cssi/SciSciGPT-SciSciNet huggingface dataset:
Trends in innovation activities in manufacturing industries across development echelons

This empirical paper explores trends in innovation activities measured by a countries’ total patent application submission intensity relative to its population, and by analyzing U.S. granted patents data for cohorts of developed countries and developing countries. In addition to tabular and graphical analyses, I use a baseline regression model and a variant model thereof to assess the relative influence of a set of aggregate variables on innovation activities in eight manufacturing industries across two cohorts of countries (developed and developing) where each cohort contains eight individual countries. Eight industries included in this study are: Chemical, Petroleum, electrical and electronics equipment, machinery, pharmaceutical, plastic, computer, and textile. The cohort of developed countries includes Australia, Canada, Czech Republic, France, Italy, Poland, Switzerland, and the United States. The cohort of developing countries includes Brazil, China, India, Malaysia, Mexico, Russia, South Africa, and Turkey. Per regression results, ethnic diversity is a statistically significant positive determinant of innovation for all industry aggregate patent count for both high income and developing countries. Also, per capita electricity usage, R&D expenditure as percent of GDP, and percent of population with internet access are three positive factors of innovation irrespective of industrial subsectors and position of a country in the development echelon. Interestingly, impact of ICT-services export is statistically significant and innovation boosting in developing countries in the cohort relative to countries in the cohort of developed countries. It also appears that trade openness served as a stronger stimulant of innovation activities for developing countries’ but not as much for the cohort of developed or high-income countries. This paper attempts to extend the literature on cross-country comparison of innovation activities by using two measures of innovation activities across developed and developing countries, and by analyzing both aggregate and sector-level data for eight manufacturing industries both graphically and utilizing panel regression models.
An infinite dimensional model for a single server priority queue

We consider a Markovian single server queue in which customers are preemptively scheduled by exogenously assigned priority levels. The novelty in our model is that the priority levels are randomly assigned from a continuous probability measure rather than a discrete one. Because the priority levels are drawn from a continuum, the queue is modeled by a measure-valued stochastic process. We analyze the steady state behavior of this process and provide several results. We derive a measure that describes the average distribution of customer priority levels in the system; we provide a formula for the expected sojourn time of a customer as a function of his priority level; and we provide a formula for the expected waiting time of a customer as a function of his priority level. We interpret these quantitative results and give a qualitative understanding of how the priority levels affect individual customers as well as how they affect the system as a whole. The theoretical analysis is verified by simulation. We also discuss some directions of future work.
A compressive multi-kernel method for privacy-preserving machine learning

As the analytic tools become more powerful, and more data are generated on a daily basis, the issue of data privacy arises. This leads to the study of the design of privacy-preserving machine learning algorithms. Given two objectives, namely, utility maximization and privacy-loss minimization, this work is based on two previously non-intersecting regimes — Compressive Privacy and multi-kernel method. Compressive Privacy is a privacy framework that employs utility-preserving lossy-encoding scheme to protect the privacy of the data, while multi-kernel method is a kernel-based machine learning regime that explores the idea of using multiple kernels for building better predictors. In relation to the neural-network architecture, multi-kernel method can be described as a two-hidden-layered network with its width proportional to the number of kernels. The compressive multi-kernel method proposed consists of two stages — the compression stage and the multi-kernel stage. The compression stage follows the Compressive Privacy paradigm to provide the desired privacy protection. Each kernel matrix is compressed with a lossy projection matrix derived from the Discriminant Component Analysis (DCA). The multikernel stage uses the signal-to-noise ratio (SNR) score of each kernel to non-uniformly combine multiple compressive kernels. The proposed method is evaluated on two mobile-sensing datasets — MHEALTH and HAR — where activity recognition is defined as utility and person identification is defined as privacy. The results show that the compression regime is successful in privacy preservation as the privacy classification accuracies are almost at the random-guess level in all experiments. On the other hand, the novel SNR-based multi-kernel shows utility classification accuracy improvement upon the state-of-the-art in both datasets. These results indicate a promising direction for research in privacy-preserving machine learning.
TouchTerrain: A simple web-tool for creating 3D-printable topographic models

Abstract An open-source web-application, TouchTerrain, was developed to simplify the production of 3D-printable terrain models. Direct Digital Manufacturing (DDM) using 3D Printers can change how geoscientists, students, and stakeholders interact with 3D data, with the potential to improve geoscience communication and environmental literacy. No other manufacturing technology can convert digital data into tangible objects quickly at relatively low cost; however, the expertise necessary to produce a 3D-printed terrain model can be a substantial burden: knowledge of geographical information systems, computer aided design (CAD) software, and 3D printers may all be required. Furthermore, printing models larger than the build volume of a 3D printer can pose further technical hurdles. The TouchTerrain web-application simplifies DDM for elevation data by generating digital 3D models customized for a specific 3D printer's capabilities. The only required user input is the selection of a region-of-interest using the provided web-application with a Google Maps-style interface. Publically available digital elevation data is processed via the Google Earth Engine API. To allow the manufacture of 3D terrain models larger than a 3D printer's build volume the selected area can be split into multiple tiles without third-party software. This application significantly reduces the time and effort required for a non-expert like an educator to obtain 3D terrain models for use in class. The web application is deployed at http://touchterrain.geol.iastate.edu , while source code and installation instructions for a server and a stand-alone version are available at Github: https://github.com/ChHarding/TouchTerrain_for_CAGEO .
The complete structure of the small-subunit processome

The 3.8-A cryo-EM structure of the Saccharomyces cerevisiae small-subunit processome in a state that precedes pre-rRNA cleavage at site A1 provides an essentially complete near-atomic model of this assembly. The small-subunit processome represents the earliest stable precursor of the eukaryotic small ribosomal subunit. Here we present the cryo-EM structure of the Saccharomyces cerevisiae small-subunit processome at an overall resolution of 3.8 A, which provides an essentially complete near-atomic model of this assembly. In this nucleolar superstructure, 51 ribosome-assembly factors and two RNAs encapsulate the 18S rRNA precursor and 15 ribosomal proteins in a state that precedes pre-rRNA cleavage at site A1. Extended flexible proteins are employed to connect distant sites in this particle. Molecular mimicry and steric hindrance, as well as protein- and RNA-mediated RNA remodeling, are used in a concerted fashion to prevent the premature formation of the central pseudoknot and its surrounding elements within the small ribosomal subunit.
Theory and simulation of anode spots in low pressure plasmas

When electrodes are biased above the plasma potential, electrons accelerated through the associated electron sheath can dramatically increase the ionization rate of neutrals near the electrode surface. It has previously been observed that if the ionization rate is great enough, a double layer separates a luminous high-potential plasma attached to the electrode surface (called an anode spot or fireball) from the bulk plasma. Here, results of the first 2D particle-in-cell simulations of anode spot formation are presented along with a theoretical model describing the formation process. It is found that ionization leads to the build-up of an ion-rich layer adjacent to the electrode, forming a narrow potential well near the electrode surface that traps electrons born from ionization. It is shown that anode spot onset occurs when a quasineutral region is established in the potential well and the density in this region becomes large enough to violate the steady-state Langmuir condition, which is a balance betwee...
An Integrative multi-lineage model of variation in leukopoiesis and acute myelogenous leukemia

Acute myelogenous leukemia (AML) progresses uniquely in each patient. However, patients are typically treated with the same types of chemotherapy, despite biological differences that lead to differential responses to treatment. Here we present a multi-lineage multi-compartment model of the hematopoietic system that captures patient-to-patient variation in both the concentration and rates of change of hematopoietic cell populations. By constraining the model against clinical hematopoietic cell recovery data derived from patients who have received induction chemotherapy, we identified trends for parameters that must be met by the model; for example, the mitosis rates and the probability of self-renewal of progenitor cells are inversely related. Within the data-consistent models, we found 22,796 parameter sets that meet chemotherapy response criteria. Simulations of these parameter sets display diverse dynamics in the cell populations. To identify large trends in these model outputs, we clustered the simulated cell population dynamics using k-means clustering and identified thirteen ‘representative patient’ dynamics. In each of these patient clusters, we simulated AML and found that clusters with the greatest mitotic capacity experience clinical cancer outcomes more likely to lead to shorter survival times. Conversely, other parameters, including lower death rates or mobilization rates, did not correlate with survival times. Using the multi-lineage model of hematopoiesis, we have identified several key features that determine leukocyte homeostasis, including self-renewal probabilities and mitosis rates, but not mobilization rates. Other influential parameters that regulate AML model behavior are responses to cytokines/growth factors produced in peripheral blood that target the probability of self-renewal of neutrophil progenitors. Finally, our model predicts that the mitosis rate of cancer is the most predictive parameter for survival time, followed closely by parameters that affect the self-renewal of cancer stem cells; most current therapies target mitosis rate, but based on our results, we propose that additional therapeutic targeting of self-renewal of cancer stem cells will lead to even higher survival rates.
Segmentation Based On Second-Order Statistics

The gray level or intensity distribution of an image is frequently inadequate to select a good threshold for image segmentation. Considerable improvement can be achieved by a histogram transformation based on second-order gray-level statistics. This paper describes an approach using the co-occurrence matrix. Results are shown for target extraction in forward looking infrared (FLIR) images.
Surface currents associated with external kink modes in tokamak plasmas during a major disruption

The surface current on the plasma-vacuum interface during a disruption event involving kink instability can play an important role in driving current into the vacuum vessel. However, there have been disagreements over the nature or even the sign of the surface current in recent theoretical calculations based on idealized step-function background plasma profiles. We revisit such calculations by replacing step-function profiles with more realistic profiles characterized by a strong but finite gradient along the radial direction. It is shown that the resulting surface current is no longer a delta-function current density, but a finite and smooth current density profile with an internal structure, concentrated within the region with a strong plasma pressure gradient. Moreover, this current density profile has peaks of both signs, unlike the delta-function case with a sign opposite to, or the same as the plasma current. We show analytically and numerically that such current density can be separated into two pa...
Application of a simplified theory of ELF propagation to a simplified worldwide model of the ionosphere

The approximate theory of ELF propagation in the Earth-ionosphere transmission line described by Booker (1980) is applied to a simplified worldwide model of the D and E regions, and of the Earth's magnetic field. At 1000 Hz by day, reflection is primarily from the gradient on the underside of the D region. At 300 Hz by day, reflection is primarily from the D region at low latitudes, but it is from the E region at high latitudes. Below 100 Hz by day, reflection is primarily from the gradient on the underside of the E region at all latitudes. By night, reflection from the gradient on the topside of the E region is important. There is then a resonant frequency (∼ 300 Hz) at which the optical thickness of the E region for the whistler mode is half a wavelength. At the Schumann resonant frequency in the Earth-ionosphere cavity (∼ 8 Hz) the nocturnal E region is almost completely transparent for the whistler mode and is semi-transparent for the Alfven mode. Reflection then takes place from the F region. ELF propagation in the Earth-ionosphere transmission line by night is quite dependent on the magnitude of the drop in ionization density between the E and F regions. Nocturnal propagation at ELF therefore depends significantly on an ionospheric feature whose magnitude and variability are not well understood. A comparison is made with results based on the computer program of the United States Naval Ocean Systems Center.
Current Status of Endovascular Training for Cardiothoracic Surgery Residents in the United States

Background Endovascular interventions for cardiovascular pathology are becoming increasingly relevant to cardiothoracic surgery. This study assessed the perceived prevalence and efficacy of endovascular skills training and identified differences among training paradigms. Methods Trainee responses to questions in the 2016 In-Service Training Examination survey regarding endovascular training were analyzed based on the four different cardiothoracic surgery training pathways: traditional 2- and 3-year thoracic, integrated 6-year, and combined 4+3 general and thoracic residency programs. Results The duration of endovascular training was substantially different among programs, at a median of 17 weeks for integrated 6-year, 8.5 weeks for 3-year, 6 weeks for 4+3, and 4 weeks for 2-year residency ( p p p Conclusions Considerable heterogeneity exists in endovascular training among cardiothoracic surgery training pathways, with a significant number of residents having minimal to no exposure to these emerging techniques. These findings highlight the need for a standardized curriculum to improve endovascular exposure and training.
Photos, tweets, and trails: Are social media proxies for urban trail use?

Decision makers need information on the use of, and demand for, public recreation and transportation facilities. Innovations in monitoring technologies and diffusion of social media enable new approaches to estimation of demand. We assess the feasibility of using geo-tagged photographs uploaded to the image-sharing website Flickr and tweets from Twitter as proxy measures for urban trail use. We summarize geo-tagged Flickr uploads and tweets along 80 one-mile segments of the multiuse trail network in Minneapolis, Minnesota, and correlate results with previously published estimates of annual average daily trail traffic derived from infrared trail monitors. Although heat maps of Flickr images and tweets show some similarities with maps of variation in trail traffic, the correlation between photographs and trail traffic is moderately weak (0.43), and there is no meaningful statistical correlation between tweets and trail traffic. Use of a simple log-log bivariate regression to estimate trail traffic from photographs results in relatively high error. The predictor variables included in published demand models for the same trails explain roughly the same amount of variation in photo-derived use, but some of the neighborhood socio-demographic and built-environment independent variables have different effects. Taken together, these findings show that both Flickr images and tweets have limitations as proxies for demand for urban trails, and that neither can be used to develop valid, reliable estimates of trail use. These results differ from previously published results that indicate social media may be useful in assessing relative demand for recreational destinations. This difference may be because urban trails are used for multiple purposes, including routine commuting and shopping, and that trail users are less inclined to use social media on trips for these purposes.
iPSC-Derived Vascular Cell Spheroids as Building Blocks for Scaffold-Free Biofabrication.

Recently a protocol was established to obtain large quantities of human induced pluripotent stem cells (iPSC)-derived endothelial progenitors, called endothelial colony forming cells (ECFC), and of candidate smooth-muscle forming cells (SMFC). Here, we tested their suitability for assembling in spheroids, and in larger 3D cell constructs. iPSC-derived ECFC and SMFC were labeled with tdTomato and eGFP, respectively. Spheroids were formed in ultra-low adhesive wells, and their dynamic proprieties were studied by time-lapse microscopy, or by confocal microscopy. Spheroids were also tested for fusion ability either in the wells, or assembled on the Regenova 3D bioprinter by lacing them in stainless steel micro-needles (the 'Kenzan' method). We found that both ECFC and SMFC formed spheroids in about 24 hr. Fluorescence monitoring indicated a continuous compaction of ECFC spheroids, but which stabilized in those prepared from SMFC. In mixed spheroids, the cell distribution changed continuously, with ECFC relocating to the core, and showing pre-vascular organization. All spheroids had ability of in-well fusion, but only those containing SMFC were robust enough to sustain assembling in tubular structures. In these constructs we found a layered distribution of alpha smooth muscle actin-positive cells and extracellular matrix deposition. In conclusion, iPSC-derived vascular cell spheroids represent a promising new cellular material for scaffold-free biofabrication.
How Much Does Money Matter?: “Buying” Votes in Japan, 1967-1990

Japanese elections are notorious for the money that flows between contributors, politicians, and voters. To date, however, nobody has estimated statistically the impact of this money on electoral o...
Planar graphs, negative weight edges, shortest paths, and near linear time

In this paper, we present an O(n log3 n) time algorithm for finding shortest paths in an n-node planar graph with real weights. This can be compared to the best previous strongly polynomial time algorithm developed by Lipton, Rose, and Tarjan in 1978 which runs in O(n3/2) time, and the best polynomial time algorithm developed by Henzinger, Klein, Subramanian, and Rao in 1994 which runs in O(n 4/3) time. We also present significantly improved data structures for reporting distances between pairs of nodes and algorithms for updating the data structures when edge weights change.
Chiral anomalous dispersion

LANL/LDRD Program; U.S. Department of Energy [DE-SC0011090, DE-FG02-00ER41132, DE-FG02-04ER41338]; RFBR [17-02-01108]
A spectroscopic study of the environments of gravitational lens galaxies

We present the first results from our spectroscopic survey of strong gravitational lens environments. Six of the eight lens galaxies in our sample belong to a poor group of galaxies, three of which are newly discovered here (those associated with BRI 0952-0115, MG 1654+1346, and B2114+022). For the three previously known groups (surrounding MG 0751+2716, PG 1115+080, and B1422+231), we more than double the number of group members. The group velocity dispersions range from 110 to 470 km s-1. The higher velocity dispersions of the richer groups (MG 0751, PG 1115, and B1422) are consistent with those of nearby X-ray-luminous groups; the lower velocity dispersions of the other groups are more typical of dynamically younger groups. The lens galaxy is the brightest member in fewer than half of the groups. The brightest group galaxy is an early-type galaxy that, at least for the poorer groups, lies outside the group centroid and on an orbit indistinguishable from other group members. In at least three cases, MG 0751, PG 1115, and B1422, the group environment significantly affects the lens potential. These happen to be the quadruply imaged lenses in our sample, suggesting a connection between image configuration and environment. Finally, we assess the importance of line-of-sight mass structures, showing that, in principle, the lens potential may be affected by structures lying at a wide range of spatial and redshift offsets from the lens. We quantify the real line-of-sight effects, finding that four of the eight systems have substantial interloping structures and that at least one of those (behind MG 0751) significantly affects the lens potential.
Thermal Inactivation of Salmonella in High-Fat Rendering Meat Products

Thermal inactivation of Salmonella is a critical component of the calculated thermal process to ensure the safety of cooked human and animal products. However, lethality performance standards for meat processing by-products that may harbor Salmonella have not been properly set under the actual conditions of rendering processes. The goal of this study was to evaluate the thermal inactivation parameters for Salmonella in high-fat beef trimmings as a model system for animal food products treated under simulated "worst-case scenario" commercial rendering conditions. Ground high-fat beef trimmings (50% fat) were artificially inoculated with a 108 CFU/g Salmonella cocktail containing human outbreak strains including the highly thermotolerant serotype Salmonella Senftenberg. The meat samples were packaged and immersed in either water or silicon oil at predetermined temperatures ranging from 60 to 121°C (from 140 to 250°F). D-values of Salmonella at each temperature were calculated from the negative inverse slope of the log CFU per gram versus time plot. The z-values were determined from the negative inverse slope of the log D versus temperature plot. The D-values in thermal death curves for low-fat (20%) content materials (between 60 and 95°C) were 2.175, 0.658, 0.237, 1.563, 0.356, 0.284, 0.264, and 0.201 min, whereas materials with 50% fat (between 100 to 121°C) were 0.277, 0.286, 0.159, 0.143, 0.137, and 0.087 min. The z-values for low- and high-temperature schedules were 43.7 and 42.9°C, respectively. Thermal lethality data for Salmonella inactivation in high-fat rendering raw materials will help animal food processors design adequate thermal processing schedules and support critical control points to ensure the safety of final beef-based rendered products.
Augmenting Markets with Mechanisms

We explain how the common practice of size-discovery trade detracts from overall financial market efficiency. At each of a series of size-discovery sessions, traders report their desired trades, generating allocations of the asset and cash that rely on the most recent exchange price. Traders can thus mitigate exchange price impacts by waiting for size-discovery sessions. This waiting causes socially costly delays in the rebalancing of asset positions across traders. As the frequency of size-discovery sessions is increased, exchange market depth is further lowered by the traders’ reduced incentive to bid aggressively on the exchange, further delaying the rebalancing of positions, and more than offsetting the gains from trade that occur at each of the size-discovery sessions.
Endogenous magnetic reconnection and associated high energy plasma processes

Abstract An endogenous reconnection process involves a driving factor that lays inside the layer where a drastic change of magnetic field topology occurs. A process of this kind is shown to take place when an electron temperature gradient is present in a magnetically confined plasma and the evolving electron temperature fluctuations are anisotropic. The width of the reconnecting layer remains significant even when large macroscopic distances are considered. In view of the fact that there are plasmas in the Universe with considerable electron thermal energy contents this feature can be relied upon in order to produce generation or conversion of magnetic energy, high energy particle populations and momentum and angular momentum transport.
TEM Study of Defects in Laterally Overgrown GaN Layers

Transmission electron microscopy was applied to study defects in laterally overgrown GaN layers, with initial growth on Al2O3 substrates followed by further growth over SiO2 masks. Dislocations found in the overgrown areas show changes in line direction. Most dislocations propagate along c-planes. In the overgrown material planar defects (faulted loops) are present on c-planes and their presence is most probably related to segregation of excess point defects and impurities present in this material. They appear to be initiated by the fast lateral growth. Some dislocations with screw orientation become helical resulting from climb motion.Formation of voids and also a high dislocation density was observed at the boundaries where two overgrowing fronts meet. Tilt and twist components were observed for these boundaries that were different for different overgrown strips grown in the same crystallographic direction suggesting that the GaN subgrain orientations on the two sides of a SiO2 mask are responsible for the final tilt and twist value.
Quantifying the economic and grid reliability impacts of improved wind power forecasting

Wind power forecasting is an important tool in power system operations to address variability and uncertainty. Accurately doing so is important to reducing the occurrence and length of curtailment, enhancing market efficiency, and improving the operational reliability of the bulk power system. This research quantifies the value of wind power forecasting improvements in the IEEE 118-bus test system as modified to emulate the generation mixes of Midcontinent, California, and New England independent system operator balancing authority areas. To measure the economic value, a commercially available production cost modeling tool was used to simulate the multi-timescale unit commitment (UC) and economic dispatch process for calculating the cost savings and curtailment reductions. To measure the reliability improvements, an in-house tool, FESTIV, was used to calculate the system's area control error and the North American Electric Reliability Corporation Control Performance Standard 2. The approach allowed scientific reproducibility of results and cross-validation of the tools. A total of 270 scenarios were evaluated to accommodate the variation of three factors: generation mix, wind penetration level, and wind forecasting improvements. The modified IEEE 118-bus systems utilized 1 year of data at multiple timescales, including the day-ahead UC, 4-hour-ahead UC, and 5-min real-time dispatch. The value of improved wind power forecasting was found to be strongly tied to the network size, market structure, and the penetration level of wind energy. The simulation results demonstrate that wind power forecasting brings clear benefits to power system operations.
A “Tug of War” Maintains a Dynamic Protein–Membrane Complex: Molecular Dynamics Simulations of C-Raf RBD-CRD Bound to K-Ras4B at an Anionic Membrane

Association of Raf kinase with activated Ras triggers downstream signaling cascades toward regulating transcription in the cells’ nucleus. Dysregulation of Ras–Raf signaling stimulates cancers. We investigate the C-Raf RBD and CRD regions when bound to oncogenic K-Ras4B at the membrane. All-atom molecular dynamics simulations suggest that the membrane plays an integral role in regulating the configurational ensemble of the complex. Remarkably, the complex samples a few states dynamically, reflecting a competition between C-Raf CRD- and K-Ras4B- membrane interactions. This competition arises because the interaction between the RBD and K-Ras is strong while the linker between the RBD and CRD is short. Such a mechanism maintains a modest binding for the overall complex at the membrane and is expected to facilitate fast signaling processes. Competition of protein–membrane contacts is likely a common mechanism for other multiprotein complexes, if not multidomain proteins at membranes.
Double Pituitary Adenomas Are Most Commonly Associated with GH- and ACTH-Secreting Tumors: Systematic Review of the Literature

Double adenomas in the pituitary gland are a rare occurrence. The ability to cure a hormone-producing adenoma with surgery is dependent on the ability to identify and completely remove the correct adenoma. The relative frequency of each subtype of hormone-secreting adenomas confirmed with magnetic resonance image (MRI), surgery and immunohistochemistry is not defined. Following PRISMA guidelines, we performed a systematic review of PubMed Central, Google Scholar, Scopus Database, Cochrane database and Science Research, using the key-words: “double pituitary adenomas”, “multiple pituitary adenomas” and only papers where multiple or truly separate double pituitary adenomas were identified pre-surgically by MRI and/or confirmed by pathology/immunohistochemistry staining were included. We reviewed papers from 1975 to 2016 and found 17 cases with two pituitary adenomas and 1 with three pituitary adenomas. The ages ranged from 22 to 67 years old, and there were twelve females and five males. Immunohistochemical staining showed that the most common double pituitary adenomas were growth hormone (GH)- followed by adrenocorticotropic (ACTH)-secreting. Double pituitary adenomas are rare but most commonly found with GH- or ACTH-producing tumors. It is critical to remove all identified possible adenomas to achieve biochemical cure and clinicians should have heightened sensitivity in patients with acromegaly or Cushing’s Disease.
PREDICTING PLANETS IN KEPLER MULTI-PLANET SYSTEMS

We investigate whether any multi-planet systems among Kepler candidates (2011 February release) can harbor additional terrestrial-mass planets or smaller bodies. We apply the packed planetary systems hypothesis that suggests all planetary systems are filled to capacity, and use a Hill stability criterion to identify eight two-planet systems with significant gaps between the innermost and outermost planets. For each of these systems, we perform long-term numerical integrations of 107?years to investigate the stability of 4000-8000 test particles injected into the gaps. We map out stability regions in orbital parameter space, and therefore quantify the ranges of semimajor axes and eccentricities of stable particles. Strong mean-motion resonances can add additional regions of stability in otherwise unstable parameter space. We derive simple expressions for the extent of the stability regions, which is related to quantities such as the dynamical spacing ?, the separation between two planets in units of their mutual Hill radii. Our results suggest that planets with separation ? < 10 are unlikely to host extensive stability regions, and that about 95 out of a total of 115 two-planet systems in the Kepler sample may have sizeable stability regions. We predict that Kepler candidate systems including KOI 433, KOI 72/Kepler-10, KOI 555, KOI 1596, KOI 904, KOI 223, KOI 1590, and KOI 139 can harbor additional planets or low-mass bodies between the inner and outer detected planets. These predicted planets may be detected by future observations.
Real-World Implementation of Infant Behavioral Sleep Interventions: Results of a Parental Survey.

Objective To describe parental practices implementing behavioral sleep intervention (BSI) outside a clinical setting. Study design Parents (n = 652), recruited through a Facebook group designed as a peer support group for parents using BSI, completed an online survey about their experience using BSI with their infant or toddler. Results On average, parents implemented BSI when their infant was 5.6 (±2.77) months. Parents most often used modified (49.5%) or unmodified extinction (34.9%), with fewer using a parental presence approach (15.6%). Regardless of BSI type, more parents endorsed “a great deal of stress” during the first night (42.2%) than 1 week later (5.2%). The duration of infant crying was typically greatest the first night (reported by 45%; M = 43 minutes) and was significantly reduced after 1 week (M = 8.54 minutes). Successful implementation of BSI on the first attempt was reported by 83%, with a median and mode of 7 days until completion (79% by 2 weeks). Regardless of BSI type, after intervention parents reported their infant had less difficulty falling asleep, fewer night awakenings, and were more likely to sleep in their room and/or in their own crib/bed. Conclusions The majority of parents report successfully implementing BSI, with significantly reduced infant crying by the end of 1 week and success within 2 weeks. Few differences were found between behavioral approaches.
Squared Away: Veterans on the Board of Directors

Given the vital importance of the board of directors, firms seek to staff their boards with competent individuals who bring valuable skills and expertise to assist a firm. Especially following crises, firms should be interested in appointing directors who possess not only superior decision-making skills under pressure, but who also may be inclined to behave more ethically to prevent future breaches of stakeholder trust. Applying a social identity perspective, we argue that directors with U.S. military experience are decidedly valuable to firms because of their human capital. Using a sample of 144 U.S. based, publicly-traded firms that experienced a Securities Class Action Lawsuit between 2002 and 2012, we test hypotheses predicting that following crises, firms are more likely to appoint directors with military experience. Our findings extend the social identity view of an individual from the self or how individuals view themselves to include how others may view them.
Coral: Clear and Customizable Visualization of Human Kinome Data

Summary Protein kinases represent one of the largest gene families in eukaryotes and play roles in a wide range of cell signaling processes and human diseases. Current tools for visualizing kinase data in the context of the human kinome superfamily are limited to encoding data through the addition of nodes to a low-resolution image of the kinome tree. We present Coral, a user-friendly interactive web application for visualizing both quantitative and qualitative data. Unlike previous tools, Coral can encode data in three features (node color, node size, and branch color), allows three modes of kinome visualization (the traditional kinome tree as well as radial and dynamic force networks), and generates high-resolution scalable vector graphics files suitable for publication without the need for refinement using graphics editing software. Due to its user-friendly, interactive, and highly customizable design, Coral is broadly applicable to high-throughput studies of the human kinome. The source code and web application are available at github.com/dphansti/CORAL and phanstiel-lab.med.unc.edu/Coral , respectively.
Foreign Fighter Returnees: An Indefinite Threat?

How long does it typically take a returned foreign fighter to launch a domestic terror attack? The issue of returnees, and appropriate national and international responses to potential threats, has...
Adaptive Detection of Structured Signals in Low-Rank Interference

In this paper, we consider the problem of detecting the presence (or absence) of an unknown but structured signal from the space-time outputs of an array under strong, non-white interference. Our motivation is the detection of a communication signal in jamming, where often the training portion is known but the data portion is not. We assume that the measurements are corrupted by additive white Gaussian noise of unknown variance and a few strong interferers, whose number, powers, and array responses are unknown. We also assume that the desired signal's array response is unknown. To address the detection problem, we propose several GLRT-based detection schemes that employ a probabilistic signal model and use the EM algorithm for likelihood maximization. Numerical experiments are presented to assess the performance of the proposed schemes.
Cognitive System to Achieve Human-Level Accuracy in Automated Assignment of Helpdesk Email Tickets

Ticket assignment/dispatch is a crucial part of service delivery business with lot of scope for automation and optimization. In this paper, we present an end-to-end automated helpdesk email ticket assignment system, which is also offered as a service. The objective of the system is to determine the nature of the problem mentioned in an incoming email ticket and then automatically dispatch it to an appropriate resolver group (or team) for resolution.
On universal Lie nilpotent associative algebras

Abstract We study the quotient Q i ( A ) of a free algebra A by the ideal M i ( A ) generated by the ith commutator of any elements. In particular, we completely describe such quotient for i = 4 (for i ⩽ 3 this was done previously by Feigin and Shoikhet). We also study properties of the ideals M i ( A ) , e.g. when M i ( A ) M j ( A ) is contained in M i + j − 1 ( A ) (by a result of Gupta and Levin, it is always contained in M i + j − 2 ( A ) ).
Demographics and interest rates in Asia

Abstract Demographic developments have been regarded as one important cause of the long-term movement in global interest rates. This paper provides empirical evidence of the relationship between demographics and interest rates over a wide sample of advanced and emerging market economies. It also finds that capital account openness limits the direct sensitivity of a country's interest rates to its own demographics. The results suggest that future demographic developments will continue to apply downward pressure on the interest rates in Asia which foresees a rapid aging.
Continuous bulk and interface description of topological insulators

We analyze the topological properties of systems of Dirac equations in the presence of heterogeneities to model transport in topological insulators. The topology is described by means of indices of Fredholm operators. We describe bulk and interface topological invariants first for two-dimensional materials, which find practical applications, and then in arbitrary dimensions. In the two-dimensional setting, we relate the interface invariant to a physical observable describing asymmetric current along the interface.We analyze the topological properties of systems of Dirac equations in the presence of heterogeneities to model transport in topological insulators. The topology is described by means of indices of Fredholm operators. We describe bulk and interface topological invariants first for two-dimensional materials, which find practical applications, and then in arbitrary dimensions. In the two-dimensional setting, we relate the interface invariant to a physical observable describing asymmetric current along the interface.
Compositional Stochastic Average Gradient for Machine Learning and Related Applications

Many machine learning, and statistical inference problems require minimization of a composition of expected value functions (CEVF). Of particular interest is the finite-sum versions of such compositional optimization problems (FS-CEVF). Compositional stochastic variance reduced gradient (C-SVRG) methods that combine stochastic compositional gradient descent (SCGD) and stochastic variance reduced gradient descent (SVRG) methods are the state-of-the-art methods for FS-CEVF problems. We introduce compositional stochastic average gradient descent (C-SAG) a novel extension of the stochastic average gradient method (SAG) to minimize composition of finite-sum functions. C-SAG, like SAG, estimates gradient by incorporating memory of previous gradient information. We present theoretical analyses of C-SAG which show that C-SAG, like C-SVRG, achieves a linear convergence rate for strongly convex objective function; However, C-CAG achieves lower oracle query complexity per iteration than C-SVRG. Finally, we present results of experiments showing that C-SAG converges substantially faster than full gradient (FG), as well as C-SVRG.
Next generation MicroRNA sequencing to identify coronary artery disease patients at risk of recurrent myocardial infarction.

Abstract Background and aims Variation in micro-RNA (miRNA) levels in blood has been associated with alterations of physiological functions of the cardiovascular system. Circulating miRNA have the potential to become reliable biomarkers for risk stratification and early detection of cardiovascular events. Recurrent thrombotic events in patients with established coronary artery disease (CAD) demonstrate the need for personalized approaches to secondary prevention, especially in light of recent novel treatment approaches. Methods In a single center cohort study, whole blood samples were collected from 437 subjects undergoing cardiac catheterization, who were followed for recurrent cardiovascular events during a mean follow up of 1.5 years. We selected a case cohort (n = 22) with recurrent thrombotic events on standard medical therapy (stent thrombosis (n = 6) or spontaneous myocardial infarction (MI) (n = 16)) and a matched cohort with CAD, but uneventful clinical follow up (n = 26), as well as a control group with cardiovascular risk factors, but without angiographic CAD (n = 24). We performed complete miRNA next generation sequencing of RNA extracted from whole blood samples (including leukocytes and platelets). Results A differential pattern of miRNA expression was found among controls, CAD patients with no events, and CAD patients with recurrent events. MiRNA previously associated with MI, CAD, endothelial function, vascular smooth muscle cells, platelets, angiogenesis, heart failure, cardiac hypertrophy, arrhythmia, and stroke were found variably expressed in our case-control cohorts. Seventy miRNA (FDR Conclusions MiRNA next generation sequencing demonstrates altered fingerprint profile of whole blood miRNA expression among subjects with subsequent recurrent thrombotic events on standard medical therapy (‘non-responders’), as compared to subjects with no recurrent cardiovascular events. MiRNA profiling may be useful to identify high risk subjects and provide additional insights into disease mechanisms not currently attenuated with standard medical therapy used in CAD treatment.
Toward Open-Ended Fraternal Transitions in Individuality.

The emergence of new replicating entities from the union of simpler entities characterizes some of the most profound events in natural evolutionary history. Such transitions in individuality are es...
Probabilistic Clustering using Maximal Matrix Norm Couplings

In this paper, we present a local information theoretic approach to explicitly learn probabilistic clustering of a discrete random variable. Our formulation yields a convex maximization problem for which it is NP-hard to find the global optimum. In order to algorithmically solve this optimization problem, we propose two relaxations that are solved via gradient ascent and alternating maximization. Experiments on the MSR Sentence Completion Challenge, MovieLens 100K, and Reuters21578 datasets demonstrate that our approach is competitive with existing techniques and worthy of further investigation.
C2TCP: A Flexible Cellular TCP to Meet Stringent Delay Requirements

Since, current widely available network protocols/ systems are mainly throughput-oriented designs, meeting stringent delay requirements of new applications such as virtual reality and vehicle-to-vehicle communications on cellular network requires new network protocol/system designs. C2TCP is an effort toward that new design direction. C2TCP is inspired by in-network active queue management designs such as RED and CoDel and motivated by lack of a flexible end-to-end approach which can adapt itself to different applications’ QoS requirements without modifying any network devices. It copes with unique challenges in cellular networks for achieving ultra-low latency (including highly variable channels, deep per-user buffers, self-inflicted queuing delays, and radio uplink/downlink scheduling delays) and intends to satisfy stringent delay requirements of different applications while maximizing the throughput. C2TCP works on top of classic throughput-oriented TCP and accommodates various target delays without requiring any channel prediction, network state profiling, or complicated rate adjustment mechanisms. We have evaluated C2TCP in both real-world environment and extensive trace-based emulations and compared its performance with different TCP variants and state-of-the-art schemes including PCC-Vivace, Google’s BBR, Verus, Sprout, TCP Westwood, and Cubic. Results show that C2TCP outperforms all these schemes and achieves lower average delay, jitter, and 95th percentile delay for packets.
STAFFING AND SERVICE AVAILABILITY IN ASSISTED LIVING: THE IMPORTANCE OF NURSE DELEGATION POLICIES

This study examined the relationships among assisted living (AL) staffing, the availability of 26 services, and state delegation regulations (whether nurses can delegate care to other staff), using data from 245 AL settings from eight U.S. states (CA, FL, IL, KS, NC, NH, NJ, OR). We found significantly more services available in AL settings in delegation states than non-delegation states (19.7 vs 18.1), and more medication technicians handling prescribed and PRN (as needed) medications (p<.001). In two-way comparisons of nurse staffing categories (none, LPNs only, RNs only, LPNs and RNs), AL communities with no nurses offered the lowest number of services and those with RNs only offered a significantly lower number of services than those with LPNs only. This session will illustrate how AL staffing and service availability relate to statewide nurse delegation practices, and discuss the significance of this work to understanding the overall quality of care in AL.
Deep Learning in Downlink Coordinated Multipoint in New Radio Heterogeneous Networks

We propose a method to improve the performance of the downlink coordinated multipoint (DL CoMP) in heterogeneous fifth generation new radio (NR) networks. The standards-compliant method is based on the construction of a surrogate CoMP trigger function using deep learning. The cooperating set is a single-tier of sub-6 GHz heterogeneous base stations operating in the frequency division duplex mode (i.e., no channel reciprocity). This surrogate function enhances the downlink user throughput distribution through online learning of non-linear interactions of features and lower bias learning models. In simulation, the proposed method outperforms industry standards in a realistic and scalable heterogeneous cellular environment.