bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics of entangled polymer chains with nanoparticle attachment under large amplitude oscillatory shear
Authors: Hershey Christopher , Jayaraman Krishnamurthy 
Published: November 2018

ABSTRACTThis paper presents a nonlinear viscoelastic model for polymer nanocomposites and the computed model response to large amplitude oscillatory shear flow. The model predicts the stress in a mixture of entangled polymer chains, with different convective constraint release (CCR) rates for free chains and nanoparticle‐attached chains, through an averaging scheme which is consistent with double reptation in the Marrucci–Ianniruberto constitutive equation. The nonlinear response of the mixture is evaluated both numerically in terms of Q and by an asymptotic analysis in terms of four frequency dependent parameters of medium amplitude oscillatory shear (MAOS) as well as the intrinsic nonlinearity parameter Q0. In the case of free polymer chains alone, the MAOS signatures are comparable to those of the Giesekus model with the notable difference of a minimum in the elastic parameter [e1] at De >1. The viscous nonlinear parameters of the mixture model depart significantly from those of the free chains, especially in mixtures where the CCR parameter for attached chains is larger than that for the free chains: [v1] has a prominent minimum and [v3] has a prominent maximum near De = 2/c, the low frequency plateau region, along with a higher Q0 compared to the matrix at all Deborah numbers. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019, 57, 62–76
Specific emitter identification for satellite communication using probabilistic neural networks
Authors: Wu Xiaopo , Shi Yangming , Meng Weibo , Ma Xiaofei , Fang Nian 
Published: November 2018

SummaryElectromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.
Homogeneous Metal Nitrate Hydroxide Nanoarrays Grown on Nickel Foam for Efficient Electrocatalytic Oxygen Evolution
Authors: Ma Yan , Chu Jiayu , Li Zhennan , Rakov Dmitrii , Han Xijiang , Du Yunchen , Song Bo , Xu Ping 
Published: November 2018

AbstractDeveloping facile routes for fabricating highly efficient oxygen evolution reaction (OER) electrocatalysts is in great demand but remains a great challenge. Herein, a novel molten salt decomposition method to prepare 3D metal nitrate hydroxide (MNH, M = Ni, Co, and Cu) nanoarrays homogenously grown on different conductive substrates, especially on nickel foam (NF) for OER applications, is reported. Compared with the as‐prepared CoNH/NF and CuNH/NF, NiNH/NF presents a superior electrocatalytic OER activity and stability in an alkaline solution, with a very low overpotential of only 231 mV versus a reversible hydrogen electrode to deliver a geometrical catalytic current density of 50 mA cm−2 and a low Tafel slope of 81 mV dec−1, outperforming most reported transition metal compound catalysts. Structural investigation after the OER process reveals the morphology integrity of the nanoarrays but the formation of metal oxyhydroxide (for NiNH and CoNH) or oxide (for CuNH) as the likely real active species. These metal nitrate hydroxide non‐noble metal electrocatalysts can be prepared by an economical and simple method, with enhanced intrinsic activity and long‐term stability and durability, which might be new candidates for energy conversion and storage applications.
Electrochemical Sensor Platforms Based on Nanostructured Metal Oxides, and Zeolite‐Based Materials
Authors: Anu Prathap M. U. , Kaur Balwinder , Srivastava Rajendra 
Published: November 2018

AbstractElectrochemical sensors have drawn significant attention over the last couple of decades because of their ability to improve detection of organic and inorganic analytes found in the field of biotechnology, environmental sciences, medicine, and food quality control. This personal account summarizes the state‐of‐art research carried out in the construction and evaluation of nanostructured metal oxides and zeolite based electrochemical sensors. Metal oxides and zeolite‐based nanomaterials have many unique and extraordinary properties such as tunable redox activity, surface functionalization ability, optimum conductivity, large surface area, biocompatibility and so forth. In this personal account, the current advances in electrochemical sensor applications of metal oxides, zeolite‐based nanomaterials, and their nanocomposites are described for the single and simultaneous determination of organic & inorganic contaminants present in water bodies, physiological bio‐molecules present in human blood & urine samples, and organic contaminants present in food materials.Moreover, concluding section focuses discussion on the future developments and applications of these materials in various emerging technologies.
Variational and numerical analysis of a quasistatic thermo‐electro‐visco‐elastic frictional contact problem
Authors: Baiz Othmane , Benaissa Hicham , Moutawakil Driss El , Fakhar Rachid 
Published: November 2018

AbstractIn this paper, we study a quasi‐static contact problem between a thermo‐electro‐viscoelastic body and an electrically and thermally conductive foundation. The contact is modeled using a normal compliance contact condition with Coulomb's friction law, a regularized electrical contact condition and a heat flux contact condition taking into account the frictional heating effects. After introducing the model, the functional framework and the assumptions about the data, we derive the variational formulation of the model and prove its solvability. The proof is based on results of variational inequalities and fixed point argument. Finally, we investigate a fully discrete approximation using, respectively, Euler scheme and finite element method for the spatial variable and the time derivatives. Some error estimates are then derived, leading to convergence results under suitable additional regularity conditions.
Precision immunoprofiling by image analysis and artificial intelligence
Authors: Koelzer Viktor H. , Sirinukunwattana Korsuk , Rittscher Jens , Mertz Kirsten D. 
Published: November 2018

AbstractClinical success of immunotherapy is driving the need for new prognostic and predictive assays to inform patient selection and stratification. This requirement can be met by a combination of computational pathology and artificial intelligence. Here, we critically assess computational approaches supporting the development of a standardized methodology in the assessment of immune-oncology biomarkers, such as PD-L1 and immune cell infiltrates. We examine immunoprofiling through spatial analysis of tumor-immune cell interactions and multiplexing technologies as a predictor of patient response to cancer treatment. Further, we discuss how integrated bioinformatics can enable the amalgamation of complex morphological phenotypes with the multiomics datasets that drive precision medicine. We provide an outline to machine learning (ML) and artificial intelligence tools and illustrate fields of application in immune-oncology, such as pattern-recognition in large and complex datasets and deep learning approaches for survival analysis. Synergies of surgical pathology and computational analyses are expected to improve patient stratification in immuno-oncology. We propose that future clinical demands will be best met by (1) dedicated research at the interface of pathology and bioinformatics, supported by professional societies, and (2) the integration of data sciences and digital image analysis in the professional education of pathologists.
The return of investment of hospital-based surgical quality improvement programs in reducing surgical site infection at a Canadian tertiary-care hospital
Authors: van Katwyk Sasha , Thavorn Kednapa , Coyle Doug , Moloo Husein , Forster Alan J. , Jackson Timothy , Schramm David 
Published: November 2018

AbstractObjectiveWe performed a return-on-investment analysis comparing the investment in surgical site infection (SSI) prevention programs in a hospital setting to the savings from averted SSI cases.DesignA retrospective case costing study using aggregated patient data to determine the incidence and costs of SSI infection in surgical departments over time. We calculated return on investment to the hospital and conducted several sensitivity and scenario analyses.SettingData were compiled for the Ottawa Hospital (TOH), a Canadian tertiary-care teaching institution.PatientsWe used aggregated records for all hospital patients who underwent surgical procedures between April 2010 and January 2015.InterventionWe estimated the potential cost savings of the hospital’s surgical quality improvement program, namely the Surgeons National Surgical Quality Improvement Program (NSQIP) and the Comprehensive Unit-based Safety Program (CUSP).ResultsFrom 2010 to 2016, TOH invested C$826,882 (US$624,384) in surgical quality improvement programs targeting SSI incidence and accrued C$1,885,110 (US$1,423,460) in cumulative savings from averted SSI cases, generating a return of $2.28 (US$3.02) per dollar invested (95% confidence interval [CI], −0.67 to 7.37). The study findings are sensitive to the estimated cost to the hospital per SSI case and the rate reduction attributable to the prevention program.ConclusionsThe NSQIP and CUSP have produced a positive return on investment at TOH; however, the result rests on several assumptions. This positive return on investment is expected to continue if the hospital can continue to reduce SSI incidence at least 0.25% annually without new investments. Findings from this study highlight the need for continuous program evaluation of the quality improvement initiatives.
Orthographic processing and children’s word reading
Authors: DEACON S. HÉLÈNE , PASQUARELLA ADRIAN , MARINUS EVA , TIMS TALISA , CASTLES ANNE 
Published: November 2018

ABSTRACTTheories of reading development generally agree that, in addition to phonological decoding, some kind of orthographic processing skill underlies the ability to learn to read words. However, there is a lack of clarity as to which aspect(s) of orthographic processing are key in reading development. We test here whether this is orthographic knowledge and/or orthographic learning. Whereas orthographic knowledge has been argued to reflect a child’s existing store of orthographic representations, orthographic learning is concerned with the ability to form these representations. In a longitudinal study of second- and third-grade students, we evaluate the relations between these two aspects of orthographic processing and word-reading outcomes. The results of our analyses show that variance captured by orthographic knowledge overlaps with that of word reading, to the point that they form a single latent word-reading factor. In contrast, orthographic learning is distinctive from this factor. Further, structural equation modeling demonstrates that early orthographic learning was related to gains in word reading skills. We discuss the implications of these findings for theories of word-reading development.
CT evaluation of aberrant right subclavian artery: anatomy and clinical implications
Authors: Krupiński Maciej , Irzyk Małgorzata , Moczulski Zbigniew , Banyś Robert , Dwojak Ireneusz , Urbańczyk-Zawadzka Małgorzata 
Published: November 2018

AbstractPurposeThe aim of the study was to perform CT angiography-based evaluation of aberrant right subclavian artery prevalence, anatomy, and its influence on clinical symptoms.MethodsA total of 6833 patients who underwent 64-slice or dual-source CT angiography and those who revealed aberrant right subclavian artery underwent evaluation of its anatomy and were interviewed for the presence of clinical symptoms.ResultsAberrant right subclavian artery was found in 32 (0.47%) patients consisting of 13 males and 19 females, with mean age of 60.8±13.4 years. Among the interviewed 30 (94%) patients, oesophageal compression was observed in 14 cases (47%) and tracheal compression in three cases (10%). None of the patients underwent surgery related to aberrant right subclavian artery. Dysphagia was the most common clinical symptom in nine cases (30%), and in those patients the median distance between aberrant right subclavian artery and trachea was lower (4 mm) than in individuals without dysphagia (7.5 mm) (p = 0.009). The median lumen area of the aberrant right subclavian artery at the level of oesophagus was higher in patients with dysphagia (208 mm2) compared with individuals without dysphagia (108 mm2) (p = 0.01).ConclusionsAberrant right subclavian artery is a rare occurring abnormality in CT angiography. In the evaluated adult population, the most common symptom was dysphagia, which occurred in patients with decreased distance between aberrant right subclavian artery and trachea and increased lumen area of the aberrant artery at the level of compressed oesophagus.
Blue Endorsements Matter: How the Fraternal Order of Police Contributed to Donald Trump’s Victory
Authors: Zoorob Michael 
Published: November 2018

ABSTRACTConventional accounts of Donald Trump’s unexpected electoral victory stress idiosyncratic events and media celebrity because most observers assume this unusual candidate won without much organized support. However, considerable evidence suggests that the support of conservative organizational networks, including police unions such as the Fraternal Order of Police (FOP), propelled Trump to victory. The FOP is both a public-sector union and a conservative, mass-membership fraternal association that was courted by the Trump campaign at a time of politically charged debates about policing. Four years before, the FOP had refused to endorse Republican candidate Mitt Romney because he opposed public-sector unionism, which provided fruitful and rare variation in interest-group behavior across electoral cycles. Using a difference-in-differences approach, I find that FOP lodge density contributed to a significant swing in vote share from Romney to Trump. Moreover, survey evidence indicates that police officers reported increased political engagement in 2016 versus 2012. Belying the notion that Trump lacked a “ground game,” this research suggests that he tapped into existing organizational networks, showing their enduring importance in electoral politics.
Differences in Facial Emotional Recognition Between Patients With the First-Episode Psychosis, Multi-episode Schizophrenia, and Healthy Controls
Authors: Bosnjak Kuharic Dina , Makaric Porin , Kekin Ivana , Lukacevic Lovrencic Iva , Savic Aleksandar , Ostojic Drazenka , Silic Ante , Brecic Petrana , Bajic Zarko , Rojnic Kuzman Martina 
Published: November 2018

AbstractObjectives: The aim of our study was to assess the differences in facial emotional recognition (FER) between patients with first-episode psychosis (FEP), patients with multi-episode schizophrenia (SCH), and healthy controls (HC) and to find possible correlations of FER with psychopathology in the two patient groups. Methods: We performed a cross-sectional study enrolling 160 patients from two psychiatric hospitals in Croatia (80 FEP and 80 SCH) and 80 HC during the period from October 2015 until October 2017. Patients were assessed once during their hospital treatment, using the Penn Emotion Recognition Task for assessment of FER, rating scales for psychopathology and depression and self-reporting questionnaires for impulsiveness, aggression, and quality of life. Results: The number of correctly identified emotions significantly decreased from HC to FEP [Δ −7%; 95% confidence interval (CI) [−12% to −3%], effect size r = 0.30] and more markedly in SCH (Δ −15%; 95% CI [−25% to −10%], effect size r = 0.59) after the adjustment for age and gender and correction for multiple testing. Correct FER for negative emotions, but not for happiness and neutral emotions, had a statistically significant negative correlation with some features on the scales of psychopathology, impulsivity and aggression in both patient groups. Conclusions: Impairment of FER is present from the first episode of schizophrenia and increases further with multiple psychotic episodes, but it may depend on or contribute to clinical symptoms. Therefore, assessment of FER should be included in the clinical assessment and integrated in the plan of treatment from the beginning of the illness. (JINS, 2019, 25, 165–173)
Fe and Nutrients in Coastal Antarctic Streams: Implications for Primary Production in the Ross Sea
Authors: Olund Sydney , Lyons W. Berry , Welch Susan A. , Welch Kathy A. 
Published: November 2018

AbstractThe Southern Ocean (SO) has been an area of biogeochemical interest due to the presence of macronutrients (N, P, and Si) but lack of the expected primary production response, which is thought to be primarily due to Fe limitation. Because primary production is associated with increased drawdown of atmospheric CO2, it is important to quantify the fluxes of Fe and other nutrients into the SO. Here we present data from subaerial streams that flow into the Ross Sea, a sector of the coastal SO. Water samples were collected in the McMurdo Dry Valleys, Antarctica, and analyzed for macronutrients and Fe to determine the potential impact of terrestrial water input on the biogeochemistry of coastal oceanic waters. The physiochemical forms of Fe were investigated through analysis of three operationally defined forms: acid‐dissolvable Fe (no filtration), filterable Fe (<0.4 μm), and dissolved Fe (<0.2 μm). The combined average flux from two McMurdo Dry Valley streams was approximately 240 moles of filterable Fe per year. The dissolved fraction of Fe made up 18%–27% of the filterable Fe. The stream data yield an average filterable stoichiometry of N3P1Si100Fe0.8, which is substantially different from the planktonic composition and suggests that these streams are a potential source of Fe and P, relative to N and Si, to coastal phytoplankton communities. While the Fe flux from these streams is orders of magnitude less than estimated eolian and iceberg sources, terrestrial streams are expected to become a more significant source of Fe to the Ross Sea in the future.
Carbon Fluxes and Primary Magma CO2Contents Along the Global Mid‐Ocean Ridge System
Authors: Le Voyer Marion , Hauri Erik H. , Cottrell Elizabeth , Kelley Katherine A. , Salters Vincent J. M. , Langmuir Charles H. , Hilton David R. , Barry Peter H. , Füri Evelyn 
Published: November 2018

AbstractThe concentration of carbon in primary mid‐ocean ridge basalts (MORBs), and the associated fluxes of CO2outgassed at ocean ridges, is examined through new data obtained by secondary ion mass spectrometry (SIMS) on 753 globally distributed MORB glasses. MORB glasses are typically 80–90% degassed of CO2. We thus use the limited range in CO2/Ba (81.3 ± 23) and CO2/Rb (991 ± 129), derived from undegassed MORB and MORB melt inclusions, to estimate primary CO2concentrations for ridges that have Ba and/or Rb data. When combined with quality‐controlled volatile‐element data from the literature (n = 2,446), these data constrain a range of primary CO2abundances that vary from 104 ppm to 1.90 wt%. Segment‐scale data reveal a range in MORB magma flux varying by a factor of 440 (from 6.8 × 105to 3.0 × 108m3/year) and an integrated global MORB magma flux of 16.5 ± 1.6 km3/year. When combined with CO2/Ba and CO2/Rb‐derived primary magma CO2abundances, the calculated segment‐scale CO2fluxes vary by more than 3 orders of magnitude (3.3 × 107to 4.0 × 1010mol/year) and sum to an integrated global MORB CO2flux of × 1012mol/year. Variations in ridge CO2fluxes have a muted effect on global climate; however, because the vast majority of CO2degassed at ridges is dissolved into seawater and enters the marine bicarbonate cycle. MORB degassing would thus only contribute to long‐term variations in climate via degassing directly into the atmosphere in shallow‐water areas or where the ridge system is exposed above sea level.
A Parameterization for Volcanic Heat Flux in Heat Pipe Planets
Authors: Kankanamge Duminda G. J. , Moore William B. 
Published: November 2018

AbstractRocky planets with high levels of internal heat production experience high rates of melting and extensive volcanic resurfacing in the heat pipe mode of planetary heat transport. On Earth, this took place prior to the onset of plate tectonics during the first billion or more years. The extraction of melt from a planetary mantle affects the mantle dynamics, the temperature structure of the interior, the viscosity of mantle material, and the timescales of thermal equilibration in the mantle, and therefore, developing a quantitative parameterization for heat transport by volcanism is necessary to calculate the thermal histories of terrestrial planets efficiently. In this work, we develop a quantitative parameterization of heat transport in planetary mantles including the effect of melting. The heat flux due to melting, the internal temperature of the mantle, the temperature of the lid base, the lid thickness, and the heat flux due to conduction were calculated using the parameterization for different cases of solidus gradient and surface melting temperatures, and the values were compared with the results of numerical simulations for validation. The good fit achieved (<15% relative error) over a large range of melt fluxes with no additional parameters indicates that the parameterization usefully and accurately models the process of mantle convection including melting.