cssi/SciSciGPT-SciSciNet huggingface dataset:
HEMODYNAMICS CHARACTERISTICS OF A FOUR-WAY RIGHT-ATRIUM BYPASS CONNECTOR

Currently, the surgical procedure followed by the majority of cardiac surgeons to address right ventricular dysfunction is the Fontan procedure, which connects the superior and inferior vena cava directly to the left and right pulmonary arteries bypassing the right atrium. However, this is not the most efficient configuration from a hemodynamics perspective. The goal of this study is to develop a patient-specific 4-way connector to bypass the dysfunctional right ventricle and augment the pulmonary circulation. The 4-way connector is intended to channel the blood flow from the inferior and superior vena cava directly to the right and left pulmonary arteries. By creating a connector with proper hemodynamic characteristics, one can control the jet flow interactions between the inferior and superior vena cava and streamline the flow towards the right and left pulmonary arteries. In this study the focus is on creating a system that can identify the optimal configuration for the 4-way connector for patients from 0–20 years of age. A platform is created in ANSYS that utilizes the DOE function to minimize power-loss and blood damage propensity in the connector based on junction geometries. A CFD model is created to simulate the blood flow through the connector. Then the geometry of the bypass connector is parameterized for DOE process. The selected design parameters include inlet and outlet diameters, radius at the intersection, and length of the connector pathways. The chosen range for each geometric parameter is based on the relative size of the patient’s arteries found in the literature. It was confirmed that as the patient’s age and artery size change, the optimal size and shape of the connector also changes. However, the corner radius did not decrease at the same rate as the opening diameters. This means that creating different sized connectors is not just a matter of scaling the original connector to match the desired opening diameter. However, it was found that power losses within the connector decrease and average and maximum blood traversal time through the connector increased for increasing opening radius. This information could be used to create a more specific relationship between the opening radius and the flow characteristics. So in order to create patient specific connectors, either a new more complicated trend needs to be found or an optimization program would need to be run on each patient’s specific geometry when they need a new connector.Copyright © 2017 by ASME
The Impact of High School Curriculum on Confidence, Academic Success, and Mental and Physical Well-Being of University Students

This paper investigates the causal effect of high school curriculum on various student outcomes including academic performance at university, happiness, physical and mental health, self-confidence, confidence in academic ability, and attitudes towards studying and learning. We exploit a curriculum reform in China, the implementation of which started in 2004, but rolled out in different years in different provinces. The new curriculum pivoted away from the old lock-step course structure where all students had to take the same courses and only those subjects that were covered in the national university entrance exam were considered important. In contrast, the new curriculum introduced a course credit system, changed textbooks, and provided flexibility in course selection. It also introduced elective courses and made such courses as arts and physical education mandatory, and a graduation requirement. Using survey data on university students and employing a difference-in-difference approach, we find that the students who were exposed to the new curriculum in high school have better academic performance in university. They are happier, and their physical and mental well-being is better. These students are more likely to have positive attitudes towards themselves and they are more involved in student clubs. They have more confidence in their academic ability, they have more positive attitudes towards studying, and they have more general self-confidence. These results indicate that the reform had a significant impact on students’ academic success and well-being, arguably by allowing them to focus on subject matters in which they are interested, and by reducing undue stress of a regimented curriculum.
The Effect of Screen Size and E-Communication Richness on Negotiation Performance

Using an empirical study, this paper investigated how each screen size and different presentation modes (video or text-only) can trigger meaningful differences when interacting with a partner in a negotiation. In a simulated multi-issue negotiation between a buyer and a seller, participants were instructed to communicate through either a large (laptop) or small (mobile phone) screen in either a video conversation or a text-based communication. The findings revealed that (a) negotiators communicating through a large screen performed better than negotiators interacting via small screen; (b) negotiators communicating through video conversation performed better than negotiators interacting via text-based communication; (c) negotiators communicating through video conversation formed higher levels of trust and satisfaction than negotiators interacting via text-based communication; and (d) negotiators communicating through video conversations over large screens achieved the highest joint outcome. Implications for the use of technology during negotiations is discussed, with attention given to the need to preserve more naturalistic cues through larger screens and the use of video conversations for best effect.
The Effects of Birth Year, Age and Sex on Hemagglutination Inhibition Antibody Responses to Influenza Vaccination

The first exposure to influenza is thought to impact subsequent immune responses later in life. The consequences of this can be seen during influenza epidemics and pandemics with differences in morbidity and mortality for different birth cohorts. There is a need for better understanding of how vaccine responses are affected by early exposures to influenza viruses. In this analysis of hemagglutination inhibition (HI) antibody responses in two cohorts of military personnel we noticed differences related to age, sex, prior vaccination, deployment and birth year. These data suggest that HI antibody production, in response to influenza vaccination, is affected by these factors. The magnitude of this antibody response is associated with, among other factors, the influenza strain that circulated following birth.
In memoriam: a tribute to Bernice R. Moss.

(1979). In Memoriam. Journal of Physical Education and Recreation: Vol. 50, Including Leisure Today, pp. 17-17.
Toeplitz Inverse Covariance-based Clustering of Multivariate Time Series Data.

Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios.
Quantifying the agreement between observed and simulated extratropical modes of interannual variability

Using historical simulations of the Coupled Model Intercomparison Project-5 (CMIP5) and multiple observationally-based datasets, we employ skill metrics to analyze the fidelity of the simulated Northern Annular Mode, the North Atlantic Oscillation, the Pacific North America pattern, the Southern Annular Mode, the Pacific Decadal Oscillation, the North Pacific Oscillation, and the North Pacific Gyre Oscillation. We assess the benefits of a unified approach to evaluate these modes of variability, which we call the common basis function (CBF) approach, based on projecting model anomalies onto observed empirical orthogonal functions (EOFs). The CBF approach circumvents issues with conventional EOF analysis, eliminating, for example, corrections of arbitrarily assigned, but inconsistent, signs of the EOF’s/PC’s being compared. It also avoids the problem that sometimes the first observed EOF is more similar to a higher order model EOF, particularly if the simulated EOFs are not well separated. Compared to conventional EOF analysis of models, the CBF approach indicates that models compare significantly better with observations in terms of pattern correlation and root-mean-squared-error (RMSE) than heretofore suggested. In many cases, models are doing a credible job at capturing the observationally-based estimates of patterns; however, errors in simulated amplitudes can be large and more egregious than pattern errors. In the context of the broad distribution of errors in the CMIP5 ensemble, sensitivity tests demonstrate that our results are relatively insensitive to methodological considerations (CBF vs. conventional approach), observational uncertainties in pattern (as determined by using multiple datasets), and internal variability (when multiple realizations from the same model are compared). The skill metrics proposed in this study can provide a useful summary of the ability of models to reproduce the observed EOF patterns and amplitudes. Additionally, the skill metrics can be used as a tool to objectively highlight where potential model improvements might be made. We advocate more systematic and objective testing of simulated extratropical variability, especially during the non-dominant seasons of each mode, when many models are performing relatively poorly.
Convolutions on the sphere: commutation with differential operators

We generalize the definition of convolution of vectors and tensors on the 2-sphere, and prove that it commutes with differential operators. Moreover, vectors and tensors that are normal/tangent to the spherical surface remain so after the convolution. These properties make the new filtering operation particularly useful to analyzing and modeling nonlinear dynamics in spherical systems, such as in geophysics, astrophysics, and in inertial confinement fusion applications. An essential tool we use is the theory of scalar, vector, and tensor spherical harmonics. We then show that our generalized filtering operation is equivalent to the (traditional) convolution of scalar fields of the Helmholtz decomposition of vectors and tensors.
Representing Social Media Users for Sarcasm Detection

We explore two methods for representing authors in the context of textual sarcasm detection: a Bayesian approach that directly represents authors’ propensities to be sarcastic, and a dense embedding approach that can learn interactions between the author and the text. Using the SARC dataset of Reddit comments, we show that augmenting a bidirectional RNN with these representations improves performance; the Bayesian approach suffices in homogeneous contexts, whereas the added power of the dense embeddings proves valuable in more diverse ones.
Adversarial Over-Sensitivity and Over-Stability Strategies for Dialogue Models.

We present two categories of model-agnostic adversarial strategies that reveal the weaknesses of several generative, task-oriented dialogue models: Should-Not-Change strategies that evaluate over-sensitivity to small and semantics-preserving edits, as well as Should-Change strategies that test if a model is over-stable against subtle yet semantics-changing modifications. We next perform adversarial training with each strategy, employing a max-margin approach for negative generative examples. This not only makes the target dialogue model more robust to the adversarial inputs, but also helps it perform significantly better on the original inputs. Moreover, training on all strategies combined achieves further improvements, achieving a new state-of-the-art performance on the original task (also verified via human evaluation). In addition to adversarial training, we also address the robustness task at the model-level, by feeding it subword units as both inputs and outputs, and show that the resulting model is equally competitive, requires only 1/4 of the original vocabulary size, and is robust to one of the adversarial strategies (to which the original model is vulnerable) even without adversarial training.
Power Laws in Economics and Finance

A power law (PL) is the form taken by a large number of surprising empirical regularities in economics and finance. This review surveys well-documented empirical PLs regarding income and wealth, the size of cities and firms, stock market returns, trading volume, international trade, and executive pay. It reviews detailindependent theoretical motivations that make sharp predictions concerning the existence and coefficients of PLs, without requiring delicate tuning of model parameters. These theoretical mechanisms include random growth, optimization, and the economics of superstars, coupled with extreme value theory. Some empirical regularities currently lack an appropriate explanation. This article highlights these open areas for future research.
Price and Size Discovery in Financial Markets: Evidence from the U.S. Treasury Securities Market

We study the workup protocol, an important size discovery mechanism in the U.S. Treasury market. We find that workup order flow shocks explain 6%–8% of the variation of returns on benchmark notes and, across maturities, 10% of the variation of the yield curve level factor. Information related to proprietary client order flow is more likely to show up in workup trades, whereas information derived from public announcements tends to come through preworkup trades. Our findings highlight how the nature of information affects the trade-off between speed and execution price when informed traders choose between the lit and workup channels.Received May 3, 2017; Editorial decision August 1, 2018 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online. Internet Appendix tables are numbered with “IA” prefix.
Leaf stable carbon isotope composition reflects transpiration efficiency in Zea mays

The increasing demand for food production and predicted climate change scenarios highlight the need for improvements in crop sustainability. The efficient use of water will become increasingly important for rain-fed agricultural crops even in fertile regions that have historically received ample precipitation. Improvements in water-use efficiency in Zea mays have been limited, and warrant a renewed effort aided by molecular breeding approaches. Progress has been constrained by the difficulty of measuring water-use in a field environment. The stable carbon isotope composition (δ13 C) of the leaf has been proposed as an integrated signature of carbon fixation with a link to stomatal conductance. However, additional factors affecting leaf δ13 C exist, and a limited number of studies have explored this trait in Z. mays. Here we present an extensive characterization of leaf δ13 C in Z. mays. Significant variation in leaf δ13 C exists across diverse lines of Z. mays, which we show to be heritable across several environments. Furthermore, we examine temporal and spatial variation in leaf δ13 C to determine the optimum sampling time to maximize the use of leaf δ13 C as a trait. Finally, our results demonstrate the relationship between transpiration and leaf δ13 C in the field and the greenhouse. Decreasing transpiration and soil moisture are associated with decreasing leaf δ13 C. Taken together these results outline a strategy for using leaf δ13 C and reveal its usefulness as a measure of transpiration efficiency under well-watered conditions rather than a predictor of performance under drought.
An inexpensive air stream temperature controller and its use to facilitate temperature-controlled behavior in Drosophila

Controlling the environment of an organism has many biologically relevant applications. Temperature-dependent inducible biological reagents have proven invaluable for elucidating signaling cascades and dissection of neural circuits. Here we develop a simple and affordable system for rapidly changing temperature in a chamber housing adult Drosophila melanogaster. Utilizing flies expressing the temperature-inducible channel dTrpA1 in dopaminergic neurons we show rapid and reproducible changes in locomotor behavior. This device should have wide application to temperature-modulated biological reagents.
New Techniques for Efficient Trapdoor Functions and Applications

We develop techniques for constructing trapdoor functions (TDFs) with short image size and advanced security properties. Our approach builds on the recent framework of Garg and Hajiabadi [CRYPTO 2018]. As applications of our techniques, we obtain The first construction of deterministic-encryption schemes for block-source inputs (both for the CPA and CCA cases) based on the Computational Diffie-Hellman (CDH) assumption. Moreover, by applying our efficiency-enhancing techniques, we obtain CDH-based schemes with ciphertext size linear in plaintext size. The first construction of lossy TDFs based on the Decisional Diffie-Hellman (DDH) assumption with image size linear in input size, while retaining the lossiness rate of [Peikert-Waters STOC 2008].
Totally orthogonal finite simple groups

We prove that if G is a finite simple group, then all irreducible complex representations of G may be realized over the real numbers if and only if every element of G may be written as a product of two involutions in G. This follows from our result that if q is a power of 2, then all irreducible complex representations of the orthogonal groups $$\mathrm {O}^{\pm }(2n,\mathbb {F}_q)$$ may be realized over the real numbers. We also obtain generating functions for the sums of degrees of several sets of unipotent characters of finite orthogonal groups.
EARS to cyber incidents in health care.

Background Connected medical devices and electronic health records have added important functionality to patient care, but have also introduced a range of cybersecurity concerns. When a healthcare organization suffers from a cybersecurity incident, its incident response strategies are critical to the success of its recovery. Objective In this article, we identify gaps in research concerning cybersecurity response plans in healthcare. Through a systematic literature review, we develop aggregated strategies that professionals can use to construct better response strategies in their organizations. Methods We reviewed journal articles on cyber incident response plans in healthcare published in PubMed and Web of Science. We sought to collect articles on the intersection of cybersecurity and healthcare that focused on incident response strategies. Results We identified and reviewed 13 articles for cybersecurity response recommendations. We then extracted information such as research methods, findings, and implications. Finally, we synthesized the recommendations into a framework of eight aggregated response strategies (EARS) that fall under managerial and technological categories. Conclusions We conducted a systematic review of the literature on cybersecurity response plans in healthcare and developed a novel framework for response strategies that could be deployed by healthcare organizations. More work is needed to evaluate incident response strategies in healthcare.
Robust modeling of acoustic phonon transmission in nanomechanical structures

The transmission of acoustic phonons is an important element in the design and performance of nano-mechanical devices operating in the mesoscopic limit. Analytic expressions for the power transmission coefficient, T, exist only in the low-frequency limit, in cases described by thin-plate elasticity theory, and for well-defined elastic waveguiding geometries. We compare two numerical techniques based on finite-element computations to determine the frequency dependence of T for arbitrary phonon scattering structures. Both methods take into account acoustic mode conversion to acoustic and optical modes. In one case, the phase and amplitude of complex-valued reflected waves are determined and related to transmission through a Fresnel equation, while in the other, the magnitude of the transmitted mechanical power is directly calculated. The numerical robustness of these methods is demonstrated by considering the transmission across an abrupt junction in a rectangular elastic beam, a well-known problem of considerable importance in mesoscopic device physics. The simulations presented extend the standard results for acoustic phonon transmission at an abrupt junction, and are in good agreement with analytic predictions in the long-wavelength limit. More generally, the numerical methods developed provide an effective tool for calculating acoustic mode energy loss in nano-mechanical resonators through mode conversion and heat transfer in arbitrary mesoscopic structures.The transmission of acoustic phonons is an important element in the design and performance of nano-mechanical devices operating in the mesoscopic limit. Analytic expressions for the power transmission coefficient, T, exist only in the low-frequency limit, in cases described by thin-plate elasticity theory, and for well-defined elastic waveguiding geometries. We compare two numerical techniques based on finite-element computations to determine the frequency dependence of T for arbitrary phonon scattering structures. Both methods take into account acoustic mode conversion to acoustic and optical modes. In one case, the phase and amplitude of complex-valued reflected waves are determined and related to transmission through a Fresnel equation, while in the other, the magnitude of the transmitted mechanical power is directly calculated. The numerical robustness of these methods is demonstrated by considering the transmission across an abrupt junction in a rectangular elastic beam, a well-known problem of c...
signSGD with Majority Vote is Communication Efficient and Fault Tolerant

Training neural networks on large datasets can be accelerated by distributing the workload over a network of machines. As datasets grow ever larger, networks of hundreds or thousands of machines become economically viable. The time cost of communicating gradients limits the effectiveness of using such large machine counts, as may the increased chance of network faults. We explore a particularly simple algorithm for robust, communication-efficient learning---signSGD. Workers transmit only the sign of their gradient vector to a server, and the overall update is decided by a majority vote. This algorithm uses 32× less communication per iteration than full-precision, distributed SGD. Under natural conditions verified by experiment, we prove that signSGD converges in the large and mini-batch settings, establishing convergence for a parameter regime of Adam as a byproduct. Aggregating sign gradients by majority vote means that no individual worker has too much power. We prove that unlike SGD, majority vote is robust when up to 50% of workers behave adversarially. The class of adversaries we consider includes as special cases those that invert or randomise their gradient estimate. On the practical side, we built our distributed training system in Pytorch. Benchmarking against the state of the art collective communications library (NCCL), our framework---with the parameter server housed entirely on one machine---led to a 25% reduction in time for training resnet50 on Imagenet when using 15 AWS p3.2xlarge machines.
Informatics in the Health Sciences

Informatics is the use of information technology, broadly conceived, to advance a domain of work or inquiry. Concerns within informatics divide into system, role, function, workflow, information repository, information tools, standards, and technology. Individual efforts go through four phases: model formulation, system development, system installation, and study of effects. Areas within health sciences informatics include medical informatics, nursing informatics, public health informatics, and statistics informatics. Keywords: medical informatics; informatics; nursing informatics; public health informatics; statistics informatics
Environmentally Assisted Cracking of Commercial Ni-Cr-Mo Alloys - A Review

Nickel-Chromium-Molybdenum alloys (Ni-Cr-Mo) are highly resistant to general corrosion, localized corrosion and environmentally assisted cracking (EAC). Cr acts as a beneficial element under oxidizing acidic conditions and Mo under reducing conditions. All three elements (Ni, Cr and Mo) act synergistically to provide resistance to EAC in environments such as hot concentrated chloride solutions. Ni-Cr-Mo alloys may suffer EAC in environments such as hot caustic solutions, hot wet hydrofluoric acid (HF) solutions and in super critical water oxidation (SCWO) applications. Not all the Ni-Cr-Mo alloys have the same susceptibility to cracking in the mentioned environments. Most of the available data regarding EAC is for the oldest Ni-Cr-Mo alloys such as N10276 and N06625.
Are You Talking to Me?: Multi-Dimensional Language Analysis of Explanations during Reading

This study examines the extent to which instructions to self-explain vs. other-explain a text lead readers to produce different forms of explanations. Natural language processing was used to examine the content and characteristics of the explanations produced as a function of instruction condition. Undergraduate students (n = 146) typed either self-explanations or other-explanations while reading a science text. The linguistic properties of these explanations were calculated using three automated text analysis tools. Machine learning classifiers in combination with the features were used to predict instruction condition (i.e., self- or other-explanation). The best machine learning model performed at rates above chance (kappa = .247; accuracy = 63%). Follow-up analyses indicated that students in the self-explanation condition generated explanations that were more cohesive and that contained words that were more related to social order (e.g., ethics). Overall, the results suggest that natural language processing techniques can be used to detect subtle differences in students' processing of complex texts.
Do investors perceive a change in audit quality following the rotation of the engagement partner

Abstract Though Section 203 of the Sarbanes-Oxley Act (SOX) calls for the rotation of the audit partner every five years, we do not know whether investors value audit partner rotation. This is an important issue since many in the auditing profession believe that mandatory rotation of the audit partner is unnecessary and may in fact impair audit quality. We identify a sample of firms that disclosed changes in the engagement partner in the proxy statement and examine whether equity investors perceive a change in audit quality following the partner rotation. We find a significant increase in earnings informativeness following audit partner rotation. We also find that short sellers regard earnings in the post-rotation to be of higher quality than earnings prior to the rotation. Finally, cost of equity capital is lower following partner rotation. Our findings have important implications for the regulators, auditors, and investors.
EFFORT EXPENDITURE FOR CASH FLOW IN A MEAN-FIELD EQUILIBRIUM

We study a mean-field game framework in which agents expend costly effort in order to transition into a state where they receive cash flows. As more agents transition into the cash flow receiving s...
E-Cadherin Represses Anchorage-Independent Growth in Sarcomas through Both Signaling and Mechanical Mechanisms

CDH1 (also known as E-cadherin), an epithelial-specific cell-cell adhesion molecule, plays multiple roles in maintaining adherens junctions, regulating migration and invasion, and mediating intracellular signaling. Downregulation of E-cadherin is a hallmark of epithelial-to-mesenchymal transition (EMT) and correlates with poor prognosis in multiple carcinomas. Conversely, upregulation of E-cadherin is prognostic for improved survival in sarcomas. Yet, despite the prognostic benefit of E-cadherin expression in sarcoma, the mechanistic significance of E-cadherin in sarcomas remains poorly understood. Here, by combining mathematical models with wet-bench experiments, we identify the core regulatory networks mediated by E-cadherin in sarcomas, and decipher their functional consequences. Unlike carcinomas, E-cadherin overexpression in sarcomas does not induce a mesenchymal-to-epithelial transition (MET). However, E-cadherin acts to reduce both anchorage-independent growth and spheroid formation of sarcoma cells. Ectopic E-cadherin expression acts to downregulate phosphorylated CREB1 (p-CREB) and the transcription factor, TBX2, to inhibit anchorage-independent growth. RNAi-mediated knockdown of TBX2 phenocopies the effect of E-cadherin on CREB levels and restores sensitivity to anchorage-independent growth in sarcoma cells. Beyond its signaling role, E-cadherin expression in sarcoma cells can also strengthen cell-cell adhesion and restricts spheroid growth through mechanical action. Together, our results demonstrate that E-cadherin inhibits sarcoma aggressiveness by preventing anchorage-independent growth. IMPLICATIONS: We highlight how E-cadherin can restrict aggressive behavior in sarcomas through both biochemical signaling and biomechanical effects.
Viewing pornography through a children’s rights lens

Recent research related to childhood exposure to pornography suggests that some children may be harmed by the exposure, which raises legal issues in light of the international legal framework that ...
GaN Decomposition in Ammonia

GaN decomposition is studied as a function of pressure and temperature in mixed NH3 and H2 flows more characteristic of the MOVPE growth environment. As NH3 is substituted for the 6 SLM H2 flow, the GaN decomposition rate at 1000 °C is reduced from 1×1016 cm−2 s−1 (i.e. 9 monolayers/s) in pure H2 to a minimum of 1×1014 cm−2 s−1 at an NH3 density of 1×1019 cm−3. Further increases of the NH3 density above 1×1019 cm−3 result in an increase in the GaN decomposition rate. The measured activation energy, EA, for GaN decomposition in mixed H2 and NH3 flows is less than the EA measured in vacuum and in N2 environments. As the growth pressure is increased under the same H2 and NH3 flow conditions, the decomposition rate increases and the growth rate decreases with the addition of trimethylgallium to the flow. The decomposition in mixed NH3 and H2 and in pure H2 flows behave similarly, suggesting that surface H plays a similar role in the decomposition and growth of GaN in NH3.
Gender and judging: evidence from the European Court of human rights

How does increasing the number of women on the bench affect the outcome of judicial proceedings? This article evaluates this question in the European Court of Human Rights using a new dataset that ...
Invite Your Friend and You’ll Move Up in Line: Optimal Design of Referral Priority Programs

Problem definition : This paper studies the optimal design of referral priority programs, in which customers on a waiting list can jump the line by inviting their friends to also join the waiting l...
The Feasibility of a Using a Smart Button Mobile Health System to Self-Track Medication Adherence and Deliver Tailored Short Message Service Text Message Feedback.

Background: As many as 50% of people experience medication nonadherence, yet studies for detecting nonadherence and delivering real-time interventions to improve adherence are lacking. Mobile health (mHealth) technologies show promise to track and support medication adherence. Objective: The study aimed to evaluate the feasibility and acceptability of using an mHealth system for medication adherence tracking and intervention delivery. The mHealth system comprises a smart button device to self-track medication taking, a companion smartphone app, a computer algorithm used to determine adherence and then deliver a standard or tailored SMS (short message service) text message on the basis of timing of medication taking. Standard SMS text messages indicated that the smartphone app registered the button press, whereas tailored SMS text messages encouraged habit formation and systems thinking on the basis of the timing the medications were taken. Methods: A convenience sample of 5 adults with chronic kidney disease (CKD), who were prescribed antihypertensive medication, participated in a 52-day longitudinal study. The study was conducted in 3 phases, with a standard SMS text message sent in phases 1 (study days 1-14) and 3 (study days 46-52) and tailored SMS text messages sent during phase 2 (study days 15-45) in response to participant medication self-tracking. Medication adherence was measured using: (1) the smart button and (2) electronic medication monitoring caps. Concordance between these 2 methods was evaluated using percentage of measurements made on the same day and occurring within ±5 min of one another. Acceptability was evaluated using qualitative feedback from participants. Results: A total of 5 patients with CKD, stages 1-4, were enrolled in the study, with the majority being men (60%), white (80%), and Hispanic/Latino (40%) of middle age (52.6 years, SD 22.49; range 20-70). The mHealth system was successfully initiated in the clinic setting for all enrolled participants. Of the expected 260 data points, 36.5% (n=95) were recorded with the smart button and 76.2% (n=198) with electronic monitoring. Concordant events (n=94), in which events were recorded with both the smart button and electronic monitoring, occurred 47% of the time and 58% of these events occurred within ±5 min of one another. Participant comments suggested SMS text messages were encouraging. Conclusions: It was feasible to recruit participants in the clinic setting for an mHealth study, and our system was successfully initiated for all enrolled participants. The smart button is an innovative way to self-report adherence data, including date and timing of medication taking, which were not previously available from measures that rely on recall of adherence. Although the selected smart button had poor concordance with electronic monitoring caps, participants were willing to use it to self-track medication adherence, and they found the mHealth system acceptable to use in most cases.
Kinetic Monte Carlo simulation of sintering behavior of additively manufactured stainless steel powder particles using reconstructed microstructures from synchrotron X-ray microtomography

Abstract In this study, the sintering behavior of additively manufactured stainless steel powder particles is simulated using a three-dimensional kinetic Monte Carlo (kMC) model. The initial microstructure of powder particles is reconstructed using micro-CT images from the Argonne National Laboratory’s synchrotron X-ray microtomography facility. Using the model, the sintering characteristics of the powder, including its relative density, neck growth, and grain coarsening, are quantitatively analyzed. Sintering temperature directly affects the rate of densification and grain growth and coarsening. Higher temperature results in faster densification and grain growth. Additionally, the relationship between grain coarsening and densification is analyzed. It is observed that when the relative density is below 0.70, the powder particles undergo densification; whereas when the relative density is higher than 0.70, grain coarsening is the main mechanism.
Estimating Time to the Common Ancestor for a Beneficial Allele

The haplotypes of a beneficial allele carry information about its history that can shed light on its age and the putative cause for its increase in frequency. Specifically, the signature of an allele's age is contained in the pattern of variation that mutation and recombination impose on its haplotypic background. We provide a method to exploit this pattern and infer the time to the common ancestor of a positively selected allele following a rapid increase in frequency. We do so using a hidden Markov model which leverages the length distribution of the shared ancestral haplotype, the accumulation of derived mutations on the ancestral background, and the surrounding background haplotype diversity. Using simulations, we demonstrate how the inclusion of information from both mutation and recombination events increases accuracy relative to approaches that only consider a single type of event. We also show the behavior of the estimator in cases where data do not conform to model assumptions, and provide some diagnostics for assessing and improving inference. Using the method, we analyze population-specific patterns in the 1000 Genomes Project data to estimate the timing of adaptation for several variants which show evidence of recent selection and functional relevance to diet, skin pigmentation, and morphology in humans.
Aminolysis of allyl esters with bislithium aryl amides

The aminolysis of allyl esters with bislithium amides is reported. Tertiary aryl amides were synthesized in a one-pot reaction with bislithium amides and a suitable electrophile in good yields. The scope of this reaction was demonstrated with a variety of anilines and aminopyridines and applied to the synthesis of triphenylmethylacetamides.
Gene synthesis allows biologists to source genes from farther away in the tree of life

Gene synthesis enables creation and modification of genetic sequences at an unprecedented pace, offering enormous potential for new biological functionality but also increasing the need for biosurveillance. In this paper, we introduce a bioinformatics technique for determining whether a gene is natural or synthetic based solely on nucleotide sequence. This technique, grounded in codon theory and machine learning, can correctly classify genes with 97.7% accuracy on a novel data set. We then classify ∼19,000 unique genes from the Addgene non-profit plasmid repository to investigate whether natural and synthetic genes have differential use in heterologous expression. Phylogenetic analysis of distance between source and expression organisms reveals that researchers are using synthesis to source genes from more genetically-distant organisms, particularly for longer genes. We provide empirical evidence that gene synthesis is leading biologists to sample more broadly across the diversity of life, and we provide a foundational tool for the biosurveillance community.
Secure and Constant Cost Public Cloud Storage Auditing with Deduplication.

Data integrity and storage efficiency are two important requirements for cloud storage. Proof of Retrievability (POR) and Proof of Data Possession (PDP) techniques assure data integrity for cloud storage. Proof of Ownership (POW) improves storage efficiency by securely removing unnecessarily duplicated data on the storage server. However, trivial combination of the two techniques, in order to achieve both data integrity and storage efficiency, results in non-trivial duplication of metadata (i.e., authentication tags), which contradicts the objectives of POW. Recent attempts to this problem introduce tremendous computational and communication costs and have also been proven not secure. It calls for a new solution to support efficient and secure data integrity auditing with storage deduplication for cloud storage. In this paper we solve this open problem with a novel scheme based on techniques including polynomial-based authentication tags and homomorphic linear authenticators. Our design allows deduplication of both files and their corresponding authentication tags. Data integrity auditing and storage deduplication are achieved simultaneously. Our proposed scheme is also characterized by constant realtime communication and computational cost on the user side. Public auditing and batch auditing are both supported. Hence, our proposed scheme outperforms existing POR and PDP schemes while providing the additional functionality of deduplication. We prove the security of our proposed scheme based on the Computational Diffie-Hellman problem, the Static Diffie-Hellman problem and the t-Strong Diffie-Hellman problem. Numerical analysis and experimental results on Amazon AWS show that our scheme is efficient and scalable.
Quantifying Platelet Margination in Diabetic Blood Flow

Patients with type 2 diabetes mellitus (T2DM) develop thrombotic abnormalities strongly associated with cardiovascular diseases. In addition to the changes of numerous coagulation factors such as elevated levels of thrombin and fibrinogen, the abnormal rheological effects of red blood cells (RBCs) and platelets flowing in blood are crucial in platelet adhesion and thrombus formation in T2DM. An important process contributing to the latter is the platelet margination. We employ the dissipative particle dynamics method to seamlessly model cells, plasma, and vessel walls. We perform a systematic study on RBC and platelet transport in cylindrical vessels by considering different cell shapes, sizes, and RBC deformabilities in healthy and T2DM blood, as well as variable flowrates and hematocrit. In particular, we use cellular-level RBC and platelet models with parameters derived from patient-specific data and present a sensitivity study. We find T2DM RBCs, which are less deformable compared to normal RBCs, lower the transport of platelets toward the vessel walls, whereas platelets with higher mean volume (often observed in T2DM) lead to enhanced margination. Furthermore, increasing the flowrate or hematocrit enhances platelet margination. We also investigated the effect of platelet shape and observed a nonmonotonic variation with the highest near-wall concentration corresponding to platelets with a moderate aspect ratio of 0.38. We examine the role of white blood cells (WBCs), whose count is increased notably in T2DM patients. We find that WBC rolling or WBC adhesion tends to decrease platelet margination due to hydrodynamic effects. To the best of our knowledge, such simulations of blood including all blood cells have not been performed before, and our quantitative findings can help separate the effects of hydrodynamic interactions from adhesive interactions and potentially shed light on the associated pathological processes in T2DM such as increased inflammatory response, platelet activation and adhesion, and ultimately thrombus formation.
Hydrazine derivatives of carbohydrates and related compounds

Publisher Summary This chapter provides an overview of the hydrazine derivatives of carbohydrates and related compounds. Hydrazine, hydroxylamine, and hydrogen peroxide are highly reactive nucleophiles that add to carbonyl compounds to give N - and O -adducts, which are not usually isolated. The chapter presents an account of the rich chemistry of the hydrazine derivatives of sugars, the versatility of their structures, and their availability, which makes them valuable enantiomerically pure synthons for chiral products. For example, reduction of aldose hydrazones affords an important class of chiral amino- and iminodeoxy sugars that contain nitrogen in place of the oxygen present in the rings of natural sugars. These imino sugars exhibit a wide spectrum of biological activities, mainly attributable to their ability to act as enzyme inhibitors. Also of considerable interest are the carba-sugars—the carbocyclic analogs of monosaccharides—which are readily available from inosose phenylhydrazones. Members of both these classes of compounds—the carba-sugars and the imino sugars (“aza sugars”)—are capable of inhibiting enzymes because they mimic the enzyme's natural substrates (the sugars). This chapter provides an overview of saccharide hydrazones and glycosylhydrazines and also discusses about saccharide osazones and poly(hydrazones).
Stereoselective nucleophilic addition to conformationally constrained piperidines. An efficient route to 2-axial-6-equatorial disubstituted piperidines.

Abstract Addition of RMgX to 2-methoxy-4-tert-butylpiperidine formamidine in dichloromethane or ether gives good to excellent yields of axial product.
A 117-year retrospective analysis of Pennsylvania tick community dynamics

Tick-borne diseases have been increasing at the local, national, and global levels. Researchers studying ticks and tick-borne diseases need a thorough knowledge of the pathogens, vectors, and epidemiology of disease spread. Both active and passive surveillance approaches are typically used to estimate tick population size and risk of tick encounter. Our data consists of a composite of active and long-term passive surveillance, which has provided insight into spatial variability and temporal dynamics of ectoparasite communities and identified rarer tick species. We present a retrospective analysis on compiled data of ticks from Pennsylvania over the last 117 years. We compiled data from ticks collected during tick surveillance research, and from citizen-based submissions. The majority of the specimens were submitted by citizens. However, a subset of the data was collected through active methods (flagging or dragging, or removal of ticks from wildlife). We analyzed all data from 1900–2017 for tick community composition, host associations, and spatio-temporal dynamics. In total there were 4491 submission lots consisting of 7132 tick specimens. Twenty-four different species were identified, with the large proportion of submissions represented by five tick species. We observed a shift in tick community composition in which the dominant species of tick (Ixodes cookei) was overtaken in abundance by Dermacentor variabilis in the early 1990s and then replaced in abundance by I. scapularis. We analyzed host data and identified overlaps in host range amongst tick species. We highlight the importance of long-term passive tick surveillance in investigating the ecology of both common and rare tick species. Information on the geographical distribution, host-association, and seasonality of the tick community can help researchers and health-officials to identify high-risk areas.