cssi/SciSciGPT-SciSciNet huggingface dataset:
FunTAL: reasonably mixing a functional language with assembly

We present FunTAL, the first multi-language system to formalize safe interoperability between a high-level functional language and low-level assembly code while supporting compositional reasoning about the mix. A central challenge in developing such a multi-language is bridging the gap between assembly, which is staged into jumps to continuations, and high-level code, where subterms return a result. We present a compositional stack-based typed assembly language that supports components, comprised of one or more basic blocks, that may be embedded in high-level contexts. We also present a logical relation for FunTAL that supports reasoning about equivalence of high-level components and their assembly replacements, mixed-language programs with callbacks between languages, and assembly components comprised of different numbers of basic blocks.
An Educational Environment for the Teaching of Quantitative Feedback Theory

Abstract During the past few years there has developed a widespread interest in Horowitz’s Quantitative Feedback Theory (QFT) because of its potential for solving complex real-world control problems. In particular, QFT focuses on achieving the desired system performance despite plant models with parameter uncertainly and additive disturbances. The design of a QFT robust controller requires the formulation of quantitative factors representing acceptable input-output models, a set of plant models due to parameter uncertainity and graphical composition. To accomplished this task requires considerable numerical and symbolic manipulation and therefore implies that an extensive educational environment be provided. The intent of this paper is to present such an educational environment in which extensive student design projects can be accomplished. Both the multi-input single-output (MISO) and the multiple-input multiple-output (MIMO) models are depicted in the classroom along with discussion of various CAD packages. The QFT MIMO controller development is approached by converting the MIMO model into a number of MISO models. Both the continuous and discrete QFT design procedures are elements of the educational program. Discussion of appropriate prerequisites for the various models is included in the paper as an integral element of a control engineer’s education. The major educational emphasis is on the development of a student’s ability to apply the unified QFT method. Various aspects of the QFT educational CAD capabilities exist under various computer operating system environments.
Formalization of design for physical model of the azimuth thruster with two degrees of freedom by computational fluid dynamics methods

Based on theoretical and practical studies into the causes of losses of propellers, caused by the axial inflows, employing the methods of computational fluid dynamics, we calculated the geometry of physical model of the thrusters with two degrees of freedom. We specified the required physical conditions of implementation, formalized geometric parameters of the model, assigned the initial and boundary conditions of differential equations that describe behavior of propeller flows in the recirculation zones. The coefficients are calculated that take into account the existence of degradation effects. The use of methods of computational fluid dynamics is necessary to account for the losses of propellers caused by the axial water inflows that are dependent on the degradation effects, which will contribute to reducing the propeller thrust and torque. As the result of the studies, we received the Reynolds and Froude numbers for the zero-velocity model of the ship: R n =4.405×106; F r =3.124. Components of the axial and tangential forces of the radial distribution of steering propellers thrusts are refined within the limits of 2.7–5.1 %. The largest deviation of similarity coefficients is in the region of 85–100 % of the rated propeller thrust. We obtained dependences of adjustment factors that affect the components of thrusts and torques proportional to the radius of propeller of the model and the actual steering propeller, related to the original geometry. The value of corrective factors depending on the propeller flow direction relative to the plane of motion of the ship is within the few hundredths of the percent. We systematized and compiled in the table the list of parameters (factors) according to the operating mode of the ship, which are required to solve the basic equations in the formalization of physical models of thrusters. The developed principles of formalization of the physical models of thrusters could be employed in the process of selection and improvement of design of combined propulsive complex and adjustment of selected regulators of components of the ship power plant.
Future Directions in H∞ Robust Control Theory

Abstract This paper presents a perspective on the H ∞ /conic-sector/ singular-value theory for robust multivariable control system analysis and design. The theory is critically evaluated in terms of its strengths and limitations in solving the robustness problems which historically motivated its development. The paper also discusses ongoing efforts to resolve the shortcomings of and expand the scope of applicability of the H ∞ theory, including reliable descriptor-systems algorithms for performing computations, the use of conformal mapping to reduce conservativeness, robust adaptive control, decentralized robust design and control, et cetera.
Big data security and privacy

Technological advances and novel applications, such as sensors, cyber-physical systems, smart mobile devices, cloud systems, data analytics, and social networks, are making possible to capture, and to quickly process and analyze huge amounts of data from which to extract information critical for security-related tasks. In the area of cyber security, such tasks include user authentication, access control, anomaly detection, user monitoring, and protection from insider threat. By analyzing and integrating data collected on the Internet and Web one can identify connections and relationships among individuals that may in turn help with homeland protection. By collecting and mining data concerning user travels and disease outbreaks one can predict disease spreading across geographical areas. And those are just a few examples; there are certainly many other domains where data technologies can play a major role in enhancing security. The use of data for security tasks is however raising major privacy concerns. Collected data, even if anonymized by removing identifiers such as names or social security numbers, when linked with other data may lead to re-identify the individuals to which specific data items are related to. Also, as organizations, such as governmental agencies, often need to collaborate on security tasks, data sets are exchanged across different organizations, resulting in these data sets being available to many different parties. Apart from the use of data for analytics, security tasks such as authentication and access control may require detailed information about users. An example is multi-factor authentication that may require, in addition to a password or a certificate, user biometrics. Recently proposed continuous authentication techniques extend access control system. This information if misused or stolen can lead to privacy breaches. It would then seem that in order to achieve security we must give up privacy. However this may not be necessarily the case. Recent advances in cryptography are making possible to work on encrypted data — for example for performing analytics on encrypted data. However much more needs to be done as the specific data privacy techniques to use heavily depend on the specific use of data and the security tasks at hand. Also current techniques are not still able to meet the efficiency requirement for use with big data sets. In this talk we will discuss methods and techniques to make this reconciliation possible and identify research directions.
Navigating the path to a biomedical science career

The number of biomedical PhD scientists undergoing training and graduating far exceeds the number of academic faculty positions and academic research jobs. This trend compels biomedical PhD scientists to increasingly seek career paths outside of academia. Prior studies have used quantitative methodology to determine trends and outcomes of single factors contributing to this shift, but there is a literature gap in studies considering multiple factors and in qualitative work focusing on biomedical PhD scientists’ experiences and their processes of career navigation. This paper draws on a social cognitive career theory (SCCT) framework and incorporates case study data from a southeastern Tier 1 research university to explore a nexus of factors influencing PhD scientists’ employment sector preferences and job search processes. It simultaneously concludes that relationships with faculty, particularly the mentor advisor, are essential to the opportunities available to these professionals and to the career paths they choose.
Migrating a Bare PC Web Server to a Multi-core Architecture.

Bare PC applications run without the support of any OS, kernel, or embedded software. Many bare PC applications such as Web servers, mail servers, SIP servers and VoIP clients have been developed previously for the x86 Intel architecture. We migrate a bare PC Web server application enabling it to run on a 64-bit multicore desktop processor. Migration poses many challenges as this application runs on a bare PC. The 64-bit CPU architecture is significantly different from its 32-bit counterpart, making migration non-trivial. First, an attempt was made to run the existing code as is on the 64-bit processor without using any 64-bit CPU architectural features. Second, paging required by the 64-bit architecture was implemented. This requires many design changes to deal with paging and virtual memory issues since the Web server application is based on real memory without any paging. Finally, multi-tasked execution of the Web server on multicore is undertaken. This phase of migration is complex due to the complexity in 64 bit architecture and its intricacies. We give technical details underlying the migration process and present results of testing functional operations with some preliminary data to validate this approach.
OKT3 Monoclonal Antibody in Pediatric Kidney Transplant Recipients With Recurrent and Resistant Allograft Rejection

Twelve pediatric patients, aged 28 months to 17 years, received OKT3 to reverse renal allograft rejection. In 11 patients, the rejection crisis was resistant to conventional antirejection therapy with high doses of prednisone or polyclonal antithymocyte globulin. Reversal of rejection was successful in 10 patients who completed a treatment course. Because of recurring resistant rejection, five patients received a second course of OKT3, which was successful in reversing the rejection crisis in two. Among these patients, the persistence or the appearance of high levels of circulating T3 lymphocytes after initiating the second treatment course correlated with treatment failure. The immediate side effects associated with OKT3 therapy were translent and medically manageable. We conclude that this monoclonal antibody preparation is a safe and effective treatment for pediatric renal allograft in recipients experiencing rejection crisis resistant to conventional therapy. However, the potential impact of this immunosuppressive medication on long-term renal allograft survival in this patient population remains to be determined.
Ultrasound and the Diagnosis of Renal and Ureteral Calculi

We retrospectively compared ultrasound examination with plain film radiography of the abdomen (KUB) in the diagnosis of renal and ureteral calcull in 13 patients. Overall, ultrasound was more sensitive than KUB (84% versus 54%) in detecting caicull. However, KUB was superior for the diagnosis of ureteral stones. No caicull were detected by intravenous urography that were not first seen on either ultrasound or KUB. Our experience suggests that the combination of ultrasound and KUB is less invasive and more sensitive than intravenous urography for the diagnosis of calcull in patients with symptoms and signs suggestive of stone disease or who are at high risk for stone formation.
Check Up Before You Check Out: Retail Clinics and Emergency Room Use

Abstract Given concern about inefficient use of the emergency room (ER) increasing health care costs, we use all ER visits in New Jersey from 2006 to 2014 to examine the impacts of retail clinics on ER use in a difference-in-difference framework. We find that among people residing close to an open retail clinic, the rate of ER use falls by 3.3–13.4% for preventable conditions and 5.7–12.0% for minor acute conditions, while a range of placebo conditions are not affected. Our estimates suggest annual cost savings of nearly $70 million from reduced ER use if retail clinics were readily available across New Jersey.
Algebraic Variety Models for High-Rank Matrix Completion

We consider a generalization of low-rank matrix completion to the case where the data belongs to an algebraic variety, i.e. each data point is a solution to a system of polynomial equations. In this case the original matrix is possibly high-rank, but it becomes low-rank after mapping each column to a higher dimensional space of monomial features. Many well-studied extensions of linear models, including affine subspaces and their union, can be described by a variety model. In addition, varieties can be used to model a richer class of nonlinear quadratic and higher degree curves and surfaces. We study the sampling requirements for matrix completion under a variety model with a focus on a union of affine subspaces. We also propose an efficient matrix completion algorithm that minimizes a convex or non-convex surrogate of the rank of the matrix of monomial features. Our algorithm uses the well-known "kernel trick" to avoid working directly with the high-dimensional monomial matrix. We show the proposed algorithm is able to recover synthetically generated data up to the predicted sampling complexity bounds. The proposed algorithm also outperforms standard low rank matrix completion and subspace clustering techniques in experiments with real data.
The Controlled Center Systems

In this correspondence, we propose a methodology to stabilize systems with control bifurcations by introducing ldquothe controlled center systems.rdquo A controlled center system is a reduced-order controlled dynamics consisting of the linearly uncontrollable dynamics with the first variable of the linearly controllable dynamics as input. The controller of the full order system is then constructed. We apply this methodology to systems with a transcontrollable, a Hopf, and a double-zero, control bifurcation.
Are Law Degrees as Valuable to Minorities

Abstract We estimate the increase in earnings from a law degree relative to a bachelor’s degree for graduates of different race/ethnic groups. Law earnings premiums are higher for whites than for minorities (excluding individuals raised outside the U.S.). The median annual law earnings premium is approximately $41,000 for whites, $34,000 for Asians, $33,000 for blacks, and $28,000 for Hispanics. Law earnings premiums for whites, blacks and Hispanics have trended upward and appear to be gradually converging. Approximately 90% of law graduates are white compared to approximately 82% of bachelor’s degree holders.
From Guayaquil to Quito: Three Nineteenth-Century Travel Narratives

Countless nineteenth-century international travelers climbed the hazardous Inca trail that led from the coastal city of Guayaquil up into the Andean highlands and then on to Ecuador’s capital city of Quito. Scientific exploration, mountain climbing, cultural and economic expansion, diplomacy, and evangelism were but a few of their callings. From tropical jungles to the magnificent “Monarch of the Andes,” Mount Chimborazo, the terrain they crossed was an ultimate challenge to their physical and mental fortitude. At the same time, it afforded them contact with unparalleled human and natural diversity.
Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning

Embedded, continual learning for autonomous and adaptive behavior is a key application of neuromorphic hardware. However, neuromorphic implementations of embedded learning at large scales that are both flexible and efficient have been hindered by a lack of a suitable algorithmic framework. As a result, most neuromorphic hardware are trained off-line on large clusters of dedicated processors or GPUs and transferred post hoc to the device. We address this by introducing the neural and synaptic array transceiver (NSAT), a neuromorphic computational framework facilitating flexible and efficient embedded learning by matching algorithmic requirements and neural and synaptic dynamics. NSAT supports event-driven supervised, unsupervised and reinforcement learning algorithms including deep learning. We demonstrate the NSAT in a wide range of tasks, including the simulation of Mihalas-Niebur neuron, dynamic neural fields, event-driven random back-propagation for event-based deep learning, event-based contrastive divergence for unsupervised learning, and voltage-based learning rules for sequence learning. We anticipate that this contribution will establish the foundation for a new generation of devices enabling adaptive mobile systems, wearable devices, and robots with data-driven autonomy.
Photonic-crystal exciton-polaritons in monolayer semiconductors

Semiconductor microcavity polaritons, formed via strong exciton-photon coupling, provide a quantum many-body system on a chip, featuring rich physics phenomena for better photonic technology. However, conventional polariton cavities are bulky, difficult to integrate, and inflexible for mode control, especially for room-temperature materials. Here we demonstrate sub-wavelength-thick, one-dimensional photonic crystals as a designable, compact, and practical platform for strong coupling with atomically thin van der Waals crystals. Polariton dispersions and mode anti-crossings are measured up to room temperature. Non-radiative decay to dark excitons is suppressed due to polariton enhancement of the radiative decay. Unusual features, including highly anisotropic dispersions and adjustable Fano resonances in reflectance, may facilitate high temperature polariton condensation in variable dimensions. Combining slab photonic crystals and van der Waals crystals in the strong coupling regime allows unprecedented engineering flexibility for exploring novel polariton phenomena and device concepts.
LOTS about attacking deep features

Deep neural networks provide state-of-the-art performance on various tasks and are, therefore, widely used in real world applications. DNNs are becoming frequently utilized in biometrics for extracting deep features, which can be used in recognition systems for enrolling and recognizing new individuals. It was revealed that deep neural networks suffer from a fundamental problem, namely, they can unexpectedly misclassify examples formed by slightly perturbing correctly recognized inputs. Various approaches have been developed for generating these so-called adversarial examples, but they aim at attacking end-to-end networks. For biometrics, it is natural to ask whether systems using deep features are immune to or, at least, more resilient to attacks than end-to-end networks. In this paper, we introduce a general technique called the layerwise origin-target synthesis (LOTS) that can be efficiently used to form adversarial examples that mimic the deep features of the target. We analyze and compare the adversarial robustness of the end-to-end VGG Face network with systems that use Euclidean or cosine distance between gallery templates and extracted deep features. We demonstrate that iterative LOTS is very effective and show that systems utilizing deep features are easier to attack than the end-to-end network.
Uniform Pricing in US Retail Chains

We show that most U.S. food, drugstore, and mass-merchandise chains charge nearly uniform prices across stores, despite wide variation in consumer demographics and competition. Demand estimates reveal substantial within-chain variation in price elasticities and suggest that the median chain sacrifices ${\$}$16 million of annual profit relative to a benchmark of optimal prices. In contrast, differences in average prices between chains are broadly consistent with the optimal benchmark. We discuss a range of explanations for nearly uniform pricing, highlighting managerial inertia and brand image concerns as mechanisms frequently mentioned by industry participants. Relative to our optimal benchmark, uniform pricing may significantly increase the prices paid by poorer households relative to the rich, dampen the response of prices to local economic shocks, alter the analysis of mergers in antitrust, and shift the incidence of intranational trade costs.
Grain growth and second-phase precipitation in nanocrystalline aluminum-manganese electrodeposits

The structural stability of nanocrystalline aluminum–manganese (Al-6.5 at.% Mn) alloys is studied in the temperature range of 200–400 °C. Transmission electron microscopy shows that grain growth in this alloy is subdued by the presence of Mn, such that 100 nm or finer grain sizes can be retained at 200 and 300 °C even after 1 month of annealing. In contrast, the principal mode of instability in the alloy is the precipitation of the equilibrium Al6Mn phase, which was observed to form at much shorter timescales and is present at 300 and 400 °C after just 30 min. Differential scanning calorimetry was used to study the kinetics of the Al6Mn reaction using Johnson–Mehl–Avrami–Kolmogorov analysis and construct a time–temperature–transformation (TTT) diagram for this process. It is found that this Al–Mn single-phase nanostructured alloy can be stable against forming the Al6Mn phase and against grain growth for several months below 200 °C and for short thermal excursions up to 300 °C.
Carbon taxes and climate commitment with non-constant time preference

We study the Markov perfect equilibrium in a dynamic game where agents have non-constant time preference, decentralized households determine aggregate savings, and a planner chooses climate policy. The article is the first to solve this problem with general discounting and general functional forms. With time-inconsistent preferences, a commitment device that allows a planner to choose climate policy for multiple periods is potentially very valuable. Nevertheless, our quantitative results show that while a permanent commitment device would be very valuable, the ability to commit policy for “only” 100 years adds less than 2% to the value of climate policy without commitment. We solve a log-linear version of the model analytically, generating a formula for the optimal carbon tax that includes the formula in Golosov et al. (2014, Econometrica, 82, 41–88) as a special case. More importantly, we develop new algorithms to solve the general game numerically. Convex damages lead to strategic interactions across generations of planners that lower the optimal carbon tax by 45% relative to the scenario without strategic interactions.
The H-scan format for classification of ultrasound scattering

Traditional B-Scan images show the envelope of received echoes as a grey scale image. The echoes are produced from specular reflections and scattering sites where changes in acoustic impedance occur (Cobbold, Foundations of Biomedical Ultrasound, Oxford Press, 2007). A long-standing area of interest concerns the frequency dependence of scatterers within different tissues, organs, and the blood.
Social Connections Within Executive Teams and Management Forecasts

We examine the role of teamwork within the top executive teams in generating management forecasts. Using social connections within the executive team to capture the team’s interaction, cooperation, and teamwork, we find that social connections among team members are associated with higher management forecast accuracy, consistent with economic theories that information is dispersed within a firm and with sociology insights that social connections facilitate information sharing. Further analyses show that the association between social connections and forecast accuracy is stronger when the teams are just beginning to work together, when their firms face more uncertainty or adversity, and when the CEOs are less powerful. Our results hold for a subsample of executive teams that experience pseudo exogenous shocks to their social connectedness. Taken together, our results underscore the importance of teamwork among executives in the forecast generation process. This paper was accepted by Suraj Srinivasan, accou...
Social Policy Expenditures and Life Expectancy in High-Income Countries

Introduction The U.S. spends more than any other country on health care, yet Americans have lower life expectancy than people in most industrialized countries. Recent studies suggest that lower expenditures on social policies in the U.S. may contribute to less-favorable trends in life expectancy. This study tests the hypothesis that greater social spending will be positively associated with life expectancy across the countries of the Organisation of Economic Co-operation and Development and that the magnitude of these associations will outweigh those between government healthcare spending and life expectancy. Methods In 2016, longitudinal data on six domains of social expenditures for the U.S. and 19 other wealthy nations between 1980 and 2010 were used to estimate the associations between prior year expenditures on education, family, unemployment, incapacity, old age, and active labor market programs, and period life expectancy using fixed effects models. Results Controlling for a wide set of confounders and government healthcare expenditures, a 1% increase in prior year education expenditures was associated with 0.160 (95% CI=0.033, 0.286) of a year gain in life expectancy, whereas a 1% increase in prior year incapacity benefit expenditures was associated with 0.168 (95% CI=0.003, 0.333) of a year gain in life expectancy. Counterfactual models suggest that if the U.S. were to increase expenditures on education and incapacity to the levels of the country with the maximum expenditures, life expectancy would increase to 80.12 years. Conclusions The U.S. life expectancy lag could be considerably smaller if U.S. expenditures on education and incapacity programs were comparable with those in other high-income countries.
Maintaining a Competent Public Health Workforce: Lessons Learned From Experiences With Public Health Accreditation Domain 8 Standards and Measures.

CONTEXT Public health accreditation is an ongoing national movement to improve the quality of public health departments and the public health system in the United States; however, calls have been made for more evidence regarding best practices in the accreditation process. OBJECTIVE The purpose of this work is to provide evidence about best practices in the accreditation process, specifically within the workforce development domain. It is the first in-depth investigation into workforce development using data collected by Public Health Accreditation Board (PHAB). DESIGN Using deidentified accreditation application data from PHAB, this study employs a mixed-methods approach to examining practices, lessons learned, challenges, and strategies pertaining to workforce development planning for Domain 8. SETTING United States. PARTICIPANTS US state (n = 19) and local health departments (n = 115). MAIN OUTCOME MEASURES Public Health Accreditation Board assessment scores for the workforce measures and the relationship between the health department's approach to meeting a PHAB measure criteria and the PHAB assessment score. RESULTS Of the 9 different approaches identified as ways of encouraging the development of a sufficient number of qualified public health workers (version 1, measure 8.1.1), only 1 approach (local health department internship programs with schools of public health; B = 0.25, P < .03) was significantly related to higher scores. An opportunity for improvement identified for measure 8.2.1 was that plans missing a clear identification of the gap between current staff competencies and staff needs were associated with a 0.88-point decrease in the 4-point score (P < .001). CONCLUSIONS Findings suggest that there are approaches adopted for meeting PHAB domain 8 measures that will impact the overall conformance assessment and score of a health department pursuing accreditation. There are several opportunities for improvement that health departments might consider when planning for accreditation or assessing their activities.
Pyk2 deficiency potentiates osteoblast differentiation and mineralizing activity in response to estrogen or raloxifene

Abstract Bone remodeling is controlled by the actions of bone-degrading osteoclasts and bone-forming osteoblasts (OBs). Aging and loss of estrogen after menopause affects bone mass and quality. Estrogen therapy, including selective estrogen receptor modulators (SERMs), can prevent bone loss and increase bone mineral density in post-menopausal women. Although investigations of the effects of estrogen on osteoclast activity are well advanced, the mechanism of action of estrogen on OBs is still unclear. The proline-rich tyrosine kinase 2 (Pyk2) is important for bone formation and female mice lacking Pyk2 (Pyk2-KO) exhibit elevated bone mass, increased bone formation rate and reduced osteoclast activity. Therefore, in the current study, we examined the role of estrogen signaling on the mechanism of action of Pyk2 in OBs. As expected, Pyk2-KO OBs showed significantly higher proliferation, matrix formation, and mineralization than WT OBs. In addition we found that Pyk2-KO OBs cultured in the presence of either 17β-estradiol (E2) or raloxifene, a SERM used for the treatment of post-menopausal osteoporosis, showed a further robust increase in alkaline phosphatase (ALP) activity and mineralization. We examined the possible mechanism of action and found that Pyk2 deletion promotes the proteasome-mediated degradation of estrogen receptor α (ERα), but not estrogen receptor β (ERβ). As a consequence, E2 signaling via ERβ was enhanced in Pyk2-KO OBs. In addition, we found that Pyk2 deletion and E2 stimulation had an additive effect on ERK phosphorylation, which is known to stimulate cell differentiation and survival. Our findings suggest that in the absence of Pyk2, estrogen exerts an osteogenic effect on OBs through altered ERα and ERβ signaling. Thus, targeting Pyk2, in combination with estrogen or raloxifene, may be a novel strategy for the prevention and/or treatment of bone loss diseases.
Online Power Control for Block i.i.d. Energy Harvesting Channels

We study the problem of online power control for energy harvesting communication nodes with random energy arrivals and a finite battery. We assume a block i.i.d. stochastic model for the energy arrivals, in which the energy arrivals are constant for a fixed duration ${T}$ , but are independent across different blocks, drawn from an arbitrary distribution. This model serves as a simple approximation to a random process with coherence time ${T}$ . We propose a simple online power control policy, and prove that its performance gap to the optimal throughput is bounded by a constant which is independent of the parameters of the problem. This also yields a simple formula for the approximately optimal long-term average throughput, which sheds some light on the qualitative behavior of the throughput and how it depends on the coherence time of the energy arrival process. Our results show that, perhaps counter-intuitively, for a fixed mean energy arrival rate the approximate throughput decreases with increasing coherence time ${T}$ of the energy arrival process. In particular, the battery size needed to approach the AWGN capacity of the channel increases linearly with the coherence time of the process. Finally, we show that our results can provide an approximation to the information-theoretic capacity of the same channel.
When does abstraction occur in semantic memory: insights from distributional models

ABSTRACTAbstraction is a core principle of Distributional Semantic Models (DSMs) that learn semantic representations for words by applying dimensional reduction to statistical redundancies in langu...
Associations of metabolic syndrome and C‐reactive protein with mortality from total cancer, obesity‐linked cancers and breast cancer among women in NHANES III

Although metabolic syndrome (MetS) is a prognostic factor for cancer occurrence, the association of MetS and cancer mortality remains unclear. The purpose of this study was to evaluate whether MetS, components of MetS and C-reactive protein (CRP) are associated with cancer mortality in women. A total of 400 cancer deaths, with 140 deaths from obesity-linked-cancers (OLCas), [breast (BCa), colorectal, pancreatic and endometrial], linked through the National Death Index, were identified from 10,104 eligible subjects aged ≥18 years. Cox proportional hazards regression was used to estimate multivariable-adjusted hazard ratios (HR) for cancer mortality. MetS was associated with increased deaths for total-cancer [HR=1.33, 95% confidence interval (CI) 1.04-1.70] and BCa [HR=2.1, 95% CI, 1.09-4.11]. The risk of total-cancer [HR=1.7, 95% CI, 1.12-2.68], OLCas [HR=2.1, 95% CI, 1.00-4.37] and BCa [HR=3.8, 95% CI, 1.34-10.91] mortality was highest for women with all MetS components abnormal, compared to those without MetS. Linear associations of blood-pressure [HR=2.5, 1.02-6.12, Quartile (Q) 4 vs Q1, p-trend=0.004] and blood-glucose [HR=2.2, 1.04-4.60, Q4 vs Q1, p-trend=0.04] with total-OLCas mortality were observed. A three-fold increased risk of BCa mortality was observed for women with enlarged waist circumference, ≥100.9cm, [HR=3.5, 1.14-10.51, p-trend=0.008] and in those with increased blood glucose, ≥101mg/dL, [HR=3.2, 1.11-9.20, p-trend=0.03] compared to those in Q1. None of the components of MetS were associated with total-cancer mortality. CRP was not associated with cancer mortality. In conclusion, MetS is associated with total-cancer and breast-cancer mortality, with waist circumference, blood pressure and blood glucose as independent predictors of OLCas and BCa mortality. This article is protected by copyright. All rights reserved.
Exploring the rise of mortgage borrowing among older Americans

Abstract Between 1980 and 2015, older households in the US more than tripled the use of home mortgage debt. Rather than using owned homes as a source of imputed rent, older households are borrowing against home equity, with loan terms that exceed their expected life spans. Using several data sources, we explore the rising use of mortgages among elderly homeowners. Rising mortgage borrowing provides low-wealth older households with increased liquid assets, but it does not appear to be meaningfully associated with increases in loan defaults. This trend of elderly mortgage borrowing is not explained by increasing levels of income or cohort demographic shifts, but is linked to a rise on ownership of homes by older households in general. However, changes in subsidies associated with mortgage debt partially contribute to differential increases in mortgage use by older households.
Applied machine learning to predict stress hotspots I: Face centered cubic materials

Abstract We investigate the formation of stress hotspots in polycrystalline materials under uniaxial tensile deformation by integrating full field crystal plasticity based deformation models and machine learning techniques to gain data driven insights about microstructural properties. Synthetic 3D microstructures are created representing single phase equiaxed microstructures for generic copper alloys. Uniaxial tensile deformation is simulated using a 3-D full-field, image-based Fast Fourier Transform (FFT) technique with rate-sensitive crystal plasticity, to get local micro-mechanical fields (stress and strain rates). Stress hotspots are defined as the grains having stress values above the 90th percentile of the stress distribution. Hotspot neighborhoods are then characterized using metrics that reflect local crystallography, geometry, and connectivity. This data is used to create input feature vectors to train a random forest learning algorithm, which predicts the grains that will become stress hotspots. We are able to achieve an area under the receiving operating characteristic curve (ROC-AUC) of 0.74 for face centered cubic materials modeled on generic copper alloys. The results show the power and the limitations of the machine learning approach applied to the polycrystalline grain networks.
Stopping rules for majority voting: A public choice experiment

Abstract Some solution concepts make the same equilibrium prediction regardless of how voting ends. As a result, experimentalists have used a variety of stopping rules without carefully considering the consequences. This experiment compares majority decision making in committees using one of three stopping rules: vote by a majority to adjourn, a fixed time period, and the chair decides when to adjourn. We compare these rules for groups of five subjects using two distributions of ideal points studied by Fiorina and Plott (1978). Although we find few differences between voting to adjourn and ending after a fixed time period, we find noticeable differences between groups with the chair decides to adjourn and those without. Allowing the chair to determine adjournment produces outcomes more favorable to the chair and can make the voting process continue for more than three times as many rounds as the other two treatments. Such results should help committees improve the rules governing their decisions.
Testing hypotheses under covariate-adaptive randomisation and additive models

Covariate-adaptive randomisation has a long history of applications in clinical trials. Shao, Yu, and Zhong [(2010). A theory for testing hypotheses under covariate-adaptive randomization. Biometri...
Trapdoor Functions from the Computational Diffie-Hellman Assumption

Trapdoor functions (TDFs) are a fundamental primitive in cryptography. Yet, the current set of assumptions known to imply TDFs is surprisingly limited, when compared to public-key encryption. We present a new general approach for constructing TDFs. Specifically, we give a generic construction of TDFs from any Chameleon Encryption (Dottling and Garg [CRYPTO’17]) satisfying a novel property which we call recyclability. By showing how to adapt current Computational Diffie-Hellman (CDH) based constructions of chameleon encryption to yield recyclability, we obtain the first construction of TDFs with security proved under the CDH assumption. While TDFs from the Decisional Diffie-Hellman (DDH) assumption were previously known, the possibility of basing them on CDH had remained open for more than 30 years.
Unleashing Linear Optimizers for Group-Fair Learning and Optimization.

Most systems and learning algorithms optimize average performance or average loss–one reason being computational complexity. However, many objectives of practical interest are more complex than simply average loss. This arises, for example, when balancing performance or loss with fairness across people. We prove that, from a computational perspective, optimizing arbitrary objectives that take into account performance over a small number of groups is not significantly harder to optimize than average performance. Our main result is a polynomial-time reduction that uses a linear optimizer to optimize an arbitrary (Lipschitz continuous) function of performance over a (constant) number of possibly-overlapping groups. This includes fairness objectives over small numbers of groups, and we further point out that other existing notions of fairness such as individual fairness can be cast as convex optimization and hence more standard convex techniques can be used. Beyond learning, our approach applies to multi-objective optimization, more generally.
Pendulum-Type Hetero-Core Fiber Optic Accelerometer for Low-Frequency Vibration Monitoring.

In this paper, a novel pendulum-type accelerometer based on hetero-core fiber optics has been proposed for structural health monitoring targeting large-scale civil infrastructures. Vibration measurement is a non-destructive method for diagnosing the failure of structures by assessing natural frequencies and other vibration patterns. The hetero-core fiber optic sensor utilized in the proposed accelerometer can serve as a displacement sensor with robustness to temperature changes, in addition to immunity to electromagnetic interference and chemical corrosions. Thus, the hetero-core sensor inside the accelerometer measures applied acceleration by detecting the rotation of an internal pendulum. A series of experiments showed that the hetero-core fiber sensor linearly responded to the rotation angle of the pendulum ranging within (−6°, 4°), and furthermore the proposed accelerometer could reproduce the waveform of input vibration in a frequency band of several Hz order.
Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation

Instance segmentation in 3D images is a fundamental task in biomedical image analysis. While deep learning models often work well for 2D instance segmentation, 3D instance segmentation still faces critical challenges, such as insufficient training data due to various annotation difficulties in 3D biomedical images. Common 3D annotation methods (e.g., full voxel annotation) incur high workloads and costs for labeling enough instances for training deep learning 3D instance segmentation models. In this paper, we propose a new weak annotation approach for training a fast deep learning 3D instance segmentation model without using full voxel mask annotation. Our approach needs only 3D bounding boxes for all instances and full voxel annotation for a small fraction of the instances, and uses a novel two-stage 3D instance segmentation model utilizing these two kinds of annotation, respectively. We evaluate our approach on several biomedical image datasets, and the experimental results show that (1) with full annotated boxes and a small amount of masks, our approach can achieve similar performance as the best known methods using full annotation, and (2) with similar annotation time, our approach outperforms the best known methods that use full annotation.
CLINICAL IMPACT OF DIGITAL CHOLANGIOSCOPY IN MANAGEMENT OF INDETERMINATE BILIARY STRICTURES AND COMPLEX BILIARY STONES: A SINGLE CENTER STUDY

Aims:Endoscopic management of indeterminate strictures and complex stones remains a challenge, for which the latest generation single-operator digital cholangioscope (SpyGlass DS) has shown promisi...
Localized attentional interference reflects competition for reentrant processing

Visual performance is compromised when attention is divided between objects that are near one another in the visual field. It has been postulated that this effect, termed localized attentional interference (LAI), reflects competition between visual-object representations for the control of cortical neural responses. To determine whether LAI arises during feedforward processing or during reentrant processing, the present study examined the influence of poststimulus pattern and four-dot masks on the strength of the effect. Experiment 1 found that pattern masks, which are believed to compromise feedforward processing, do not produce stronger LAI than do four-dot masks, which are believed to leave feedforward processing undisrupted. Experiment 2 found that LAI is weaker when reentrant processing is interrupted shortly after initiation than it is when reentrant processing is allowed to run to completion. The results suggest that LAI emerges from competition between objects during reentrant processing.
Vouchers can create a thriving market for distributed power generation in developing countries

Abstract I propose that vouchers offer a promising approach to making distributed power generation, such as solar home systems, affordable to consumers and profitable for producers and distributors. In a voucher-based system, governments give vouchers to eligible beneficiaries, who then use the vouchers to purchase qualifying products and services. This system enables consumer choice, helps the poor with the affordability of distributed energy products, and injects money into the market for relevant products and services. I discuss practical implementation challenges and argue that digitalization allows governments to significantly reduce corruption and red tape, making vouchers a realistic energy access policy for many governments all over the world.
Network-level allosteric effects are elucidated by detailing how ligand-binding events modulate utilization of catalytic potentials.

Allosteric regulation has traditionally been described by mathematically-complex allosteric rate laws in the form of ratios of polynomials derived from the application of simplifying kinetic assumptions. Alternatively, an approach that explicitly describes all known ligand-binding events requires no simplifying assumptions while allowing for the computation of enzymatic states. Here, we employ such a modeling approach to examine the “catalytic potential” of an enzyme—an enzyme’s capacity to catalyze a biochemical reaction. The catalytic potential is the fundamental result of multiple ligand-binding events that represents a “tug of war” among the various regulators and substrates within the network. This formalism allows for the assessment of interacting allosteric enzymes and development of a network-level understanding of regulation. We first define the catalytic potential and use it to characterize the response of three key kinases (hexokinase, phosphofructokinase, and pyruvate kinase) in human red blood cell glycolysis to perturbations in ATP utilization. Next, we examine the sensitivity of the catalytic potential by using existing personalized models, finding that the catalytic potential allows for the identification of subtle but important differences in how individuals respond to such perturbations. Finally, we explore how the catalytic potential can help to elucidate how enzymes work in tandem to maintain a homeostatic state. Taken together, this work provides an interpretation and visualization of the dynamic interactions and network-level effects of interacting allosteric enzymes.
Impact of the Self-Determined Learning Model of Instruction on Self-Determination and Goal Attainment in Adolescents With Intellectual Disability:

The Self-Determined Learning Model of Instruction (SDLMI) is an evidence-based practice designed to enable teachers to teach students to self-regulate problem solving to set and attain educationall...
Beyond Policy Diffusion: Spatial Econometric Models of Public Administration

Interdependence in the decision making or behaviors of various organizations and administrators is often neglected in the study of public administration. Failing to account for such interdependence risks an incomplete understanding of the choices made by these actors and agencies. As such, we show how researchers analyzing cross-sectional or time-series-cross-sectional (TSCS) data can utilize spatial econometric methods to improve inference on existing questions, and, more interestingly, engage a new set of theoretical questions. Specifically, we articulate several general mechanisms for spatial dependence that are likely to appear in research on public administration (isomorphism, competition, benchmarking, and common exposure). We then demonstrate how these mechanisms can be tested using spatial econometric models in two applications: first, a cross-sectional study of district-level bilingual education spending and, second, a TSCS analysis on state-level health care administration. In our presentation, we also briefly discuss many of the practical challenges confronted in estimating spatial models (e.g., weights specification, model selection, effects calculation) and offer some guidance on each.