bluuebunny/crossref_metadata_2025_split huggingface dataset:
A sparse representation‐based radiomics for outcome prediction of higher grade gliomas
Authors: Wu Guoqing , Shi Zhifeng , Chen Yinsheng , Wang Yuanyuan , Yu Jinhua , Lv Xiaofei , Chen Liang , Ju Xue , Chen Zhongping 
Published: November 2018

PurposeAccurately predicting outcome (i.e., overall survival (OS) time) for higher grade glioma (HGG) has great clinical value and would provide optimized guidelines for treatment planning. Radiomics focuses on revealing underlying pathophysiological information in biomedical images for disease analysis and demonstrates promising prognostic clinical performance. In this paper, we propose a novel sparse representation‐based radiomics framework to predict if HGG patients would have long or short OS time.MethodsFirst, taking advantages of the scale invariant feature transform (SIFT) feature in image characterizing, we developed a sparse representation‐based method to convert a local SIFT descriptor into a global tumor feature. Next, because preserving sample structure is beneficial for feature selection, we proposed a locality preserving projection and sparse representation‐combined feature selection method to select more discriminative features for tumor classification. Finally, we employed a multifeature collaborative sparse representation classification to combine the information of multimodal images to classify OS time.ResultsThree experiments were performed on the two datasets provided by different institutions. Specifically, the proposed model was trained and independently tested on dataset 1 (135 subjects), on dataset 2 (86 subjects), and on the combination of dataset 1 and dataset 2, respectively. Experimental results demonstrated that the proposed method achieved encouraging prediction performance, exhibiting a testing accuracy of 93.33% on dataset 1 (one modality), 92.31% on dataset 2 (two modalities), and 87.93% on the combined dataset (one modality).ConclusionsThe sparse representation theory provides reasonable solutions to feature extraction, feature selection, and classification for radiomics. This study provides a promising tool to enhance the prediction performance of HGG patient's outcome.
Accelerated, first‐pass cardiac perfusion pulse sequence with radial k‐space sampling, compressed sensing, and k‐space weighted image contrast reconstruction tailored for visual analysis and quantification of myocardial blood flow
Authors: Naresh Nivedita K. , Haji‐Valizadeh Hassan , Aouad Pascale J. , Barrett Matthew J. , Chow Kelvin , Ragin Ann B. , Collins Jeremy D. , Carr James C. , Lee Daniel C. , Kim Daniel 
Published: November 2018

PurposeTo develop an accelerated cardiac perfusion pulse sequence and test whether it is capable of increasing spatial coverage, generating high‐quality images, and enabling quantification of myocardial blood flow (MBF).MethodsWe implemented an accelerated first‐pass cardiac perfusion pulse sequence by combining radial k‐space sampling, compressed sensing (CS), and k‐space weighted image contrast (KWIC) filtering. The proposed and clinical standard pulse sequences were evaluated in a randomized order in 13 patients at rest. For visual analysis, 3 readers graded the conspicuity of wall enhancement, artifact, and noise level on a 5‐point Likert scale (overall score index = sum of 3 individual scores). Resting MBF was calculated using a Fermi function model with and without KWIC filtering. Mean visual scores and MBF values were compared between sequences using appropriate statistical tests.ResultsThe proposed pulse sequence produced greater spatial coverage (6–8 slices) with higher spatial resolution (1.6 × 1.6 × 8 mm3) and shorter readout duration (78 ms) compared to clinical standard (3–4 slices, 3 × 3 × 8 mm3, 128 ms, respectively). The overall image score index between accelerated (11.1 ± 1.3) and clinical standard (11.2 ± 1.3) was not significantly different (P = 0.64). Mean resting MBF values with KWIC filtering (0.9–1.2 mL/g/min across different slices) were significantly lower (P < 0.0001) than those without KWIC filtering (3.1–4.3 mL/g/min) and agreed better with values reported in literature.ConclusionAn accelerated, first‐pass cardiac perfusion pulse sequence with radial k‐space sampling, CS, and KWIC filtering is capable of increasing spatial coverage, generating high‐quality images, and enabling quantification of MBF.
Retrospective artifact elimination in MEGA‐PRESS using a correlation approach
Authors: Tapper Sofie , Tisell Anders , Helms Gunther , Lundberg Peter 
Published: November 2018

PurposeTo develop a method for retrospective artifact elimination of MRS data. This retrospective method was based on an approach that combines jackknife analyses with the correlation of spectral windows, and therefore termed “JKC.”MethodsTwelve healthy volunteers performed 3 separate measurement protocols using a 3T MR system. One protocol consisted of 2 cerebellar MEGA‐PRESS measurements: 1 reference and 1 measurement including head movements. One‐third of the artifact‐influenced datasets were treated as training data for the implementation the JKC method, and the rest were used for validation.ResultsThe implemented JKC method correctly characterized most of the validation data. Additionally, after elimination of the detected artifacts, the resulting concentrations were much closer to those computed for the reference datasets. Moreover, when the JKC method was applied to the reference data, the estimated concentrations were not affected, compared with standard averaging.ConclusionThe implemented JKC method can be applied without any extra cost to MRS data, regardless of whether the dataset has been contaminated by artifacts. Furthermore, the results indicate that the JKC method could be used as a quality control of a dataset, or as an indication of whether a shift in voxel placement has occurred during the measurement.
Robust retrospective frequency and phase correction for single‐voxel MR spectroscopy
Authors: Wilson Martin 
Published: November 2018

PurposeSubject motion and static field (B0) drift are known to reduce the quality of single voxel MR spectroscopy data due to incoherent averaging. Retrospective correction has previously been shown to improve data quality by adjusting the phase and frequency offset of each average to match a reference spectrum. In this work, a new method (RATS) is developed to be tolerant to large frequency shifts (>7 Hz) and baseline instability resulting from inconsistent water suppression.MethodsIn contrast to previous approaches, the variable‐projection method and baseline fitting is incorporated into the correction procedure to improve robustness to fluctuating baseline signals and optimization instability. RATS is compared to an alternative method, based on time‐domain spectral registration (TDSR), using simulated data to model frequency, phase, and baseline instability. In addition, a J‐difference edited glutathione in‐vivo dataset is processed using both approaches and compared.ResultsRATS offers improved accuracy and stability for large frequency shifts and unstable baselines. Reduced subtraction artifacts are demonstrated for glutathione edited MRS when using RATS, compared with uncorrected or TDSR corrected spectra.ConclusionsThe RATS algorithm has been shown to provide accurate retrospective correction of SVS MRS data in the presence of large frequency shifts and baseline instability. The method is rapid, generic and therefore readily incorporated into MRS processing pipelines to improve lineshape, SNR, and aid quality assessment.
Quantifying the Net Benefits of Suppression: Truncated Size Structure and Consumption of Native Salmonids by Invasive Northern Pike in an Alaska Lake
Authors: Courtney Michael B. , Schoen Erik R. , Wizik Andy , Westley Peter A. H. 
Published: November 2018

Abstract
Predation by nonnative Northern Pike Esox lucius is implicated in the decline of native salmonid Oncorhynchus spp. populations in south-central Alaska. In response to the ongoing invasion of Northern Pike, eradication and suppression programs are under way in several severely impacted watersheds throughout the region. As previous research indicates that owing to the particular composition of their diet small Northern Pike may have disproportionate impacts on juvenile Pacific salmon Oncorhynchus spp. (hereafter, “salmon”) populations, there is a potentially important trade-off between overall predator reduction and truncation of the size structure of the population. We examined this trade-off using bioenergetics models and field data collected during a 5-year Northern Pike suppression program in Shell Lake, a heavily impacted Sockeye Salmon O. nerka nursery lake in the Susitna River drainage of south-central Alaska. Our results confirm that Northern Pike of all sizes consumed salmon and that on average salmon made up a smaller proportion of the diets of large Northern Pike. However, large Northern Pike consumed more salmon biomass per capita than smaller Northern Pike, according to the bioenergetics model incorporating size-dependent metabolic needs. Compared with the period prior to initiation of suppression efforts in 2013, Northern Pike consumed 68% less salmon in 2014, 87% less in 2015, and 88% less in 2016. Despite the fact that the catches are now dominated by smaller and younger Northern Pike, the suppression program has been highly effective at reducing the consumption of salmon in Shell Lake, with stark reductions in the catch of all size- and age-classes. Importantly, the reduction in the abundance of the oldest (age 5) Northern Pike to near zero was an key element in this reduction in predator consumption. Therefore, we conclude that suppression strategies targeting a broad range of size-classes of Northern Pike are more likely to be effective at reducing the consumption of salmon than strategies targeting only smaller size-classes.
Highly efficient optical aggregation network with network functions virtualization
Authors: Miyamura Takashi , Misawa Akira , Kani Jun‐ichi 
Published: November 2018

SummaryNetwork functions virtualization enables network edge functions to be relocated from dedicated hardware to distributed pools of commodity servers. Metro aggregation networks provide transport between access gateway nodes and such servers accommodating virtual network functions (VNFs). Networks need to be designed to increase the efficiency of network resource usage and reducing network cost as well as energy consumption. However, independently placing VNFs on a server from a physical network design degrades the efficiency of resource usage and causes an increase in network cost. We can avoid such problems by adequately placing each VNF in consideration of the location of access gateway nodes and a network topology. We thus propose a method for designing an optical aggregation network with VNF placement. We successfully formulate the design method as mixed‐integer linear programming and demonstrate its effectiveness through intensive mathematical experiments. The experiments showed that the proposed method reduced network cost by up to about 18% while performing almost optimally in terms of server load dispersion.
iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations
Authors: Geng Cunliang , Vangone Anna , Folkers Gert E. , Xue Li C. , Bonvin Alexandre M. J. J. 
Published: November 2018

AbstractQuantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning‐based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using a small number of sensitive predictive features is vital to the generalization and robustness of such machine learning methods. Here we introduce a fast and reliable predictor of binding affinity changes upon single point mutation, based on a random forest approach. Our method, iSEE, uses a limited number of interface Structure, Evolution, and Energy‐based features for the prediction. iSEE achieves, using only 31 features, a high prediction performance with a Pearson correlation coefficient (PCC) of 0.80 and a root mean square error of 1.41 kcal/mol on a diverse training dataset consisting of 1102 mutations in 57 protein‐protein complexes. It competes with existing state‐of‐the‐art methods on two blind test datasets. Predictions for a new dataset of 487 mutations in 56 protein complexes from the recently published SKEMPI 2.0 database reveals that none of the current methods perform well (PCC < 0.42), although their combination does improve the predictions. Feature analysis for iSEE underlines the significance of evolutionary conservations for quantitative prediction of mutation effects. As an application example, we perform a full mutation scanning of the interface residues in the MDM2–p53 complex.
Concise Review: Lessons Learned from Islet Transplant Clinical Trials in Developing Stem Cell Therapies for Type 1 Diabetes
Authors: Welsch Carole A. , Rust William L. , Csete Marie 
Published: November 2018

Abstract
We examined data and patterns in clinical islet transplant studies registered on ClinicalTrials.gov (CTgov) for treatment of type 1 diabetes (T1D), with a goal of extracting insights to apply in the design of a pluripotent stem cell-derived islet therapy. Clinical islet transplantation, as a cell therapy (rather than solid organ transplant) is a unique precedent for stem cell-based islet therapies. Registration activity shows that the field is not growing significantly, and newer registrations suggest that the reasons for stagnation include need for a more optimal site of infusion/transplantation, and especially a need for better immune protective strategies to advance a more effective and durable therapy for T1D. Stem Cells Translational Medicine 2019;8:209&214
Why the social cost of carbon will always be disputed
Authors: Pezzey John C. V. 
Published: November 2018

Any social cost of carbon (SCC) calculated from an integrated assessment model of global climate‐economy interactions will always be disputed. This is because a key model input–namely the valuation of centennial climate damage–is highly unknowable for fundamental reasons discussed here. Problems with damage valuation are highlighted by the implicit implausibility to climate scientists of a leading model's (centennial) damage function, and by strong criticisms of damage functions by many climate economists. The claim that statistical analyses of past weather impacts on local economies, combined with structural modeling of sectoral impacts, can significantly improve centennial damage valuation rests on untestable, far‐out‐of‐sample extrapolation. Testing centennial climate (natural) science projections is generally harder than testing predictions in astronomy, geology and other earth sciences, because of Earth's uniqueness, and the unprecedented degree of likely climate change; but stable underlying laws make climate modeling based on past observations meaningful. By contrast, the added complexity of human behavior means there are no quantitatively stable laws for modeling the value of centennial climate damage. I suggest that any carbon prices used to inform climate policies, be they carbon prices used as policy instruments, or complementary, non‐carbon‐price policies, should instead be based on marginal abatement costs, found by modeling low‐cost pathways to socially agreed, physical climate targets. A pathway approach to estimating carbon prices poses challenges to many economists, and is no panacea, but it avoids any illusion of optimality, and facilitates detailed analysis of sectoral policies.This article is categorized under:Climate Economics > Aggregation Techniques for Impacts and Mitigation CostsAssessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change
Shared neural and cognitive mechanisms in action and language: The multiscale information transfer framework
Authors: Blumenthal‐Dramé Alice , Malaia Evie 
Published: November 2018

This review compares how humans process action and language sequences produced by other humans. On the one hand, we identify commonalities between action and language processing in terms of cognitive mechanisms (e.g., perceptual segmentation, predictive processing, integration across multiple temporal scales), neural resources (e.g., the left inferior frontal cortex), and processing algorithms (e.g., comprehension based on changes in signal entropy). On the other hand, drawing on sign language with its particularly strong motor component, we also highlight what differentiates (both oral and signed) linguistic communication from nonlinguistic action sequences. We propose the multiscale information transfer framework (MSIT) as a way of integrating these insights and highlight directions into which future empirical research inspired by the MSIT framework might fruitfully evolve.This article is categorized under:

Psychology > Language
Linguistics > Language in Mind and Brain
Psychology > Motor Skill and Performance
Psychology > Prediction
Rembrandt's Old Woman Praying, 1629/30: A look below the surface using X‐ray fluorescence mapping
Authors: Uhlir Katharina , Gironda Michele , Bombelli Luca , Eder Michael , Aresi Nicola , Groschner Gabriele , Griesser Martina 
Published: November 2018

Rembrandt's painting Old Woman Praying, 1629/30, is the most valuable and exceptional work of art of the Residenzgalerie Salzburg (RGS). It is painted on a gilded copper plate with dimensions of only approximately 15 × 12 cm. The painting probably belongs to a series of three small‐scale tronies, all executed on gilded copper plates. This particular picture preparation, which represents a special feature in Rembrandt's work, is quite unusual in the history of art.Previous investigations on the comparable paintings The Laughing Man, 1629/30, in the Mauritshuis, The Hague and the Self Portrait, 1630, in the National Museum, Stockholm showed that the gilding of the copper plate was applied over a lead white ground.To characterize the painting in the RGS, X‐ray fluorescence (XRF) mapping was performed in a collaboration between the Research Office Residenzgalerie, Land Salzburg, the XGLab S.R.L, Milan, and the Conservation Science Department of the Kunsthistorische Museum Vienna (KHM). The results indicate a different structure for this painting than that used for The Laughing Man and the Self Portrait. The gilding was applied directly onto the copper plate, but with three areas with the gilding missing. It seems likely that in these sections, the gold was purposely removed to provide a different darker effect.XRF mapping yielded valuable insights into the structure of the painting and its technique as well as the principal pigments used for its composition.
Decision tree supports the interpretation of CSF biomarkers in Alzheimer's disease
Authors: Babapour Mofrad Rosha , Schoonenboom Niki S.M. , Tijms Betty M. , Scheltens Philip , Visser Pieter Jelle , van der Flier Wiesje M. , Teunissen Charlotte E. 
Published: November 2018

AbstractIntroductionWe developed and validated a clinically applicable decision tree for the use of cerebrospinal fluid biomarkers in the diagnosis of Alzheimer's disease (AD).MethodsSubjects with probable AD (n = 1004) and controls (n = 442) were included. A decision tree was modeled using Classification And Regression Tree analysis in a training cohort (AD n = 221; controls n = 221) and validated in an independent cohort (AD n = 783; controls n = 221). Diagnostic performance was compared to previously defined cutoffs (amyloid β 1‐42 < 813 pg/ml; tau>375 pg/ml).ResultsTwo cerebrospinal fluid AD biomarker profiles were revealed: the “classical” AD biomarker profile (amyloid β 1‐42: 647‐803 pg/ml; tau >374 pg/ml) and an “atypical” AD biomarker profile with strongly decreased amyloid β 1‐42 (<647 pg/ml) and normal tau concentrations (<374 pg/ml). Compared to previous cutoffs, the decision tree performed better on diagnostic accuracy (86% [84‐88] vs 80% [78‐83]).DiscussionTwo cerebrospinal fluid AD biomarker profiles were identified and incorporated in a readily applicable decision tree, which improved diagnostic accuracy.
Merchant’s Road Toward the Utopia in Heliodorus’Aethiopica
Authors: Sanchez Hernandez Juan Pablo 
Published: November 2018

AbstractHeliodorus’Aethiopicanarrates the adventurous journey of a couple through Egypt to the kingdom of Meroe in Ethiopia where they get married. To increase the plausibility of this story Heliodorus uses his knowledge of Rome’s trade activities in the East and he even introduces some characters involved in trade ventures in those regions (e.g. Nausicles) at crucial moments of its development. On the other hand, Heliodorus’ references to luxurious products of Eastern and African origin, as well as to exotic animals or tribes, are recurring elements (orleitmotifs) that are consciously interspersed throughout the novel. Those references not only serve to unify a carefully planned plot and guide the reader to an intended conclusion, but also to map the idealised Ethiopia and its neighboring subjected regions (inhabited by some fantastic tribes), where the protagonists will eventually live.
The Knowledge Level of Dentists in Turkey About Their Potential Role on the Disaster Victims Identification (DVI) Team
Authors: Yasar Zehtiye Fusun , Durukan Elif , Buken Erhan 
Published: November 2018

AbstractObjectiveAlthough dentists are valuable assets in identification teams during disaster events, forensic dentistry is not used effectively in the identification studies conducted in Turkey, and the importance of dental data is ignored. The aim of this study was to determine the level of knowledge of dentists regarding their duties and responsibilities during major disasters.MethodsThis descriptive study was conducted between December 2015 and June 2016. Registered dentists (n=20.280) of the Turkish Dental Association were invited to complete the organization’s online survey. A total of 539 dentists participated in the volunteer workshop. Data were analyzed using SPSS, version 22.0 (IBM Corp, Armonk, NY). The chi-square analysis was used to evaluate the knowledge level of dentists by group regarding disaster victim identification (DVI) – the process and procedure of recovering and identifying victims of major disasters (eg, earthquake, terrorist attack).ResultsThe dentists included in the study consisted of 320 (59.4%) females and 219 (40.6%) males with a mean age of 37.4±12.6 years. The number of specialists and general dentists were 249 (45.6%) and 297 (54.4%), respectively; 249 (69.71%) dentists who had knowledge about forensic dentistry stated that they received this information during their formal training. The percentage of dentists who were aware of the existence of an organization of a disaster response operation in Turkey was 74.2%, but only 20.5% (n=110) had knowledge about DVI. We found that 92.9% (n=104) of these dentists believed that dentists should be included in the team for the identification of disaster victims. On the other hand, only half (52.3%) of the dentists with knowledge of DVI wanted to work on the identification teams. The majority (99.1%) considered DNA analysis to be the safest method for identification.ConclusionOur findings show that, although dentists know about the identification process, they do not have enough relevant knowledge. (Disaster Med Public Health Preparedness.2019;13:533-538)