bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hand‐eye calibration method for augmented reality applied to computer‐assisted orthopedic surgery
Authors: de Oliveira Marcelo E. , Debarba Henrique G. , Lädermann Alexandre , Chagué Sylvain , Charbonnier Caecilia 
Published: November 2018

AbstractBackground: Augmented reality (AR) allows the surgeon to represent holographic patient‐specific anatomical information and surgical instruments in the physical world. To correctly superimpose virtual and physical objects, a hand‐eye (HE) calibration method for mapping the virtual and physical spaces was proposed.Methods: Mathematical relationships between the virtual camera and the physical space were derived. Finally, the accuracy and robustness of the proposed HE calibration method were qualitatively and quantitatively evaluated.Results: The proposed calibration method allows us to determine an optimal invariant spatiotemporal mapping between the virtual camera and the physical space.Conclusion: Qualitatively and quantitatively reliable and accurate estimates for the physical‐virtual mapping transformation were verified. Consequently, imaging data and surgical instruments holograms can be precisely represented in the physical space.
Cognitive functions in young adults with generalized anxiety disorder
Authors: Leonard Kiara , Abramovitch Amitai 
Published: November 2018

AbstractBackground:Anxiety and worry are central symptoms of Generalized Anxiety Disorder (GAD) that have been theorized to negatively impact cognitive functions. However, most of the research has focused on threat-related or emotionally-charged stimuli, and a surprisingly small number of investigations examined ‘cold’ cognitive functions using classic neuropsychological tests. Such investigations are particularly important given that some theoretical models suggest compensatory mechanisms associated with anxiety that in certain circumstances may result in intact performance. The aim of the present study is to assess the neuropsychological profile associated with GAD, using a comprehensive neuropsychological battery.Methods:A sample of 23 college students meeting criteria for DSM-5 GAD and 20 control participants completed a psychometrically valid comprehensive computerized neuropsychological battery and clinical questionnaires.Results:The GAD sample presented with significantly elevated symptomatic rates of anxiety, worry, depression and stress. However, no significant differences were found on any neuropsychological outcome measures or domain indexes. Effect sizes were small, some of which favored the GAD sample.Conclusion:Despite substantial psychopathological burden, GAD exhibited intact cognitive functioning. These results support the Cognitive Control Theory of Anxiety, suggesting that elevated primary anxiety may not impact ‘cold’ cognitive functions in the absence of threat or substantial cognitive load. Given that this is one of the only studies employing a comprehensive neuropsychological battery in GAD, more research is needed in this population to replicate these results and to examine the impact of anxiety on cognitive functions at varying degrees of cognitive load in this population.
Snakes on a Spaceship—An Overview of Python in Heliophysics
Authors: Burrell A. G. , Halford A. , Klenzing J. , Stoneback R. A. , Morley S. K. , Annex A. M. , Laundal K. M. , Kellerman A. C. , Stansby D. , Ma J. 
Published: November 2018

AbstractComputational analysis has become ubiquitous within the heliophysics community. However, community standards for peer review of codes and analysis have lagged behind these developments. This absence has contributed to the reproducibility crisis, where inadequate analysis descriptions and loss of scientific data have made scientific studies difficult or impossible to replicate. The heliophysics community has responded to this challenge by expressing a desire for a more open, collaborative set of analysis tools. This article summarizes the current state of these efforts and presents an overview of many of the existing Python heliophysics tools. It also outlines the challenges facing community members who are working toward the goal of an open, collaborative, Python heliophysics toolkit and presents guidelines that can ease the transition from individualistic data analysis practices to an accountable, communalistic environment.
J-PLUS: Identification of low-metallicity stars with artificial neural networks using SPHINX
Authors: Whitten D. D. , Placco V. M. , Beers T. C. , Chies-Santos A. L. , Bonatto C. , Varela J. , Cristóbal-Hornillos D. , Ederoclite A. , Masseron T. , Lee Y. S. , Akras S. , Borges Fernandes M. , Caballero J. A. , Cenarro A. J. , Coelho P. , Costa-Duarte M. V. , Daflon S. , Dupke R. A. , Lopes de Oliveira R. , López-Sanjuan C. , Marín-Franch A. , Mendes de Oliveira C. , Moles M. , Orsi A. A. , Rossi S. , Sodré L. , Vázquez Ramió H. 
Published: November 2018

Context.We present a new methodology for the estimation of stellar atmospheric parameters from narrow- and intermediate-band photometry of the Javalambre Photometric Local Universe Survey (J-PLUS), and propose a method for target pre-selection of low-metallicity stars for follow-up spectroscopic studies. Photometric metallicity estimates for stars in the globular cluster M15 are determined using this method.Aims.By development of a neural-network-based photometry pipeline, we aim to produce estimates of effective temperature,Teff, and metallicity, [Fe/H], for a large subset of stars in the J-PLUS footprint.Methods.The Stellar Photometric Index Network Explorer, SPHINX, was developed to produce estimates ofTeffand [Fe/H], after training on a combination of J-PLUS photometric inputs and synthetic magnitudes computed for medium-resolution (R~ 2000) spectra of the Sloan Digital Sky Survey. This methodology was applied to J-PLUS photometry of the globular cluster M15.Results.Effective temperature estimates made with J-PLUS Early Data Release photometry exhibit low scatter, σ(Teff) = 91 K, over the temperature range 4500 <Teff(K) < 8500. For stars from the J-PLUS First Data Release with 4500 <Teff(K) < 6200, 85 ± 3% of stars known to have [Fe/H] < −2.0 are recovered by SPHINX. A mean metallicity of [Fe/H] = − 2.32 ± 0.01, with a residual spread of 0.3 dex, is determined for M15 using J-PLUS photometry of 664 likely cluster members.Conclusions.We confirm the performance of SPHINX within the ranges specified, and verify its utility as a stand-alone tool for photometric estimation of effective temperature and metallicity, and for pre-selection of metal-poor spectroscopic targets.
Change in Metaphorical Framing: Metaphors of TRade in 225 Years of State of the Union Addresses (1790–2014)
Authors: Burgers Christian , Ahrens Kathleen 
Published: November 2018

AbstractThe literature provides diverging perspectives on the universality and stability of economic metaphors over time. This article contains a diachronic analysis of economic metaphors describing trade in a corpus of 225 years of US State of the Union addresses (1790–2014). We focused on two types of change: (i) replacement of a source domain by another domain and (ii) change in mapping within a source domain. In our corpus, five source domains of trade were predominant: (i) PhysicalObject, (ii) Building, (iii) Container, (iv) Journey, and (v) LivingBeing. Only the relative frequency of the Container source domain was related to time. Additionally, mappings between source and target domains were mostly stable. Nevertheless, our analyses suggest that the Trade metaphors in our corpus are related to concreteness in a more nuanced way as typically assumed in conceptual metaphor theory: metaphors high in the concreteness dimension of physicality and low in the concreteness dimension of specificity are likeliest to be used over longer time periods, by providing communicators with freedom to adjust the metaphor to changing societal circumstances.
Genetic Neural Networks: an artificial neural network architecture for capturing gene expression relationships
Authors: Eetemadi Ameen , Tagkopoulos Ilias 
Published: November 2018

AbstractMotivationGene expression prediction is one of the grand challenges in computational biology. The availability of transcriptomics data combined with recent advances in artificial neural networks provide an unprecedented opportunity to create predictive models of gene expression with far reaching applications.ResultsWe present the Genetic Neural Network (GNN), an artificial neural network for predicting genome-wide gene expression given gene knockouts and master regulator perturbations. In its core, the GNN maps existing gene regulatory information in its architecture and it uses cell nodes that have been specifically designed to capture the dependencies and non-linear dynamics that exist in gene networks. These two key features make the GNN architecture capable to capture complex relationships without the need of large training datasets. As a result, GNNs were 40% more accurate on average than competing architectures (MLP, RNN, BiRNN) when compared on hundreds of curated and inferred transcription modules. Our results argue that GNNs can become the architecture of choice when building predictors of gene expression from exponentially growing corpus of genome-wide transcriptomics data.Availability and implementationhttps://github.com/IBPA/GNNSupplementary informationSupplementary data are available at Bioinformatics online.
DeepCrystal: a deep learning framework for sequence-based protein crystallization prediction
Authors: Elbasir Abdurrahman , Moovarkumudalvan Balasubramanian , Kunji Khalid , Kolatkar Prasanna R , Mall Raghvendra , Bensmail Halima 
Published: November 2018

Abstract

Motivation
Protein structure determination has primarily been performed using X-ray crystallography. To overcome the expensive cost, high attrition rate and series of trial-and-error settings, many in-silico methods have been developed to predict crystallization propensities of proteins based on their sequences. However, the majority of these methods build their predictors by extracting features from protein sequences, which is computationally expensive and can explode the feature space. We propose DeepCrystal, a deep learning framework for sequence-based protein crystallization prediction. It uses deep learning to identify proteins which can produce diffraction-quality crystals without the need to manually engineer additional biochemical and structural features from sequence. Our model is based on convolutional neural networks, which can exploit frequently occurring k-mers and sets of k-mers from the protein sequences to distinguish proteins that will result in diffraction-quality crystals from those that will not.

Results
Our model surpasses previous sequence-based protein crystallization predictors in terms of recall, F-score, accuracy and Matthew’s correlation coefficient (MCC) on three independent test sets. DeepCrystal achieves an average improvement of 1.4, 12.1% in recall, when compared to its closest competitors, Crysalis II and Crysf, respectively. In addition, DeepCrystal attains an average improvement of 2.1, 6.0% for F-score, 1.9, 3.9% for accuracy and 3.8, 7.0% for MCC w.r.t. Crysalis II and Crysf on independent test sets.

Availability and implementation
The standalone source code and models are available at https://github.com/elbasir/DeepCrystal and a web-server is also available at https://deeplearning-protein.qcri.org.

Supplementary information
Supplementary data are available at Bioinformatics online.
Comparison of Amyloid β and Tau Spread Models in Alzheimer’s Disease
Authors: Kim Hang-Rai , Lee Peter , Seo Sang Won , Roh Jee Hoon , Oh Minyoung , Oh Jungsu S , Oh Seung Jun , Kim Jae Seung , Jeong Yong 
Published: November 2018

Abstract
Tau and amyloid β (Aβ), 2 key pathogenic proteins in Alzheimer’s disease (AD), reportedly spread throughout the brain as the disease progresses. Models of how these pathogenic proteins spread from affected to unaffected areas had been proposed based on the observation that these proteins could transmit to other regions either through neural fibers (transneuronal spread model) or through extracellular space (local spread model). In this study, we modeled the spread of tau and Aβ using a graph theoretical approach based on resting-state functional magnetic resonance imaging. We tested whether these models predict the distribution of tau and Aβ in the brains of AD spectrum patients. To assess the models’ performance, we calculated spatial correlation between the model-predicted map and the actual map from tau and amyloid positron emission tomography. The transneuronal spread model predicted the distribution of tau and Aβ deposition with significantly higher accuracy than the local spread model. Compared with tau, the local spread model also predicted a comparable portion of Aβ deposition. These findings provide evidence of transneuronal spread of AD pathogenic proteins in a large-scale brain network and furthermore suggest different contributions of spread models for tau and Aβ in AD.
The Epidemiology of Herpes Zoster in the United States During the Era of Varicella and Herpes Zoster Vaccines: Changing Patterns Among Children
Authors: Harpaz Rafael , Leung Jessica W 
Published: November 2018

AbstractVaricella vaccination can have complex direct and indirect influences on the epidemiology of herpes zoster among children. We evaluated pediatric herpes zoster trends using administrative databases. The incidence has declined in a step-wise pattern since the varicella vaccination program’s introduction, suggesting that rates may eventually decline in the entire population.
Respiratory syncytial virus F and G protein core fragments fused to HBsAg-binding protein (SBP) induce a Th1-dominant immune response without vaccine-enhanced disease
Authors: Khan Inam Ullah , Ahmad Farooq , Zhang Shuren , Lu Panpan , Wang Jingbo , Xie Jun , Zhu Naishuo 
Published: November 2018

AbstractThe induction of a dominant Th2-type response is the main cause of harmful inflammation in respiratory syncytial virus (RSV) vaccine trials. A balanced Th1 versus Th2 immune response is needed for a safe and effective RSV vaccine. In this study, we evaluated the potential of a recombinant protein SBP-FG as a vaccine candidate with the main focus on shifting the harmful Th2 response to a Th1 response. SBP-FG consists of epitopes from RSV fusion (F) and attachment (G) proteins conjugated to the N-terminus of HBsAg-binding protein (SBP). SBP-FG induced significantly stronger immune responses assessed at the level of total IgG, IgA and neutralizing antibodies as compared with formalin-inactivated RSV (FI-RSV) and live RSV. Analysis of IgG isotypes, lung cytokines and T helper cells showed that SBP-FG induced a dominant Th1-type response. Further, SBP-FG immunized mice showed significantly reduced lung eosinophilia, reduced viral multiplication in lungs after challenge infection and provided protection against RSV infection. These results suggest that SBP-FG can be developed into a safe and effective vaccine against RSV. However, more studies are required to further evaluate SBP-FG as a potent vaccine candidate against RSV.
Extended-field intensity-modulated radiation therapy combined with concurrent chemotherapy for cervical cancer with para-aortic lymph nodes metastasis
Authors: Liu Xiaoliang , Wang Weiping , Meng Qingyu , Zhang Fuquang , Hu Ke 
Published: November 2018

Abstract

Objective
This study was conducted to evaluate the efficacy and toxicity of extended-field intensity-modulated radiation therapy combined with concurrent chemotherapy in patients with cervical cancer with positive para-aortic lymph nodes (PALN).

Methods
From September 2007 to December 2014, a total of 59 patients who had cervical cancer with para-aortic lymph node metastasis were treated with concurrent chemoradiotherapy at our institution. A dose of 45–50.4 Gy in 25–28 fractions with extended-field intensity-modulated radiation therapy was prescribed to planning target volume, and a dose of 30–36 Gy in 5–6 fractions was prescribed to Point A with high-dose-rate brachytherapy. A concurrent first-line cisplatin-based chemotherapy regimen was used.

Results
The median duration of follow-up was 32.1 months (range, 3.2–103.7 months). The 2- and 3-year overall survival, disease-free survival and local control rates were 69.0 and 52.8%, 45.0 and 41.3% and 83.4 and 81.0%, respectively. Distant metastasis was the major pattern of treatment failure, which occurred in 26 patients (44.1%). The incidence of Grade 3 or greater acute hematologic, gastrointestinal and genitourinary toxicity was 50.9, 1.7 and 3.4%, respectively. Only one patient had both Grade 3 late gastrointestinal and genitourinary toxicity.

Conclusions
The study found that extended-field intensity-modulated radiation therapy combined with concurrent chemotherapy was safe and effective in patients who had cervical cancer with positive PALN.
Theorizing Fundamental Music/Dance Interactions in Salsa
Authors: Simpson-Litke Rebecca , Stover Chris 
Published: November 2018

AbstractCommunication between music and dance can take many forms. In salsa, this communication begins with and builds upon two simple but crucial criteria: for music, a metric-rhythmic foundation based on clave and other essential performance strata, and for dance, the flow and metric orientation of one of three basic footwork patterns. Most of the rich complexity of music, dance, and their interaction stems from these fundamental gestures. In this article we analyze the basic structures of salsa music and dance, theorize how they interact, and investigate three scenarios where dancers have to make decisions about how to attend to musical features via their footwork orientations.
An intermediate-velocity H i cloud falling to the galactic disk; Possible evidence for low-metallicity H i gas originating outside the galactic disk
Authors: Fukui Yasuo , Koga Masako , Maruyama Shohei , Hayakawa Takahiro , Okamoto Ryuji , Yamamoto Hiroaki , Tachihara Kengo , Shelton Robin , Sasaki Manami 
Published: November 2018

Abstract
We found that an intermediate-velocity cloud (IVC), IVC 86−36, in H i 21 cm emission shows a head–tail distribution toward the Galactic plane with marked parallel filamentary streamers, which is extended over 40° in the sky. The distance of IVC 86−36 is constrained to be less than ∼3 kpc from absorption of a background star as determined from optical spectroscopy. There is a bridge feature in velocity between the IVC and the local interstellar medium with velocity separation of ∼50 km s−1, which may indicate dynamical interaction of the IVC with the disk. If the interaction is correct, the distance estimate d of the IVC ranges from 200 pc to 3 kpc, and the mass of the IVC head is estimated to be $7\times 10^3(d/1\:\mbox{kpc})^2\, M_{\odot }$. The IVC shares similar properties to the Smith Cloud located at 12 kpc, including the head–tail distribution, streamers, and bridge feature, while the mass of the IVC is less than ∼0.1 of the Smith Cloud. A comparison between the H i and the Planck/IRAS dust emission indicates that the dust emission of IVC 86−36 is not detectable in spite of its H i column density of 2 × 1020 cm−2, indicating a low metallicity for IVC 86−36, reduced by a factor of $\lesssim \!\!0.2$ as compared with the solar neighbor. We conclude that IVC 86−38 is an infalling cloud which likely originated in the low-metallicity environment of the Galactic halo or the Magellanic system.
Trends in Postoperative Opioid Prescribing in Outpatient Pediatric Surgery
Authors: Donohoe Gabrielle C , Zhang Bingqing , Mensinger Janell L , Litman Ronald S 
Published: November 2018

AbstractObjectiveTo determine trends in opioid prescribing for home use after pediatric outpatient surgery.DesignRetrospective analysis of a de-identified database.SettingMultispecialty children’s hospital and freestanding surgery centers.Patients, ParticipantsA total of 65,190 encounters of pediatric outpatient surgeries from 2013 through 2017 for nine different surgical specialties. Patients in the cardiothoracic service and nonpainful procedures were excluded.MainOutcome Measures. Incidence rate of prescribing, dose, number of doses available (i.e., duration of therapy), and maximum weight-based home opioid availability from 2013 to 2017. Additional independent variables included sex, age, weight, race/ethnicity, insurance type (private vs public), and surgical service.ResultsThe incidence rate of receiving a take-home opioid prescription at discharge ranged from 18% to 21% between 2013 and 2017, with no clear directional trend. Among patients prescribed opioids, however, the maximum available take-home dose steadily declined from 2013 through 2017 (P < 0.001). This was due to both a decrease in the number of doses prescribed (i.e., duration of treatment) and, beginning in 2015, the amount per dose. Females were more likely to receive an opioid than males, and patients with public insurance were more likely to receive an opioid than those with private insurance. Opioid prescribing was more likely in patients who did not disclose their ethnicity and those of ethnic minority compared with white patients (all P < 0.0001).ConclusionsThe rate of receiving a take-home opioid prescription and the dose prescribed remained stable from 2013 to 2017, but the duration of treatment steadily declined, and beginning in 2015, the amount per dose also decreased. Certain subgroups of patients were more likely to be prescribed opioids and will require further investigation and confirmation.