase extracts a tree in (empirically) linear time. Our parser achieves 95.4 F1 on the WSJ test set while also achieving substantial speedups compared to current state-of-the-art parsers with comparable accuracies.
Evaluating the Effect of Timeline Shape on Visualization Task Performance

Timelines are commonly represented on a horizontal line, which is not necessarily the most effective way to visualize temporal event sequences. However, few experiments have evaluated how timeline shape influences task performance. We present the design and results of a controlled experiment run on Amazon Mechanical Turk (n=192) in which we evaluate how timeline shape affects task completion time, correctness, and user preference. We tested 12 combinations of 4 shapes --- horizontal line, vertical line, circle, and spiral  and 3 data types  recurrent, non-recurrent, and mixed event sequences. We found good evidence that timeline shape meaningfully affects user task completion time but not correctness and that users have a strong shape preference. Building on our results, we present design guidelines for creating effective timeline visualizations based on user task and data types. A free copy of this paper, the evaluation stimuli and data, and code are available https://osf.io/qr5yu/
Trapped Factors and China’s Impact on Global Growth

When China’s accession to the WTO exposed European firms to import competition, they responded by increasing their investment in innovation. This response was stronger in industries and firms where factors of production were less mobile. Motivated by this evidence, we incorporate “trapped factors” at the micro level into a general equilibrium model of product-cycle trade and growth. In a calibrated version of the model that starts with a baseline growth rate of 2%, trade integration between the OECD and low-wage countries can increase the steady-state growth rate to 2.4% per year. Factors that are trapped at a firm by an unexpected change in trade policy do not change this long-run growth rate, but in the medium run, they could have a noticeable effect on aggregate growth. Simulations of the model show that in the first decade after liberalization, growth jumps to 2.7% per year and that trapped factors account for almost all of the 0.3% = 2.7% − 2.4% increase above the steady state growth rate.
Explaining Multi-stage Tasks by Learning Temporal Logic Formulas from Suboptimal Demonstrations

We present a method for learning multi-stage tasks from demonstrations by learning the logical structure and atomic propositions of a consistent linear temporal logic (LTL) formula. The learner is given successful but potentially suboptimal demonstrations, where the demonstrator is optimizing a cost function while satisfying the LTL formula, and the cost function is uncertain to the learner. Our algorithm uses the Karush-Kuhn-Tucker (KKT) optimality conditions of the demonstrations together with a counterexample-guided falsification strategy to learn the atomic proposition parameters and logical structure of the LTL formula, respectively. We provide theoretical guarantees on the conservativeness of the recovered atomic proposition sets, as well as completeness in the search for finding an LTL formula consistent with the demonstrations. We evaluate our method on high-dimensional nonlinear systems by learning LTL formulas explaining multi-stage tasks on 7-DOF arm and quadrotor systems and show that it outperforms competing methods for learning LTL formulas from positive examples.
Integrating Security in Resource-Constrained Cyber-Physical Systems

Defense mechanisms against network-level attacks are commonly based on the use of cryptographic techniques, such as lengthy message authentication codes (MAC) that provide data integrity guarantees. However, such mechanisms require significant resources (both computational and network bandwidth), which prevents their continuous use in resource-constrained cyber-physical systems (CPS). Recently, it was shown how physical properties of controlled systems can be exploited to relax these stringent requirements for systems where sensor measurements and actuator commands are transmitted over a potentially compromised network; specifically, that merely intermittent use of data authentication (i.e., at occasional time points during system execution), can still provide strong Quality-of-Control (QoC) guarantees even in the presence of false-data injection attacks, such as Man-in-the-Middle (MitM) attacks. Consequently, in this work, we focus on integrating security into existing resource-constrained CPS, in order to protect against MitM attacks on a system where a set of control tasks communicates over a real-time network with system sensors and actuators. We introduce a design-time methodology that incorporates requirements for QoC in the presence of attacks into end-to-end timing constraints for real-time control transactions, which include data acquisition and authentication, real-time network messages, and control tasks. This allows us to formulate a mixed integer linear programming-based method for direct synthesis of schedulable tasks and message parameters (i.e., deadlines and offsets) that do not violate timing requirements for the already deployed controllers, while adding a sufficient level of protection against network-based attacks; specifically, the synthesis method also provides suitable intermittent authentication policies that ensure the desired QoC levels under attack. To additionally reduce the security-related bandwidth overhead, we propose the use of cumulative message authentication at time instances when the integrity of messages from subsets of sensors should be ensured. Furthermore, we introduce a method for the opportunistic use of the remaining resources to further improve the overall QoC guarantees while ensuring system (i.e., task and message) schedulability. Finally, we demonstrate applicability and scalability of our methodology on synthetic automotive systems as well as a real-world automotive case-study.
Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networks

The human brain displays rich communication dynamics that are thought to be particularly well-reflected in its marked community structure. Yet, the precise relationship between community structure in structural brain networks and the communication dynamics that can emerge therefrom is not well understood. In addition to offering insight into the structure-function relationship of networked systems, such an understanding is a critical step toward the ability to manipulate the brain's large-scale dynamical activity in a targeted manner. We investigate the role of community structure in the controllability of structural brain networks. At the region level, we find that certain network measures of community structure are sometimes statistically correlated with measures of linear controllability. However, we then demonstrate that this relationship depends on the distribution of network edge weights. We highlight the complexity of the relationship between community structure and controllability by performing numerical simulations using canonical graph models with varying mesoscale architectures and edge weight distributions. Finally, we demonstrate that weighted subgraph centrality, a measure rooted in the graph spectrum, and which captures higher order graph architecture, is a stronger and more consistent predictor of controllability. Our study contributes to an understanding of how the brain's diverse mesoscale structure supports transient communication dynamics.
Revisiting steady viscous flow of a generalized Newtonian fluid through a slender elastic tube using shell theory

A flow vessel with an elastic wall can deform significantly due to viscous fluid flow within it, even at vanishing Reynolds number (no fluid inertia). Deformation leads to an enhancement of throughput due to the change in cross-sectional area. The latter gives rise to a non-constant pressure gradient in the flow-wise direction and, hence, to a nonlinear flow rate--pressure drop relation (unlike the Hagen--Poiseuille law for a rigid tube). Many biofluids are non-Newtonian, and are well approximated by generalized Newtonian (say, power-law) rheological models. Consequently, we analyze the problem of steady low Reynolds number flow of a generalized Newtonian fluid through a slender elastic tube by coupling fluid lubrication theory to a structural problem posed in terms of Donnell shell theory. A perturbative approach (in the slenderness parameter) yields analytical solutions for both the flow and the deformation. Using matched asymptotics, we obtain a uniformly valid solution for the tube's radial displacement, which features both a boundary layer and a corner layer caused by localized bending near the clamped ends. In doing so, we obtain a ``generalized Hagen--Poiseuille law'' for soft microtubes. We benchmark the mathematical predictions against three-dimensional two-way coupled direct numerical simulations (DNS) of flow and deformation performed using the commercial computational engineering platform by ANSYS. The simulations show good agreement and establish the range of validity of the theory. Finally, we discuss the implications of the theory on the problem of the flow-induced deformation of a blood vessel, which is featured in some textbooks.