cssi/SciSciGPT-SciSciNet huggingface dataset:
Structure Building Predicts Grades in College Psychology and Biology

Summary Knowing what skills underlie college success can allow students, teachers, and universities to identify and to help at-risk students. One skill that may underlie success across a variety of subject areas is structure building, the ability to create mental representations of narratives (Gernsbacher, Varner, & Faust, 1990). We tested if individual differences in structure-building ability predicted success in two college classes: introductory to psychology and introductory biology. In both cases, structure building predicted success. This effect was robust, with structure building explaining variance in course grades even after accounting for high school GPA and SAT scores (in the psychology course) or a measure of domain knowledge (in the biology course). The results support the claim that structure building is an important individual difference, one that is associated with learning in different domains. Copyright © 2016 John Wiley & Sons, Ltd.
In-situ measurements of Saturn's dusty rings based on dust impact signals detected by Cassini RPWS

Abstract The Cassini Radio and Plasma Wave Science (RPWS) instrument can detect dust particles when voltage pulses induced by the dust impacts are observed in the wideband receiver. The size of the voltage pulse is proportional to the mass of the impacting dust particle. In this paper, we show RPWS measurements of dust particles in Saturn's dusty rings. The differential size distribution of the dust particles can be characterized as a power law dn/dr∝rμ, where μ ∼ − 4 and r is the particle radius. The observed particle radius ranged from 0.2 to 10 μm. The dust density profiles of the dusty rings are derived from the impact rates measured by the RPWS wideband receiver. The radial density profiles show peaks near Enceladus’ orbit and the G ring. The region around the G ring is found to be a very thin layer of dust particles with no observable vertical offset of the peak density from the ring plane. The vertical scale height of the E ring varies with the radial distance from Saturn with a local minimum at Enceladus’ orbit. The vertical density profiles of the E ring show dips at the equatorial plane near Enceladus’ orbit and vertical offsets of the peak locations away from Enceladus’ orbit. These observations are consistent with previous modeling studies and measurements by other instruments onboard Cassini.
Structure of (±)-(1R*,6S*)-1-benzyloxy-8,11,11-trimethyl-6-phenylthiobicyclo[5.3.1]undec-7-en-3-one

C28H34O2S, Mr = 434.64, triclinic, P1, a = 8.9868 (7), b = 11.2933 (11), c = 12.3497 (6) A, alpha = 80.937 (6), beta = 73.108 (5), gamma = 87.405 (7) degrees, V = 1184.32 (15) A3, Z = 2, Dx = 1.22 g cm-3, mu = 1.509 cm-1, Mo K alpha radiation, lambda = 0.7107 A, F(000) = 468, T = 298 K, R = 0.0583 for 6924 reflections [Fo greater than or equal to 4 sigma(Fo)]. The cyclooctane portion of the [5.3.1] ring system is in the boat-chair conformation while the cyclohexene portion assumes the boat conformation. The carbonyl group and the alkene group are nearly parallel in the molecule with a dihedral angle of 14.9 (1) degree between planes through the two groups. Ring strain appears to cause distortion in the alkene functionality. The bond length [C7-C8 1.343 (2) A] is long for an isolated C-C double bond. The torsion angles deviate between 3.7 (2) and 18.39 (14) degrees (absolute values) from ideality. This twist in the alkene group is reflected in the non-planarity of the group [max. deviation -0.177 (2) A for C9] and in the dihedral angle between the nearly planar portions (C6,C7,C8,C11 and C7,C8,C9,C16) which is 12.1 (1) degrees.
Nitrogenases—A Tale of Carbon Atom(s)

Named after its ability to catalyze the reduction of nitrogen to ammonia, nitrogenase has a surprising rapport with carbon-both through the interstitial carbide that resides in the central cavity of its cofactor and through its ability to catalyze the reductive carbon-carbon coupling of small carbon compounds into hydrocarbon products. Recently, a radical-SAM-dependent pathway was revealed for the insertion of carbide, which signifies a novel biosynthetic route to complex bridged metalloclusters. Moreover, a sulfur-displacement mechanism was proposed for the activation of carbon monoxide by nitrogenase, which suggests an essential role of the interstitial carbide in maintaining the stability while permitting a certain flexibility of the cofactor structure during substrate turnover.
A probabilistic proof of a binomial identity

We give an elementary probabilistic proof of a binomial identity. The proof is obtained by computing the probability of a certain event in two different ways, yielding two different expressions for...
Structural studies of TcO2 by neutron powder diffraction and first-principles calculations.

Crystalline technetium dioxide was prepared and for the first time its crystal structure determined by neutron powder diffraction. In addition, electronic structure calculations using density functional theory were performed to further elucidate the bonding mechanisms in TcO2. The crystal structure determined by Rietveld analysis with the NPD data is of a distorted rutile type, similar to that of MoO2; space group P21/c, a = 5.6891(1), b = 4.7546(1), c = 5.5195(1) A, and β = 121.453(1)°. The NPD analysis also establishes a new neutron scattering length of 6.00(3) fm for 99Tc. Our results clearly show metal−metal bonding between Tc pairs along the edge-sharing chains of TcO6 octahedra. The Tc−Tc bond was found to be 2.622(1) A from NPD profile analysis and 2.59 A from first-principles DFT calculations. The bond is somewhat longer than expected from earlier predictions, suggesting that the nature of the Tc−Tc interaction is weaker than anticipated for the Tc(IV) cation with three outer electrons. The NPD re...
Messenger RNA modifications: Form, distribution, and function

RNA contains more than 100 distinct modifications that promote the functions of stable noncoding RNAs in translation and splicing. Recent technical advances have revealed widespread and sparse modification of messenger RNAs with N(6)-methyladenosine (m(6)A), 5-methylcytosine (m(5)C), and pseudouridine (Ψ). Here we discuss the rapidly evolving understanding of the location, regulation, and function of these dynamic mRNA marks, collectively termed the epitranscriptome. We highlight differences among modifications and between species that could instruct ongoing efforts to understand how specific mRNA target sites are selected and how their modification is regulated. Diverse molecular consequences of individual m(6)A modifications are beginning to be revealed, but the effects of m(5)C and Ψ remain largely unknown. Future work linking molecular effects to organismal phenotypes will broaden our understanding of mRNA modifications as cell and developmental regulators.
Constrained Deep Transfer Feature Learning and Its Applications

Feature learning with deep models has achieved impressive results for both data representation and classification for various vision tasks. Deep feature learning, however, typically requires a large amount of training data, which may not be feasible for some application domains. Transfer learning can be one of the approaches to alleviate this problem by transferring data from data-rich source domain to data-scarce target domain. Existing transfer learning methods typically perform one-shot transfer learning and often ignore the specific properties that the transferred data must satisfy. To address these issues, we introduce a constrained deep transfer feature learning method to perform simultaneous transfer learning and feature learning by performing transfer learning in a progressively improving feature space iteratively in order to better narrow the gap between the target domain and the source domain for effective transfer of the data from source domain to target domain. Furthermore, we propose to exploit the target domain knowledge and incorporate such prior knowledge as constraint during transfer learning to ensure that the transferred data satisfies certain properties of the target domain. To demonstrate the effectiveness of the proposed constrained deep transfer feature learning method, we apply it to thermal feature learning for eye detection by transferring from the visible domain. We also applied the proposed method for cross-view facial expression recognition as a second application. The experimental results demonstrate the effectiveness of the proposed method for both applications.
Expertensysteme zur Software-Konfiguration

Expertensysteme sind Computerprogramme, die Expertenwissen uber ein Spezialgebiet in leicht verstandlicher Form zur Verfugung stellen. Haufig umfast Expertenwissen neben fundiertem Sach- und Faktenwissen auch personliches, manchmal vages, schwierig zu formulierendes, in langer Zeit erworbenes Erfahrungswissen. Der menschliche Experte — und somit auch das Expertensystem findet nicht nur die Losung fur ein Problem, sondern mus daruber hinaus wahrend des Losungsprozesses Erklarungen, Begrundungen und Teillosungen anbieten (Hayes-Roth et al. 1983). Hierbei ist es hilfreich, wenn das Wissen im Rechner symbolisch dargestellt wird.
The Cation–π Interaction in Small-Molecule Catalysis

Catalysis by small molecules (≤1000 Da, 10−9 m) that are capable of binding and activating substrates through attractive, noncovalent interactions has emerged as an important approach in organic and organometallic chemistry. While the canonical noncovalent interactions, including hydrogen bonding, ion pairing, and π stacking, have become mainstays of catalyst design, the cation–π interaction has been comparatively underutilized in this context since its discovery in the 1980s. However, like a hydrogen bond, the cation–π interaction exhibits a typical binding affinity of several kcal mol−1 with substantial directionality. These properties render it attractive as a design element for the development of small-molecule catalysts, and in recent years, the catalysis community has begun to take advantage of these features, drawing inspiration from pioneering research in molecular recognition and structural biology. This Review surveys the burgeoning application of the cation–π interaction in catalysis.
A Declarative Framework for Linking Entities

We introduce and develop a declarative framework for entity linking and, in particular, for entity resolution. As in some earlier approaches, our framework is based on a systematic use of constraints. However, the constraints we adopt are link-to-source constraints, unlike in earlier approaches where source-to-link constraints were used to dictate how to generate links. Our approach makes it possible to focus entirely on the intended properties of the outcome of entity linking, thus separating the constraints from any procedure of how to achieve that outcome. The core language consists of link-to-source constraints that specify the desired properties of a link relation in terms of source relations and built-in predicates such as similarity measures. A key feature of the link-to-source constraints is that they employ disjunction, which enables the declarative listing of all the reasons two entities should be linked. We also consider extensions of the core language that capture collective entity resolution by allowing interdependencies among the link relations. We identify a class of “good” solutions for entity-linking specifications, which we call maximum-value solutions and which capture the strength of a link by counting the reasons that justify it. We study natural algorithmic problems associated with these solutions, including the problem of enumerating the “good” solutions and the problem of finding the certain links, which are the links that appear in every “good” solution. We show that these problems are tractable for the core language but may become intractable once we allow interdependencies among the link relations. We also make some surprising connections between our declarative framework, which is deterministic, and probabilistic approaches such as ones based on Markov Logic Networks.
Computer-controlled radiochemical synthesis: A chemistry process control unit for the automated production of radiochemicals

Abstract A computer-controlled general purpose chemistry process control unit (CPCU) suitable for the automated production of radiochemicals has been developed. This valve-and-tubing synthesis system can be user programmed to accommodate a variety of chemical processes. In a practical demonstration of its utility, the CPCU has been configured and programmed to synthesize 2-deoxy-2-[ 18 F]fluoro- d -glucose (2-[ 18 F]FDG) using aqueous [ 18 F]fluoride ion. Using this instrument, the yield of 2-[ 18 F]FDG from [ 18 F]fluoride ion is 54.9% (± 11.2%, n = 125) corrected to EOB, after a synthesis time of 50–55 min. The average total activity produced (for runs of 5–10 μA) is 28.1 mCi/μA (± 5.03 m Ci/ μ A). Thus, the amount of 2-[ 18 F]FDG produced from a 10 μA for 1 h bombardment was 154.3 mCi (± 27.4 mCi). The unit has been similarly configured and programmed to synthesize 2-deoxy-2-[ 18 F]fluoro- d -mannose (48% EOB), 3-(2′-[ 18 F]fluoroethyl)spiperone (29% EOB), and [ 18 F]fluoroacetate (66% EOB) from aqueous [ 18 F]fluoride ion, and 2-[ 18 F]FDG from gaseous acetyl hypo[ 18 F]fluorite (20% EOB).
Extracting Geography from Trade Data

Abstract Understanding international trade is a fundamental problem in economics—one standard approach is via what is commonly called the “gravity equation”, which predicts the total amount of trade F i j between two countries i and j as F i j = G M i M j D i j , where G is a constant, M i , M j denote the “economic mass” (often simply the gross domestic product) and D i j is the “distance” between countries i and j . Here “distance” is a complex notion that includes geographical, historical, linguistic and sociological components. We take the inverse route and ask ourselves to what extent it is possible to reconstruct meaningful information about countries simply from knowing the bilateral trade volumes F i j : indeed, we show that a remarkable amount of geopolitical information can be extracted. The main ingredient is a spectral decomposition of the Graph Laplacian as a tool to perform nonlinear dimensionality reduction.
SUPERIOR CAPSULOTOMY: THE IDEAL APPROACH FOR THA – OPPOSES

Merriam Webster - ide•al adjective \ī-′dē(−ə)l, ′ī\: exactly right for a particular purpose, situation, or person Dictionary.com - 1: conceived as constituting a standard of perfection or excellence; 2: regarded as perfect of its kind; 3: existing only in the imagination; not real or actual Concepts: Tissue Preserving - anterior and posterior capsule maintained: YES; No dislocation; Minimal leg manipulation; Rapid Rehabilitation: YES; Half the average LOS at NE Baptist; Safe: YES; Fewer complications than standard approach; Transferable and Reproducible ???; Limited adoption; Optimally executed with navigation; Leg length assessment less accessible; Neck cut measured from GT; “Funny looking” impactors/reamers - different “feel”. IDEAL: For some… but not for most.
Synergistic Communication between CD4+ T Cells and Monocytes Impacts the Cytokine Environment

Physiological cytokine environments arise from factors produced by diverse cell types in coordinated concert. Understanding the contributions of each cell type in the context of cell-cell communication is important for effectively designing disease modifying interventions. Here, we present multi-plexed measurement of 48 cytokines from a coculture system of primary human CD4+ T cells and monocytes across a spectrum of stimuli and for a range of relative T cell/monocyte compositions, coupled with corresponding measurements from PBMCs and plasma from the same donors. Computational analysis of the resulting data-sets elucidated communication-independent and communication-dependent contributions, including both positive and negative synergies. We find that cytokines in cell supernatants were uncorrelated to those found in plasma. Additionally, as an example of positive synergy, production levels of CXCR3 cytokines IP-10 and MIG, depend non-linearly on both IFNγ and TNFα levels in cross-talk between T cells and monocytes. Overall, this work demonstrates that communication between cell types can significantly impact the consequent cytokine environment, emphasizing the value of mixed cell population studies.
Male labor supply and generational fiscal policy

Abstract Between 1948 and 2000, hours worked by men in the United States fell by twenty percent. Using a life cycle model of labor supply with intensive and extensive margins, we assess how much of this decline can be accounted for by changes in tax and transfer policies. We use policy measures from the generational accounting literature, capturing the lifetime fiscal burdens faced by each male birth-year cohort. Changes in age demographics and fiscal policy account for 44% of the decline in hours worked. Policy alone explains approximately a quarter of the decline, both in the aggregate and across age groups.
Affinity purification of bacterial outer membrane vesicles (OMVs) utilizing a His-tag mutant

To facilitate the rapid purification of bacterial outer membrane vesicles (OMVs), we developed two plasmid constructs that utilize a truncated, transmembrane protein to present an exterior histidine repeat sequence. We chose OmpA, a highly abundant porin protein, as the protein scaffold and utilized the lac promoter to allow for inducible control of the epitope-presenting construct. OMVs containing mutant OmpA-His6 were purified directly from Escherichia coli culture media on an immobilized metal affinity chromatography (IMAC) Ni-NTA resin. This enabling technology can be combined with other molecular tools directed at OMV packaging to facilitate the separation of modified/cargo-loaded OMV from their wt counterparts. In addition to numerous applications in the pharmaceutical and environmental remediation industries, this technology can be utilized to enhance basic research capabilities in the area of elucidating endogenous OMV function.
Interplay between Social Influence and Network Centrality: A Comparative Study on Shapley Centrality and Single-Node-Influence Centrality

We study network centrality based on dynamic influence propagation models in social networks. To illustrate our integrated mathematical-algorithmic approach for understanding the fundamental interplay between dynamic influence processes and static network structures, we focus on two basic centrality measures: (a) Single Node Influence (SNI) centrality, which measures each node's significance by its influence spread; and (b) Shapley Centrality, which uses the Shapley value of the influence spread function --- formulated based on a fundamental cooperative-game-theoretical concept --- to measure the significance of nodes. We present a comprehensive comparative study of these two centrality measures. Mathematically, we present axiomatic characterizations, which precisely capture the essence of these two centrality measures and their fundamental differences. Algorithmically, we provide scalable algorithms for approximating them for a large family of social-influence instances. Empirically, we demonstrate their similarity and differences in a number of real-world social networks, as well as the efficiency of our scalable algorithms. Our results shed light on their applicability: SNI centrality is suitable for assessing individual influence in isolation while Shapley centrality assesses individuals' performance in group influence settings.
The Role of Cognitive Processes, Foundational Math Skill, and Calculation Accuracy and Fluency in Word-Problem Solving versus Prealgebraic Knowledge.

The purpose of this study was to examine child-level pathways in development of prealgebraic knowledge versus word-problem solving, while evaluating the contribution of calculation accuracy and fluency as mediators of foundational skills/processes. Children (n = 962; mean 7.60 years) were assessed on general cognitive processes and early calculation, word-problem, and number knowledge at start of Grade 2; calculation accuracy and calculation fluency at end of Grade 2; and prealgebraic knowledge and word-problem solving at end of Grade 4. Important similarities in pathways were identified, but path analysis also indicated that language comprehension is more critical for later word-problem solving than prealgebraic knowledge. We conclude that pathways in development of these forms of 4th-grade mathematics performance are more alike than different, but demonstrate the need to fine-tune instruction for strands of the mathematics curriculum in ways that address individual students' foundational mathematics skills or cognitive processes. (PsycINFO Database Record
Metamorphic In0.52Al0.48As/In0.53Ga0.47As HEMTs on GaAs substrate with fT over 200 GHz

MBE-grown metamorphic In/sub 0.52/Al/sub 0.48/As/In/sub 0.53/Ga/sub 0.47/As HEMTs on GaAs substrates are presented. A linearly-graded InAlGaAs buffer layer is employed for strain relaxation. A mobility of 9520 cm/sup 2//Vs and a sheet density of 2.85/spl times/10/sup 12/ cm/sup -2/ are achieved at room temperature. Devices with gate lengths ranging from 0.18 to 1.0 /spl mu/m have been fabricated. Large drain currents and extrinsic transconductances with values up to 900 mA/mm and 1.1 mS/mm, respectively, are reported. For a 0.18 /spl mu/m gate length device, a unity current gain cutoff frequency (f/sub T/) of 204 GHz is obtained. To the authors' knowledge, this is the highest f/sub T/ to date for a metamorphic HEMT on GaAs.
Data-driven Estimation of Origin-Destination Demand and User Cost Functions for the Optimization of Transportation Networks

Abstract In earlier work (Zhang et al., 2016) we used actual traffic data from the Eastern Massachusetts transportation network in the form of spatial average speeds and road segment flow capacities in order to estimate Origin-Destination (OD) flow demand matrices for the network. Based on a Traffic Assignment Problem (TAP) formulation (termed “forward problem”), in this paper we use a scheme similar to our earlier work to estimate initial OD demand matrices and then propose a new inverse problem formulation in order to estimate user cost functions. This new formulation allows us to efficiently overcome numerical difficulties that limited our prior work to relatively small subnetworks and, assuming the cost functions are available, to adjust the values of the OD demands accordingly so that the flow observations are as close as possible to the solutions of the forward problem. Finally, using the same actual traffic data from the Eastern Massachusetts transportation network, we quantify the Price of Anarchy (PoA) for a much larger network than that in Zhang et al. (2016).
3D printed dancing humanoid robot “Buddy” for homecare

This paper describes a 3D printed humanoid robot that can perform dancing and demonstrate human-like facial expressions to expand humanoid robotics in entertainment and at the same time to have an assistive role for children and elderly people. The humanoid is small and has an expressive face that is in a comfort zone for a child or an older person. It can maneuver in a day care or home care environment using its wheeled base. This paper discusses on the capabilities of the robot to carry and handle small loads like pills, common measurement tools such as pressure and temperature measurement units. The paper also discusses the use of IP camera for color identification and an Arduino based audio system to synchronize music with dance movements of the robot.
Synthesis of low-moment CrVTiAl: A potential room temperature spin filter

The efficient production of spin-polarized currents at room temperature is fundamental to the advancement of spintronics. Spin-filter materials—semiconductors with unequal band gaps for each spin channel—can generate spin-polarized current without the need for spin-polarized contacts. In addition, a spin-filter material with zero magnetic moment would have the advantage of not producing strong fringing fields that would interfere with neighboring electronic components and limit the volume density of devices. The quaternary Heusler compound CrVTiAl has been predicted to be a zero-moment spin-filter material with a Curie temperature in excess of 1000 K. In this work, CrVTiAl has been synthesized with a lattice constant of a = 6.15 A. Magnetization measurements reveal an exceptionally low moment of μ = 2.3 × 10−3 μB/f.u. at a field of μ0H = 2 T that is independent of temperature between T = 10 K and 400 K, consistent with the predicted zero-moment ferrimagnetism. Transport measurements reveal a combination o...
Electrohydrodynamics of viscous drops in strong electric fields: numerical simulations

Weakly conducting dielectric liquid drops suspended in another dielectric liquid and subject to an applied uniform electric field exhibit a wide range of dynamical behaviours contingent on field strength and material properties. These phenomena are best described by the Melcher–Taylor leaky dielectric model, which hypothesizes charge accumulation on the drop–fluid interface and prescribes a balance between charge relaxation, the jump in ohmic currents from the bulk and charge convection by the interfacial fluid flow. Most previous numerical simulations based on this model have either neglected interfacial charge convection or restricted themselves to axisymmetric drops. In this work, we develop a three-dimensional boundary element method for the complete leaky dielectric model to systematically study the deformation and dynamics of liquid drops in electric fields. The inclusion of charge convection in our simulations permits us to investigate drops in the Quincke regime, in which experiments have demonstrated a symmetry-breaking bifurcation leading to steady electrorotation. Our simulation results show excellent agreement with existing experimental data and small-deformation theories.
Stochastic Geometry-Based Comparison of Secrecy Enhancement Techniques in D2D Networks

This letter presents a performance comparison of two popular secrecy enhancement techniques in wireless networks: 1) creating guard zones by restricting transmissions of legitimate transmitters whenever any eavesdropper is detected in their vicinity, and 2) adding artificial noise to the confidential messages to make it difficult for the eavesdroppers to decode them. Focusing on a noise-limited regime, we use tools from stochastic geometry to derive the secrecy outage probability at the eavesdroppers as well as the coverage probability at the legitimate users for both these techniques. Using these results, we derive a threshold on the density of the eavesdroppers below which no secrecy enhancing technique is required to ensure a target secrecy outage probability. For eavesdropper densities above this threshold, we concretely characterize the regimes in which each technique outperforms the other. Our results demonstrate that guard zone technique is better when the distances between the transmitters and their legitimate receivers are higher than a certain threshold.
A computational approach to extinction events in chemical reaction networks with discrete state spaces.

Abstract Recent work of Johnston et al. has produced sufficient conditions on the structure of a chemical reaction network which guarantee that the corresponding discrete state space system exhibits an extinction event. The conditions consist of a series of systems of equalities and inequalities on the edges of a modified reaction network called a domination-expanded reaction network. In this paper, we present a computational implementation of these conditions written in Python and apply the program on examples drawn from the biochemical literature. We also run the program on 458 models from the European Bioinformatics Institute’s BioModels Database and report our results.
Map-guided hyperspectral image superpixel segmentation using proportion maps

A map-guided superpixel segmentation method for hyperspectral imagery is developed and introduced. The proposed approach develops a hyperspectral version of the SLIC superpixel algorithm, leverages map information to guide segmentation, and incorporates the semi-supervised Partial Membership Latent Dirichlet Allocation (sPM-LDA) to obtain a final segmentation. The proposed method is applied to two hyperspectral data sets and quantitative cluster validity metrics indicate that the proposed approach outperforms existing hyperspectral superpixel segmentation methods.
Longitudinal structures in Mars’ upper atmosphere as observed by MAVEN/NGIMS

Here we report the first comprehensive study of longitudinal structures in Mars' neutral upper atmosphere associated with atmospheric tides in composition, density and temperature using the Mars Atmosphere and Volatile Evolution Mission/Neutral Gas Ion Mass Spectrometer observations during 2015. These are in situ measurements of number densities of atmospheric species (including CO2, Ar, N2, and CO) in the altitude range from 120 to 200 km above the areoid (corresponding to a total density range from ~108–1011 cm−3), providing a data set that is larger than all previous measurements of these waves combined. These observations span from ±70° latitude and cover a wide range of local times and solar longitudes (Ls), allowing for the study of longitudinal structures under various conditions. Furthermore, the data in May and November 2015 are at similar latitudes and local times but different Ls (~340° in May, close to northern spring equinox, and 70° in November, close to northern summer solstice and aphelion), ideal for studying the seasonal effects of tides. Our analysis shows that in each month the Ar density varies with longitude having a large wave structure. It is dominated by wave 2 and 3, accounting for 8–16% of the change of the mean density. Comparison shows that the longitudinal structures at a constant CO2 density level have different amplitudes at different seasons, although their patterns are similar. The temperature structure has a phase difference from the density variation, indicating the dissipation of tides in this altitude region. The longitudinal structure is seen in all species, including major and minor species, consistent with the tidal signatures.
Network Backboning with Noisy Data

Networks are powerful instruments to study complex phenomena, but they become hard to analyze in data that contain noise. Network backbones provide a tool to extract the latent structure from noisy networks by pruning non-salient edges. We describe a new approach to extract such backbones. We assume that edge weights are drawn from a binomial distribution, and estimate the error-variance in edge weights using a Bayesian framework. Our approach uses a more realistic null model for the edge weight creation process than prior work. In particular, it simultaneously considers the propensity of nodes to send and receive connections, whereas previous approaches only considered nodes as emitters of edges. We test our model with real world networks of different types (flows, stocks, cooccurrences, directed, undirected) and show that our Noise-Corrected approach returns backbones that outperform other approaches on a number of criteria. Our approach is scalable, able to deal with networks with millions of edges.
Monetary policy regime switches and macroeconomic dynamics

This article considers the determinacy and distributional consequences of regime switching in monetary policy. Although switching in the inflation target does not affect determinacy, switches in the inflation response can cause indeterminacy. Satisfying the Taylor principle period by period is neither necessary nor sufficient for determinacy when inflation responses switch; indeterminacy can arise if monetary policy responds too aggressively to inflation in the active regime. Inflation target switches primarily impact the level of inflation, whereas inflation response switches primarily impact the volatility. Expecting an inflation target switch has minor effects on volatility, whereas expecting an inflation response switch raises volatility more substantially.
Motion induced coherence degradation in passive systems

The problem of correlation degradation introduced as a result of the track and motional instabilities in a transiting target is addressed. The target is assumed to consist of a narrow-band signal source which is received at two remotely located sensors. The outputs are processed through a correlation-type detector. The correlator output will, in general, suffer a degradation which is nondeterministic and statistical in character. Two important aspects of are, the mean target track relative to the source-sensor geometry, and the motional instabilities relative to the mean target track. The former creates an absolute upper bound on the useful coherence integration time which can be employed in the processor. The latter will depend on the spectral characteristics of the motional instabilities as well as the variance of the target course and speed. Results of the expected processor degradation are presented in both functional and graphical form for convenience in interpretation and data abstraction. An optimum integration time is derived from the standpoint of optimizing the processor gain for signal detection in an incoherent signal background. It is concluded that target motion can be the most serious deterrent to the use of coherent signal processors over exceptionally long integration intervals.
Why and How the Supreme Court Should Have Decided O’Bannon v. NCAA

Despite requests by both parties, the U.S. Supreme Court refused to grant a writ of certiorari in O’Bannon v. NCAA, the first federal appellate court decision holding that an NCAA student-athlete eligibility rule violates Section 1 of the Sherman Act. The Ninth Circuit ruled that NCAA rules prohibiting intercollegiate athletes from receiving any revenue from videogames and telecasts incorporating their names, images, or likenesses unreasonably restrain economic competition among its member universities in the college education market in which these athletes purchase higher education services and sell their athletic services, which violates federal antitrust law. Circuit court rulings conflict regarding whether student-athlete eligibility rules are commercial restraints subject to the Sherman Act, and lower courts have inconsistently interpreted and applied NCAA v. Board of Regents of University of Oklahoma, the Supreme Court’s only intercollegiate athletics antitrust law precedent. The Supreme Court’s ref...
Monitoring and Employee Shirking: Evidence From MLB Umpires:

Neoclassical principal–agent theory predicts stricter monitoring should reduce employee shirking; however, recent analyses indicate social aspects of principal–agent relationships may result in “cr...
Testing the Accuracy of Data-driven MHD Simulations of Active Region Evolution

Models for the evolution of the solar coronal magnetic field are vital for understanding solar activity, yet the best measurements of the magnetic field lie at the photosphere, necessitating the development of coronal models which are "data-driven" at the photosphere. We present an investigation to determine the feasibility and accuracy of such methods. Our validation framework uses a simulation of active region (AR) formation, modeling the emergence of magnetic flux from the convection zone to the corona, as a ground-truth data set, to supply both the photospheric information and to perform the validation of the data-driven method. We focus our investigation on how the accuracy of the data-driven model depends on the temporal frequency of the driving data. The Helioseismic and Magnetic Imager on NASA's Solar Dynamics Observatory produces full-disk vector magnetic field measurements at a 12-minute cadence. Using our framework we show that ARs that emerge over 25 hr can be modeled by the data-driving method with only ~1% error in the free magnetic energy, assuming the photospheric information is specified every 12 minutes. However, for rapidly evolving features, under-sampling of the dynamics at this cadence leads to a strobe effect, generating large electric currents and incorrect coronal morphology and energies. We derive a sampling condition for the driving cadence based on the evolution of these small-scale features, and show that higher-cadence driving can lead to acceptable errors. Future work will investigate the source of errors associated with deriving plasma variables from the photospheric magnetograms as well as other sources of errors, such as reduced resolution, instrument bias, and noise.
Detecting election Fraud from irregularities in vote-share distributions

I develop a novel method to detect election fraud from irregular patterns in the distribution of vote-shares. I build on a widely discussed observation that in some elections where fraud allegations abound, suspiciously many polling stations return coarse vote-shares (e.g., 0.50, 0.60, 0.75) for the ruling party, which seems highly implausible in large electorates. Using analytical results and simulations, I show that sheer frequency of such coarse vote-shares is entirely plausible due to simple numeric laws and does not by itself constitute evidence of fraud. To avoid false positive errors in fraud detection, I propose a resampled kernel density method (RKD) to measure whether the coarse vote-shares occur too frequently to raise a statistically qualified suspicion of fraud. I illustrate the method on election data from Russia and Canada as well as simulated data. A software package is provided for an easy implementation of the method.
On Fujita’s log spectrum conjecture

We prove Fujita’s log spectrum conjecture. It follows from the ACC of a suitable set of pseudo-effective thresholds.
Multiple disjunction for spaces of Poincaré embeddings

We obtain multirelative connectivity statements about spaces of Poincare embeddings, as precursors to analogous statements about spaces of smooth embeddings. The latter are the key to convergence results in the functor calculus approach to spaces of embeddings.
Rab7 GTPase controls lipid metabolic signaling in myeloid-derived suppressor cells.

// Xinchun Ding 1 , Wenjing Zhang 1 , Ting Zhao 1 , Cong Yan 1, 2 , Hong Du 1, 2 1 Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA 2 IU Simon Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA Correspondence to: Hong Du, email: hongdu@iupui.edu Cong Yan, email: coyan@iupui.edu Keywords: Rab7 GTPase, myeloid-derived suppressor cells, lipid metabolism, tumor growth Received: November 18, 2016 Accepted: March 09, 2017 Published: March 16, 2017 ABSTRACT Lysosomal acid lipase (LAL) is a critical neutral lipid metabolic enzyme that regulates metabolic reprogramming in myeloid-derived suppressor cells (MDSCs) through over-activation of mammalian target of rapamycin (mTOR). Affymetrix GeneChip microarray analysis of MDSCs from LAL deficient mouse ( lal –/– ) revealed upregulation of Rab7 GTPase protein, which belongs to a superfamily of small-molecular-weight GTPase known to regulate intracellular membrane trafficking from early to late endosomes and lysosomes. Here, the physical protein-protein interaction between Rab7 GTPase and mTOR has been detected by co-immunoprecipitation in the cell extract of wild type HD1A and lal –/– MDSC-like HD1B myeloid cell lines. The GST pull down assay using the recombinant GST-Rab7 GTPase fusion protein showed that Rab7 GTPase interacts with the mTOR N-terminal heat repeat domain. Rab7 GTPase siRNA knocking down reversed the altered lysosome/mTOR distribution and expression levels in HD1B cells. Rab7 GTPase siRNA knocking down in isolated bone marrow lal –/– MDSCs or HD1B cells not only reduced over-activation of mTOR and its downstream effector S6, but also decreased glucose consumption, decreased ROS over-production, and increased healthy mitochondria by membrane potential measurement. Inhibition of Rab7 GTPase led to reduced lal –/– MDSCs differentiation from bone marrow Lin – progenitor cells, reduced lal –/– MDSCs trans-endothelial migration, and reversed lal –/– MDSCs suppression of T cell proliferation. Furthermore, inhibition of Rab7 GTPase reduced lal –/– MDSCs ability to stimulate tumor cell proliferation in vitro , tumor growth in vivo , and tumor invasion. Together, these results showed that Rab7 GTPase is critically involved in MDSCs homeostasis and pathogenic functions.
Pairwise Stochastic Bounded Confidence Opinion Dynamics: Heavy Tails and Stability

Unlike traditional graph-based linear dynamics, where agents exchange opinions with their neighbors in a static social graph regardless of their differences in opinions, the bounded confidence opinion dynamics models exchange between agents with similar opinions. We generalize the bounded confidence opinion dynamics model by incorporating pairwise stochastic interactions, probabilistic influencing based on opinion differences and the self or endogenous evolutions of the agent opinions, which are represented by random processes. The opinion exchanges resulting from influencing have pairwise contraction effects, whereas endogenous motions have an expansive effect, for instance, of a diffusive nature. We analytically characterize the conditions under which this stochastic dynamics is stable in an appropriate sense. In the diffusive case, the presence of heavy tailed influence functions with a Pareto exponent of 2 is critical for stability (for a pair of agents an influence function maps opinion differences to probabilities of influence). Moreover, this model sheds light on dynamics that combine aspects of graph-based and bounded confidence dynamics.
The Galaxy's veil of excited hydrogen

Many of the baryons in our Galaxy probably lie outside the well-known disk and bulge components. Despite a wealth of evidence for the presence of some gas in galactic halos—including absorption line systems in the spectra of quasars, high-velocity neutral hydrogen clouds in our Galaxy halo, line-emitting ionized hydrogen originating from galactic winds in nearby starburst galaxies and the X-ray coronas surrounding the most massive galaxies—accounting for the gas in the halo of any galaxy has been observationally challenging, primarily because of the low density in these expansive regions. The most sensitive measurements come from detecting absorption due to the intervening gas in the spectra of distant objects, such as quasars or distant halo stars, but these have typically been limited to a few lines of sight to sufficiently bright objects. Extensive spectroscopic surveys of millions of objects provide an alternative approach to the problem. Here, we present evidence for a newly discovered, widely distributed, neutral, excited hydrogen component of the Galaxy’s halo. It is observed as the slight (0.779 ± 0.006%) absorption of flux near the rest wavelength of Hα in the combined spectra of hundreds of thousands of galaxy spectra and is ubiquitous in high-latitude lines of sight. This observation provides an avenue to tracing, both spatially and kinematically, the majority of the gas in the halo of our Galaxy. The stacking of nearly three-quarters of a million spectra has unearthed a previously unknown component of the Galactic halo: a widely distributed, neutral, excited hydrogen layer that could harbour a sizeable proportion of the Milky Way’s baryons.
Flattening a non-degenerate CR singular point of real codimension two

This paper continues the previous studies in two papers of Huang–Yin [HY16,HY17] on the flattening problem of a CR singular point of real codimension two sitting in a submanifold in $${{\mathbb {C}}^{n+1}}$$ with n + 1 ≥ 3, whose CR points are non-minimal. Partially based on the geometric approach initiated in [HY16] and a formal theory approach used in [HY17], we are able to provide more or less a complete solution to the flattening problem for a non-degenerate CR singular point along the lines of such studies. As an application, we provide a solution to the local complex Plateau problem and obtain the analyticity of the local hull of holomorphy near a real analytic definite CR singular point in a general setting.
LOW INCIDENCE OF POST-OPERATIVE COMPLICATIONS WITH NAVIGATED TOTAL KNEE ARTHROPLASTY

Abstract A number of postoperative complications of navigated total knee arthroplasty have been discussed in the literature, including tracker pin site infection and fracture. In this paper we discuss the low postoperative complication rate in a series of 3100 navigated total knee arthroplasties and the overall complication rate in a systematic analysis of the literature. Methods 3100 consecutive patients with navigated total knee arthroplasties from 2001 to 2016 were retrospectively evaluated for complications specific to navigation. We discuss the two cases of postoperative fracture through tracker pin sites that we experienced and compare this systematically to the literature. Results Postoperatively, our 3100 patient cohort experienced a total of two fractures through pin sites for an incidence of 0.065%. One was a distal femoral fracture which was treated surgically, and the other was a proximal tibial fracture treated nonoperatively. Due to our incorporation of the tracker sites within our operative incision, there were no identifiable pin site infections which others have noted. Our 0.065% fracture rate compares favorably with the 0.16% rate of fracture published in the literature. We had no separate pin site infections in comparison to the 0.47% incidence of separate pin site infection reported by those who use seperate percutaneous incisions for tracker placement. Conclusion There is an extremely low risk of perioperative complications due to the instrumentation used in navigated total knee arthroplasty when utilizing the Stryker Navigation System and 4.0 mm anchoring pins placed within the surgical incision. Our experience has demonstrated that careful placement of the bicortical anchoring pin is important.
The Structural Fate of Individual Multicomponent Metal-Oxide Nanoparticles in Polymer Nanoreactors

Multicomponent nanoparticles can be synthesized with either homogeneous or phase-segregated architectures depending on the synthesis conditions and elements incorporated. To understand the parameters that determine their structural fate, multicomponent metal-oxide nanoparticles consisting of combinations of Co, Ni, and Cu were synthesized by using scanning probe block copolymer lithography and characterized using correlated electron microscopy. These studies revealed that the miscibility, ratio of the metallic components, and the synthesis temperature determine the crystal structure and architecture of the nanoparticles. A Co-Ni-O system forms a rock salt structure largely owing to the miscibility of CoO and NiO, while Cu-Ni-O, which has large miscibility gaps, forms either homogeneous oxides, heterojunctions, or alloys depending on the annealing temperature and composition. Moreover, a higher-ordered structure, Co-Ni-Cu-O, was found to follow the behavior of lower ordered systems.