cssi/SciSciGPT-SciSciNet huggingface dataset:
Nucleation–elongation: a mechanism for cooperative supramolecular polymerization

The kinetic and thermodynamic characteristics of polymerizations following a cooperative, nucleation-elongation mechanism are discussed in comparison to those of non-cooperative, isodesmic polymerizations. Nucleation-elongation polymerization is a relatively unexplored avenue of synthetic polymer chemistry and offers some unique and interesting thermodynamic and kinetic attributes not found in the more classical mechanisms of polymer chemistry.
Relationship between serum leptin and chronic obstructive pulmonary disease in US adults: results from the third National Health and Nutrition Examination Survey.

Background Recent studies suggest an important role for leptin in respiratory immune responses and pathogenesis of inflammatory respiratory diseases. There has been an interest to explore whether leptin plays any role in the pathogenesis of chronic obstructive pulmonary disease (COPD). Objective We conducted a population-based study to evaluate the relationship between serum leptin and COPD in the third US National Health and Nutrition Examination Survey participants. Participants and Design Our study group was constituted by 6415 adults who had fasting serum leptin and underwent spirometry measurement. Main Outcome Measures Serum leptin levels were compared (1) between subjects with normal lung function and those with COPD and (2) among COPD subjects with different severities. Results Among male participants, 2257 were controls, and 680 had COPD. Compared with controls, COPD subjects were older (62 vs 43 years) and had higher prevalence of smokers (78% vs 58%), lower body mass index (BMI) (26.3 vs 26.9), and higher serum leptin levels (6.6 vs 5.9). For female participants, 2918 were controls, and 560 had COPD. Those with COPD were older (60 vs 43 years) and had lower BMI (26.9 vs 27.7). No differences in serum leptin levels were observed. The independent predictors of COPD in both sexes were age, BMI, and smoking, but not serum leptin. There were no differences in serum leptin among COPD subjects with different severities. Conclusions We did not find any significant difference in the levels of serum leptin in subjects with COPD. Our data provide indirect evidence against a major role for serum leptin in the pathogenesis of COPD in humans.
Shear-Induced Nitric Oxide Production by Endothelial Cells

We present a biochemical model of the wall shear stress-induced activation of endothelial nitric oxide synthase (eNOS) in an endothelial cell. The model includes three key mechanotransducers: mechanosensing ion channels, integrins, and G protein-coupled receptors. The reaction cascade consists of two interconnected parts. The first is rapid activation of calcium, which results in formation of calcium-calmodulin complexes, followed by recruitment of eNOS from caveolae. The second is phosphorylation of eNOS by protein kinases PKC and AKT. The model also includes a negative feedback loop due to inhibition of calcium influx into the cell by cyclic guanosine monophosphate (cGMP). In this feedback, increased nitric oxide (NO) levels cause an increase in cGMP levels, so that cGMP inhibition of calcium influx can limit NO production. The model was used to predict the dynamics of NO production by an endothelial cell subjected to a step increase of wall shear stress from zero to a finite physiologically relevant value. Among several experimentally observed features, the model predicts a highly nonlinear, biphasic transient behavior of eNOS activation and NO production: a rapid initial activation due to the very rapid influx of calcium into the cytosol (occurring within 1–5 min) is followed by a sustained period of activation due to protein kinases.
ULTRASOUND FINDINGS IN ASYMPTOMATIC PATIENTS WITH DUAL TAPER MODULAR TOTAL HIP ARTHROPLASTY

Introduction The use of metal-on-metal (MOM) and modular total hip arthroplasty (THA) is associated with potentially serious complications including elevated serum metal ion levels, pseudotumor, cardiomyopathy and neurologic abnormalities. The primary aim of this analysis was to identify any associations between the presence of pseudotumor, serum metal ion levels, and specific dual modular implant components. Methods We evaluated prospectively collected data from 49 patients, mean age 58.4 years, who underwent implantation of modular THA from 01/2004-01/2010. The collected data spanned a 5–11 year period from the time of index procedure. Serum metal ion levels, including titanium, cobalt and chromium, were collected in 2012 and 2015. Hip ultrasounds were performed on each patient by a trained musculoskeletal radiologist for evaluation of the presence of soft-tissue pseudotumor. Univariate nonparametric tests were used to compare the two groups: Fisher9s exact tests for categorical variables, and Wilcoxon two-group tests for continuous variables. For the purposes of analysis, values that were below the level of detection (LOD) were set to half the LOD. All analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, NC, USA). Statistical significance is set at p Results Eight of 49 patients (16.3%) had pseudotumors on ultrasound examination. The average size measured 35.05 cm3 (7.35 cm3 – 130.81 cm3). In patients without pseudotumor, the serum levels (ng/mL) of titanium, cobalt and chromium were 3.2 ± 2.7, 4.4 ± 5.7 and 3.4 ± 4.9 in 2012 and 3.6 ± 4.9, 11.3 ± 33.7 and 5.3 ± 10.8 in 2015, respectively. Patients with pseudotumor had titanium, cobalt and chromium levels of 3.5 ± 2.3, 8.4 ± 8.7 and 6.2 ± 9.4 in 2012 and 4.1 ± 3.4, 6.0 ± 4.5 and 5.1 ± 6.4 in 2015. The ratio of cobalt to chromium was 1.6 ± 1.3 in 2012 and 1.8 ± 1.2 in 2015 in patients without pseudotumor and 2.1 ± 1.2 and 1.9 ± 1.3 with patients with pseudotumor, respectively. There was no statistical correlation between the presence of pseudotumor and age, component pairings (stem, neck and cup) and any of the serum metal ion levels. Discussion/Conclusion In this prospective cohort study the incidence of pseudotumor was 16.3% in asymptomatic patients with modular THA. The presence of pseudotumor did not correlate with component pairings, serum metal ion levels or cobalt to chromium ratios.
Global synthesis of drought effects on cereal, legume, tuber and root crops production: A review

Abstract As a result of climate change, drought is predicted to pose greater pressure on food production system than in the past. At the same time, crop yield co-varies with both environmental (e.g., water, temperature, aridity) and agronomic variables (i.e., crop species, soil texture, phenological phase). To improve our quantitative understanding on the effects of these co-varying factors on agricultural productivity, we synthesized previous meta-analysis studies summarizing the results of numerous independent field experiments on drought and its effect on the production of cereal, legume, root and/or tuber (root/tuber) crops. We also included new crops species that were not covered in previous meta-analyses and the effects of heat stress. Our results indicated that cereals tended to be more drought resistant than legumes and root/tubers. Most crops were more sensitive to drought during their reproductive (i.e., grains filling, tuber initiation) than during their vegetative phase, except for wheat, which was also sensitive during vegetative phase. Recovery from drought impact at reproductive phase was either: (i) unfeasible for crops experiencing damage to their reproductive organs (e.g., maize, rice) or (ii) limited for root/tuber crops, provided that water was abundant during the subsequent root/tuber bulking period. Across soil texture, the variability of yield reduction for cereals was also lower in comparison to legume or root/tuber crops, probably due to the extensive and deep rooting system of cereal crops. As crop species, plant phenology, and soil texture were important co-varying factors in determining drought-induced crop yield reduction, no single approach would be sufficient to improve crop performance during drought. Consequently, a combination of approaches, particularly site-specific management practices that consider soil conditions (i.e., intercropping, mulching, and crop rotation) and selection of crop varieties adjusted to the local climate should be adopted in order to improve the sustainability of agricultural production in a changing climate.
Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks

RNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitation-microarray) data for 69 yeast RBPs to construct a network of genome-wide RBP- target RNA interactions for each RBP. We show in humans that majority (~78%) of the RBPs are strongly associated with their target transcripts at transcript level while ~95% of the studied RBPs were also found to be strongly associated with expression levels of target transcripts when protein expression levels of RBPs were employed. At transcript level, RBP - RNA interaction data for the yeast genome, exhibited a strong association for 63% of the RBPs, confirming the association to be conserved across large phylogenetic distances. Analysis to uncover the features contributing to these associations revealed the number of target transcripts and length of the selected protein-coding transcript of an RBP at the transcript level while intensity of the CLIP signal, number of RNA-Binding domains, location of the binding site on the transcript, to be significant at the protein level. Our analysis will contribute to improved modelling and prediction of post-transcriptional networks.
Confirmatory Factor Analysis of the Pittsburgh Sleep Quality Index in Women with Hot Flashes

AbstractObjective:Women, especially those with hot flashes, report poor sleep quality during various stages of the menopausal transition and postmenopause. Sleep measurements vary widely because of the copious instruments available. The Pittsburgh Sleep Quality Index (PSQI) is a frequently used ques
CEMENTING THE PERFECT TKA: ASSURING LONGEVITY

Introduction The common causes of failure leading to revision Total Knee Replacement (TKR) include instability, infection, improper alignment, implant wear and osteolysis and improper cementation. This presentation outlines the details of the art of cementation. Technique 1.Proper exposure with adequate length of incision 2.Avoid cutting of quadriceps tendon in oblique direction (medial-lateral plain) 3.Reduced Tissue Trauma Surgery (RTTS), no tourniquet except for cementing 4.Deliver the tibia in front of the femur (Ran-Sall maneuver) 5.Preserve supra-patellar pouch, coagulate lateral genicular artery 6.8 to 10 mm tibial cut from the uninvolved side, identify the cortical tibial cut 7.Adequate rotation, alignment, lateralisation and restoration of the posterior offset of the femoral component 8.Pulseatile lavage the cut surfaces to clean the cancellous bone 9.Drill holes in the sclerotic bone surface 10.Heated Simplex cement at a doughy state 11.Apply cement on the bone surfaces including posterior femoral condyles and pressurise, apply cement on the components as well 12.Apply manual constant pressure 13.Remove excess cement from posterior femoral condyles, tibia and patella (if resurfaced) 14.Further pressurisation in extension with trial insert 15.Release of the tourniquet and throughout irrigation 16.Closure in flexion without tourniquet and with good approximation of dermis and epidermis. Discussion and Conclusion Based on 15–20 year data, a properly cemented TKR has a survivorship between 93% to 98% with high level of function.
Fraud in medical research.

Les avantages, les causes, la prevention et les reactions dues a la fraude dans la recherche medicale sont analyses
The price of anarchy in transportation networks by estimating user cost functions from actual traffic data

We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.
Lewis Acid Catalyzed Displacement of Trichloroacetimidates in the Synthesis of Functionalized Pyrroloindolines

The pyrroloindoline core is found in many natural products. These structures often differ at the C3a position, which may be substituted with an oxygen, nitrogen, or sp3- or sp2-hybridized carbon. Utilizing a trichloroacetimidate leaving group, a diversity-oriented approach to these structures has been developed. The trichloroacetimidate intermediate allows for the rapid incorporation of anilines, alcohols, thiols, and carbon nucleophiles. This method was applied in the synthesis of arundinine and a formal synthesis of psychotriasine.
Does Bundling Decrease the Probability of Switching Telecommunications Service Providers

I examine whether bundling of telecommunications services makes individuals less likely to switch their service provider because of increased switching costs. Using a detailed survey dataset from the Korea Information Society Development Institute (KISDI), I find that Internet subscribers who previously bundled are less likely to switch their Internet service provider than are those who did not bundle. The results are robust to correction for the potential selection problem through the use of an endogenous treatment model. The finding that bundling reduces the probability of switching service providers and locks-in existing users can have important implications for market competitiveness and consumer welfare.
On a functional equation related to a pair of hedgehogs with congruent projections

Abstract Hedgehogs are geometrical objects that describe the Minkowski differences of arbitrary convex bodies in the Euclidean space E n . We prove that two hedgehogs in E n , n ≥ 3 , coincide up to a translation and a reflection in the origin, provided that their projections onto any two-dimensional plane are directly congruent and have no direct rigid motion symmetries. Our result is a consequence of a more general analytic statement about the solutions of a functional equation in which the support functions of hedgehogs are replaced with two arbitrary twice continuously differentiable functions on the unit sphere.
A recursive framework for expression recognition: from web images to deep models to game dataset

In this paper, we propose a recursive framework to recognize facial expressions from images in real scenes. Unlike traditional approaches that typically focus on developing and refining algorithms for improving recognition performance on an existing dataset, we integrate three important components in a recursive manner: facial dataset generation, facial expression recognition model building, and interactive interfaces for testing and new data collection. To start with, we first create candid images for facial expression (CIFE) dataset. We then apply a convolutional neural network (CNN) to CIFE and build a CNN model for web image expression classification. In order to increase the expression recognition accuracy, we also fine-tune the CNN model and thus obtain a better CNN facial expression recognition model. Based on the fine-tuned CNN model, we design a facial expression game engine and collect a new and more balanced dataset, GaMo. The images of this dataset are collected from the different expressions our game users make when playing the game. Finally, we run yet another recursive step—a self-evaluation of the quality of the data labeling and propose a self-cleansing mechanism for improve the quality of the data. We evaluate the GaMo and CIFE datasets and show that our recursive framework can help build a better facial expression model for dealing with real scene facial expression tasks.
Prospective Fathers and Their Unborn Children

While significant national attention has recently been paid to varying questions about the legal duties of prospective mothers to their unborn children, little comparable focus has been placed on the duties of prospective fathers. Why the difference? Though men and women obviously participate differently in nurturing the development of potential human life, there is much that both prospective parents can do to pro- mote the well-being of their future offspring. This inattention to male responsibilities not only undercuts prevailing governmental interests in protecting potential life, but also may, at times, constitute prohibited sex discrimination. When attention has been paid to prospective fathers, the results are usually disheartening. Treatment of men is often too lenient; yet, on occasion, treatment is too harsh. Further, many times there is little correlation between the legal duties of prospective mothers and fathers in situations where their conduct is comparable. This article seeks to prompt greater dialogue on the legal duties of prospective fathers to their unborn children. In doing so, it employs a recent case litigated in the courts of Florida and involving certain aspects of a prospective father's legal duties. The article utilizes the case, as well as recent controversies over pre-birth maternal duties, to suggest some guidelines for establishing pre-birth paternal duties. In particular, it addresses paternal duties in settings involving criminal prosecution, coercive civil laws, and involuntary termination of parental rights-areas which to date have been significantly considered only for prospective mothers. Finally, it examines additional pre-birth paternal duties in settings where there are no easy parallels to maternal conduct.
The strength to face the facts: Self-regulation defends against defensive information processing

Abstract Five studies examined the impact of self-regulatory capacities on defensive information processing—the tendency to deny, distort, or avoid diagnostic self-threatening information. Across domains, we found that people low in trait (Studies 1 and 5) and state (Studies 2, 3, and 4) self-regulatory capacities were more likely to deny the validity and importance of negative feedback, and were less willing to seek improvement based on this information. Alternative explanations based on self-esteem and competence-based deficits were ruled out. Moreover, we demonstrated a boundary condition of this effect: For participants high in self-improvement motivation, reduced self-regulatory capacities did not affect defensive processing (Studies 4 and 5). Taken together, these results suggest that trait and state levels of self-regulatory capacities are a key factor in determining whether people engage in defensive information processing.
Formal Hypothesis Tests for Additive Structure in Random Forests

ABSTRACTWhile statistical learning methods have proved powerful tools for predictive modeling, the black-box nature of the models they produce can severely limit their interpretability and the ability to conduct formal inference. However, the natural structure of ensemble learners like bagged trees and random forests has been shown to admit desirable asymptotic properties when base learners are built with proper subsamples. In this work, we demonstrate that by defining an appropriate grid structure on the covariate space, we may carry out formal hypothesis tests for both variable importance and underlying additive model structure. To our knowledge, these tests represent the first statistical tools for investigating the underlying regression structure in a context such as random forests. We develop notions of total and partial additivity and further demonstrate that testing can be carried out at no additional computational cost by estimating the variance within the process of constructing the ensemble. Fur...
Optimization of Airport Surface Operations Under Uncertainty

With the rapidly increasing air traffic volume and airports becoming bottlenecks of the air transportation system, integrated aircraft routing and flight scheduling have the potential to improve th...
Simulation of orographic effects with a Quasi-3-D Multiscale Modeling Framework: Basic algorithm and preliminary results

The global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of the topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation. This article is protected by copyright. All rights reserved.
Learning regular omega languages

We provide an algorithm for learning an unknown regular set of infinite words, using membership and equivalence queries. Three variations of the algorithm learn three different canonical representations of omega regular languages, using the notion of families of dfas. One is of size similar to L $, a dfa representation recently learned using L* [7]. The second is based on the syntactic forc, introduced in [14]. The third is introduced herein.We show that the second can be exponentially smaller than the first, and the third is at most as large as the first two, with up to a quadratic saving with respect to the second.
Error exponents for channel coding with side information

Capacity formulas and random-coding and sphere-packing exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. Information is to be reliably transmitted through a noisy channel with random state sequence. Partial information about the state sequence is available to the encoder and decoder. Two families of channels are considered: (1) compound discrete memoryless channels (C-DMC); and (2) channels with arbitrary memory, subject to an additive cost constraint, or more generally to a constraint on the conditional type of the channel output given the input. Both problems are closely connected. For the C-DMC case, our random-coding and sphere-packing exponents coincide at high rates, thereby determining the reliability function of the channel family. The random-coding exponent is achieved using a 3D binning scheme and a maximum penalized mutual information decoder. In the case of arbitrary channels, with memory, a larger random-coding error exponent than in the C-DMC case is obtained. Applications of this study include watermarking, data hiding, communication in presence of partially known interferers, and problems such as broadcast channels, all of which involve the fundamental idea of binning.
Supporting novel biomedical research via multilayer collaboration networks.

The value of research containing novel combinations of molecules can be seen in many innovative and award-winning research programs. Despite calls to use innovative approaches to address common diseases, an increasing majority of research funding goes toward “safe” incremental research. Counteracting this trend by nurturing novel and potentially transformative scientific research is challenging and it must be supported in competition with established research programs. Therefore, we propose a tool that helps to resolve the tension between safe/fundable research vs. high-risk/potentially transformational research. It does this by identifying hidden overlapping interests around novel molecular research topics. Specifically, it identifies paths of molecular interactions that connect research topics and hypotheses that would not typically be associated, as the basis for scientific collaboration. Because these collaborations are related to the scientists’ present trajectory, they are low risk and can be initiated rapidly. Unlike most incremental steps, these collaborations have the potential for leaps in understanding, as they reposition research for novel disease applications. We demonstrate the use of this tool to identify scientists who could contribute to understanding the cellular role of genes with novel associations with Alzheimer’s disease, which have not been thoroughly characterized, in part due to the funding emphasis on established research.
A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra

Motivation: Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a ‘bird's eye view’ of intact proteoforms. The combinatorial explosion of various alterations on a protein may result in billions of possible proteoforms, making proteoform identification a challenging computational problem. Results: We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry datasets showed that TopMG outperformed existing methods in identifying complex proteoforms. Availability and implementation: http://proteomics.informatics.iupui.edu/software/topmg/ Contact: xwliu@iupui.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Contactless hand tremor detector based on an inductive sensor

A contactless detector is presented for evaluating hand tremors caused by exercise-induced fatigue and early Parkinson’s disease. The device consists of a spiral coil, a microcontroller, and an inductive sensor circuitry. Theory shows that the resonant frequency of the circuitry increases when the distance between the hand and the spiral coil decreases, thus small variations of distance from tremor can be detected from the changes of resonant frequencies. A mechanical hand was built for experiments to simulate human hand tremors with repeatability at a fixed frequency. The magnitudes and frequencies of the tremors in the mechanical hand were quantitatively identified using the inductive sensor. Hence, feasibility and accuracy of the contactless hand tremor detector were determined. A triaxial accelerometer was used for comparison. By comparing spectral distributions and magnitudes of the tremors, the inductive sensor performed better than the accelerometer. The detector was applied to evaluate actual hand tremors of three subjects who had undergone exercise to induce tremors. The tremor waveform amplitudes of the subjects were quantitatively analyzed by the standard deviations method. The increased signal energies of exercise-induced tremor within 8–12 Hz were confirmed. Then, a subject with early Parkinson’s disease was evaluated by the proposed hand tremor detector. The tremor magnitudes and frequencies of the patient hand were quantitatively identified within in 4–7 Hz. Therefore, the new contactless hand tremor detector can be developed as a clinical instrument for monitoring the fatigue symptoms of post-exercise and diagnosing the early Parkinson’s disease.
Acceleration sensitivity of crystal resonators affected by the mass and location of electrodes

Predominant thickness-shear frequencies and modes of a crystal plate with electrodes of arbitrary shape and mass distribution are obtained by a finite-element method, based on Mindlin's first-order equations with platings. These frequencies and modes are used in a perturbation method for computing the acceleration sensitivity of crystal resonators with electrodes. Computations are made for a square AT-cut quartz plate that is supported by a four-point mount and coated with identical square and uniform electrodes on the upper and lower faces of the plate. To study the effect of uneven distribution of electrode mass, acceleration sensitivities are calculated when a small mass is added at various locations near the edges of the square electrodes. It is found that the percent increase of the acceleration sensitivity of the resonator with a small added mass to that of the resonator without added mass ranges from 3.8% to 541.7%, depending on the location of the small mass placed at the edges of the electrodes. >
Rotor Tip Vortex Geometry Measurements Using the Wide-Field Shadowgraph Technique

Rotor tip vortex geometry data have been acquired using the wide-field shadowgraph technique. Shadowgraphs were taken of the wakes of two model main-rotor systems in hover. These shadowgraphs provided detailed tip vortex trajectories from which axial and radial vortex coordinates were measured. Using these coordinates, prescribed-wake parameters were determined and input into a hover-performance prediction code. The resultant predictions were compared with experimental performance data to help assess the capabilities of this code. Another result of the experimental work was the development of a method to predict the visibility of rotor tip vortices on shadowgraphs. Using this method, the ability of the shadowgraph technique to visualize tip vortices in the rotor wake was quantified.
Evaluation of automated vehicles in the frontal cut-in scenario — An enhanced approach using piecewise mixture models

Evaluation and testing are critical for the development of Automated Vehicles (AVs). Currently, companies test AVs on public roads, which is very time-consuming and inefficient. We proposed the Accelerated Evaluation concept which uses a modified statistics of the surrounding vehicles and the Importance Sampling theory to reduce the evaluation time by several orders of magnitude, while ensuring the final evaluation results are accurate. In this paper, we further extend this idea by using Piecewise Mixture Distribution models instead of Single Distribution models. We demonstrate this idea to evaluate vehicle safety in lane change scenarios. The behavior of the cut-in vehicles was modeled based on more than 400,000 naturalistic driving lane changes collected by the University of Michigan Safety Pilot Model Deployment Program. Simulation results confirm that the accuracy and efficiency of the Piecewise Mixture Distribution method are better than the single distribution.
Big Data in HEP: A comprehensive use case study

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data technologies have emerged to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and promise a fresh look at analysis of very large datasets and could potentially reduce the time-to-physics with increased interactivity. In this talk, we present an active LHC Run 2 analysis, searching for dark matter with the CMS detector, as a testbed for Big Data technologies. We directly compare the traditional NTuple-based analysis with an equivalent analysis using Apache Spark on the Hadoop ecosystem and beyond. In both cases, we start the analysis with the official experiment data formats and produce publication physics plots. We will discuss advantages and disadvantages of each approach and give an outlook on further studies needed.
Mutual information based labelling and comparing clusters

After a clustering solution is generated automatically, labelling these clusters becomes important to help understanding the results. In this paper, we propose to use a mutual information based method to label clusters of journal articles. Topical terms which have the highest normalised mutual information with a certain cluster are selected to be the labels of the cluster. Discussion of the labelling technique with a domain expert was used as a check that the labels are discriminating not only lexical-wise but also semantically. Based on a common set of topical terms, we also propose to generate lexical fingerprints as a representation of individual clusters. Eventually, we visualise and compare these fingerprints of different clusters from either one clustering solution or different ones.
A COMPARISON OF CLINICAL AND PATIENT-RECORDED OUTCOMES OF TKR IN INDONESIAN VERSUS AMERICAN PATIENTS

Introduction There has not been a comparison of patients and outcomes between two separate countries for any knee prosthesis. This study compares total knee replacement outcomes between an Indonesian and American cohort. We aim to compare the clinical results between two different hospitals in two different countries using post-operative range of motion as the primary clinical result. Materials and Methods 177 Indonesian RPF TKR patients were compared to 84 American patients. Demographics, patient recorded outcomes scores (KSS, PAQ, WOMAC), flexion, and component size were compared between the groups. Standard t-test was used to compare the variables between the two countries and regression analysis adjusting for age, BMI, length of follow-up, sex, preoperative WOMAC and PAQ score, preoperative KSS knee score, preoperative KSS function score, and preoperative UCLA was used to compare outcomes. Results Between the Indonesian and American RPF cohorts there was significant difference between age (64.6±7.08 vs. 67.8±6.53; p=.003), preoperative KSS function score (54.2±14.1 vs. 60.4±18.4; p=.011), preoperative WOMAC (71.2±7.9 vs. 65.1±16.9; p=.012), postoperative KSS Knee score (93.3±4.74 vs. 95.7±6.25; p=.003), and postoperative KSS function score (97.0±4.26 vs. 93.5±13.1). No difference was found in pre or postoperative flexion. Regression analysis found no significance difference in outcomes between Indonesian and American patients when adjusted for variables (p=0.45). Conclusions Despite cultural differences, the Indonesian and American cohort had similar clinical outcomes including improved flexion, which coincides with a high flexion knee design. Interestingly, Indonesian patients rated themselves worse on patient recorded preoperative outcome scores. More research is needed to investigate the difference between the cultural impacts on TKR outcomes.
Vector Bundles and F Theory

To understand in detail duality between heterotic string and F theory compactifications, it is important to understand the construction of holomorphic G bundles over elliptic Calabi-Yau manifolds, for various groups G. In this paper, we develop techniques to describe these bundles, and make several detailed comparisons between the heterotic string and F theory.
HEAVY ION COLLISIONS AND BLACK HOLE DYNAMICS

Relativistic heavy ion collisions create a strongly coupled quark–gluon plasma. Some of the plasma's properties can be approximately understood in terms of a dual black hole. These properties include shear viscosity, thermalization time, and drag force on heavy quarks. They are hard to calculate from first principles in QCD. Extracting predictions about quark–gluon plasmas from dual black holes mostly involves solving Einstein's equations and classical string equations of motion. AdS/CFT provides a translation from gravitational calculations to gauge theory predictions. The gauge theory to which the predictions apply is $\mathcal{N} = 4$ super-Yang–Mills theory. QCD is different in many respects from super-Yang–Mills, but it seems that its high temperature properties are similar enough for us to make some meaningful comparisons.
Sound and Vibration Produced by an Airfoil Tip in a Turbulent Boundary Layer Flow with an Elastic End Wall

*† The sound and vibration produced by a finite membrane in proximity to an airfoil tip immersed in a turbulent flow was investigated. Specifically, an experiment was conducted in which a flat plate airfoil was placed in a turbulent flow such that the tip of the airfoil was close to a very thin circular membrane in an anechoic wind tunnel. The wall pressure spectra, structural vibratory response of the membrane and radiated sound pressure were measured with and without the airfoil. The presence of the airfoil caused a substantial change in the magnitude and phase of the wall pressure, and the vibration amplitudes of the membrane were found to be generally larger. The radiated sound was found to be 1-2 dB larger with the airfoil over the frequency range in which the unsteady lift from the leading edge affected the wall pressure spectra.
Linearized error analysis for an accelerator and application to the APS injector synchrotron

This paper presents a tolerance budget for accelerators dictated by the linear transverse dynamics of particle motion. The linearized equations satisfied by the particle motion when errors in the lattice are present are given along with the solution to these equations. The forms of these errors giving rise to the linearized equation are stated. These results are used to derive a tolerance budget for the Advanced Photon Source (APS) injector synchrotron.
Microplasma Field Effect Transistors

Micro plasma devices (MPD) with power gains are of interest in applications involving operations in the presence of ionizing radiations, in propulsion, in control, amplification of high power electromagnetic waves, and in metamaterials for energy management. Here, we review and discuss MPDs with an emphasis on new architectures that have evolved during the past seven years. Devices with programmable impact ionization rates and programmable boundaries are developed to control the plasma ignition voltage and current to achieve power gain. Plasma devices with 1–10 μm gaps are shown to operate in the sub-Paschen regime in atmospheric pressures where ion-assisted field emission results in a breakdown voltage that linearly depends on the gap distance in contrast to the exponential dependence dictated by the Paschen curve. Small gap devices offer higher operation frequencies at low operation voltages with applications in metamaterial skins for energy management and in harsh environment inside nuclear reactors and in space. In addition to analog plasma devices, logic gates, digital circuits, and distributed amplifiers are also discussed.
Android Malware Detection with Weak Ground Truth Data.

For Android malware detection, precise ground truth is a rare commodity. As security knowledge evolves, what may be considered ground truth at one moment in time may change, and apps once considered benign turn out to be malicious. The inevitable noise in data labels poses a challenge to creating effective machine learning models. Our work is focused on approaches for learning classifiers for Android malware detection in a manner that is methodologically sound with regard to the uncertain and ever-changing ground truth in the problem space. We leverage the fact that although data labels are unavoidably noisy, a malware label is much more precise than a benign label. While you can be confident that an app is malicious, you can never be certain that a benign app is really benign or just an undetected malware. Based on this insight, we leverage a modified Logistic Regression classifier that allows us to learn from only positive and unlabeled data, without making any assumptions about benign labels. We find Label Regularized Logistic Regression to perform well for noisy app datasets, as well as datasets where there is a limited amount of positive labeled data, both of which are representative of real-world situations.
The effects of elite public colleges on primary and secondary schooling markets in India

Abstract We present the first estimates of the effects of higher education investments on lower levels of schooling. Using the roll-out of elite public colleges in India, we show that investments in higher education increased educational attainment among school-age children. Private schools entered districts with new elite public colleges, and students switched from public to private schools. In addition, elite public colleges crowded in investments in electricity, roads, and water services. We find suggestive evidence that public investments in infrastructure may have reduced setup costs for private schools, and consequently, travel costs for school-going children.
Spoofing the Limit Order Book: An Agent-Based Model

We present an agent-based model of manipulating prices in financial markets through spoofing: submitting spurious orders to mislead traders who observe the order book. Built around the standard limit-order mechanism, our model captures a complex market environment with combined private and common values, the latter represented by noisy observations upon a dynamic fundamental time series. We consider background agents following two types of trading strategies: zero intelligence (ZI) that ignores the order book and heuristic belief learning (HBL) that exploits the order book to predict price outcomes. By employing an empirical game-theoretic analysis to derive approximate strategic equilibria, we demonstrate the effectiveness of HBL and the usefulness of order book information in a range of non-spoofing environments. We further show that a market with HBL traders is spoofable, in that a spoofer can qualitatively manipulate prices towards its desired direction. After re-equilibrating games with spoofing, we find spoofing generally hurts market surplus and decreases the proportion of HBL. However, HBL's persistence in most environments with spoofing indicates a consistently spoofable market. Our model provides a way to quantify the effect of spoofing on trading behavior and efficiency, and thus measures the profitability and cost of an important form of market manipulation.
Effects of graphite surface roughness on bypass flow computations for an HTGR

Abstract Bypass flow in a prismatic high temperature gas reactor (HTGR) occurs between graphite blocks as they sit side by side in the core. Bypass flow is not intentionally designed to occur in the reactor, but is present because of tolerances in manufacture, imperfect installation and expansion and shrinkage of the blocks from heating and irradiation. It is desired to increase the knowledge of the effects of such flow; it has been suggested that it may be as much as 20% of the total helium coolant flow [INL Report 2007, INL/EXT-07-13289]. Computational fluid dynamic (CFD) simulations can provide estimates of the scale and impacts of bypass flow. Previous CFD calculations have examined the effects of bypass gap width, level and distribution of heat generation and effects of shrinkage. The present contribution examines the effects of graphite surface roughness on the bypass flow for different relative roughness factors for three gap widths. Such calculations should be validated using specific bypass flow measurements. While such experiments are currently underway for the specific reference prismatic HTGR design for the next generation nuclear plant (NGNP) program of the U.S. Dept. of Energy, the data are not yet available. To enhance confidence in the present calculations, wall shear stress and heat transfer results for several turbulence models and their associated wall treatments are first compared for steady flow in a single tube that is representative of a coolant channel in the prismatic HTGR core. The results are compared to published correlations for wall shear stress and Nusselt number in turbulent pipe flow. Turbulence models that perform well are then used to make steady bypass flow calculations in a symmetric one-twelfth sector of a prismatic block that includes bypass flow. The comparison of shear stress and Nusselt number results with published correlations constitutes a partial validation of the CFD model. Results indicate that increasing surface roughness increases the maximum fuel and helium temperatures as do increases in gap width. However, maximum coolant temperature variation due to increased gap width is not changed by surface roughness.
The LDB1 Complex Co-opts CTCF for Erythroid Lineage-Specific Long-Range Enhancer Interactions

Lineage-specific transcription factors are critical for long-range enhancer interactions, but direct or indirect contributions of architectural proteins such as CCCTC-binding factor (CTCF) to enhancer function remain less clear. The LDB1 complex mediates enhancer-gene interactions at the β-globin locus through LDB1 self-interaction. We find that an LDB1-bound enhancer upstream of carbonic anhydrase 2 (Car2) activates its expression by interacting directly with CTCF at the gene promoter. Both LDB1 and CTCF are required for enhancer-Car2 looping, and the domain of LDB1 contacted by CTCF is necessary to rescue Car2 transcription in LDB1-deficient cells. Genome-wide studies and CRISPR/Cas9 genome editing indicate that LDB1-CTCF enhancer looping underlies activation of a substantial fraction of erythroid genes. Our results provide a mechanism by which long-range interactions of architectural protein CTCF can be tailored to achieve a tissue-restricted pattern of chromatin loops and gene expression.
Error Estimation for Determination of Unknown Coefficients in Parabolic Equations

Abstract We analyze a direct numerical method for the parameter identification problem of the one-dimensional parabolic equation. The method is based on a "Space Marching" idea while we use the hyperbolic perturbation to stabilize the computation. Using the "Space Marching" technique, the parameter identification problem can be solved without any iterative procedure. An error estimate is obtained in the energy norm.