bluuebunny/crossref_metadata_2025_split huggingface dataset:
Liver Fat Assessment in Multiview Sonography Using Transfer Learning With Convolutional Neural Networks
Authors: Byra Michal , Han Aiguo , Boehringer Andrew S. , Zhang Yingzhen N. , O'Brien William D. , Erdman John W. , Loomba Rohit , Sirlin Claude B. , Andre Michael 
Published: March 2021

ObjectivesTo develop and evaluate deep learning models devised for liver fat assessment based on ultrasound (US) images acquired from four different liver views: transverse plane (hepatic veins at the confluence with the inferior vena cava, right portal vein, right posterior portal vein) and sagittal plane (liver/kidney).MethodsUS images (four separate views) were acquired from 135 participants with known or suspected nonalcoholic fatty liver disease. Proton density fat fraction (PDFF) values derived from chemical shift‐encoded magnetic resonance imaging served as ground truth. Transfer learning with a deep convolutional neural network (CNN) was applied to develop models for diagnosis of fatty liver (PDFF ≥ 5%), diagnosis of advanced steatosis (PDFF ≥ 10%), and PDFF quantification for each liver view separately. In addition, an ensemble model based on all four liver view models was investigated. Diagnostic performance was assessed using the area under the receiver operating characteristics curve (AUC), and quantification was assessed using the Spearman correlation coefficient (SCC).ResultsThe most accurate single view was the right posterior portal vein, with an SCC of 0.78 for quantifying PDFF and AUC values of 0.90 (PDFF ≥ 5%) and 0.79 (PDFF ≥ 10%). The ensemble of models achieved an SCC of 0.81 and AUCs of 0.91 (PDFF ≥ 5%) and 0.86 (PDFF ≥ 10%).ConclusionDeep learning‐based analysis of US images from different liver views can help assess liver fat.
Point‐of‐Care Ultrasound Pronator Quadratus Hematoma Sign for Detection of Clinically Non‐Angulated Pediatric Distal Forearm Fractures
Authors: Snelling Peter J. , Keijzers Gerben , Ware Robert S. 
Published: March 2021

ObjectivesPoint‐of‐care ultrasound (POCUS) diagnosis of distal forearm fractures relies on the identification of buckling or breach of hyperechoic bone cortex. We describe the pronator quadratus hematoma (PQH) formation visualized on POCUS, the PQH sign, as it may aid diagnosis of pediatric distal forearm cortical breach fractures.MethodsA prospective cohort of children presenting to an emergency department with isolated, clinically non‐angulated distal forearm injuries received POCUS by an expert emergency physician sonologist who identified the presence or absence of the PQH sign. They secondarily recorded the difference between the size of the pronator quadratus (PQ) muscle on both the affected and non‐affected forearms (PQ delta thickness). Children received an x‐ray subsequent to POCUS and were diagnosed based on an x‐ray reported by a radiologist masked to POCUS findings.ResultsThirty‐eight children were recruited. All 22 patients with cortical breach fracture had PQH sign present (100%; 95%CI: 85–100%), while all 16 patients without cortical breach fracture had PQH sign absent (100%; 95%CI: 79–100%). PQ delta thickness ranged from 2.1 to 10.2 mm in cortical breach fractures, 0.0 to 1.1 mm in buckle fractures, and 0.2 to 0.8 mm in patients without fracture.ConclusionsThe PQH sign correctly distinguished all children with, and without, cortical breach fractures. All PQ delta thicknesses were ≧2.1 mm when cortical breach fracture was present and ≦1.1 mm when cortical breach fracture was absent. The PQH sign and PQ delta thickness are promising measurements to identify pediatric distal forearm cortical breach fractures, and their utility should be confirmed in larger studies with sonologists of different abilities.
High‐throughput NGS‐based genotyping and phenotyping: Role in genomics‐assisted breeding for soybean improvement
Authors: Bhat Javaid Akhter , Yu Deyue 
Published: March 2021

AbstractSoybean is an important food crop that provides edible protein and oil for human and animal nutrition. Conventional phenotypic‐based breeding approaches have made significant contribution in the last century by developing many improved soybean varieties. However, due to the longer time taken to develop a variety, low genetic gain per unit time, and adverse environmental influence of phenotypic‐based selection, conventional approaches are not sufficient to maintain pace with growing population and climate change. In this context, the recent method of genotypic selection, that is, genomics‐assisted breeding (GAB) is considered a promising approach to address the challenges in soybean breeding. However, to harness the true potential of GAB in soybean improvement, the great coverage and precision in the genotyping and phenotyping are required. Previously, a huge gap was observed between the discovery and practical use of quantitative trait loci (QTLs) in soybean improvement. It has been suggested that low marker density and manually collected phenotypes are the major reasons for this failure. Hence, high‐throughput genotyping (HTG) providing higher genome‐wide marker density, as well as accurate and precise phenotyping using high‐throughput digital phenotyping (HTP) platforms, can significantly increase the success of QTL and candidate gene identification in soybean. These approaches can greatly increase the practical utility of GAB in soybean and also offer a faster characterization of germplasm and breeding materials. This review provides the detailed information on how the recent innovations in genomics and phenomics can assists in improving the efficiency and potential of GAB in soybean improvement.
Longitudinal Changes in Neuromelanin MRI Signal in Parkinson's Disease: A Progression Marker
Authors: Gaurav Rahul , Yahia‐Cherif Lydia , Pyatigorskaya Nadya , Mangone Graziella , Biondetti Emma , Valabrègue Romain , Ewenczyk Claire , Hutchison R. Matthew , Cedarbaum Jesse M. , Corvol Jean‐Christophe , Vidailhet Marie , Lehéricy Stéphane 
Published: March 2021

ABSTRACTBackgroundDevelopment of reliable and accurate imaging biomarkers of dopaminergic cell neurodegeneration is necessary to facilitate therapeutic drug trials in Parkinson's disease (PD). Neuromelanin‐sensitive MRI techniques have been effective in detecting neurodegeneration in the substantia nigra pars compacta (SNpc). The objective of the current study was to investigate longitudinal neuromelanin signal changes in the SNpc in PD patients.MethodsIn this prospective, longitudinal, observational case–control study, we included 140 PD patients and 64 healthy volunteers divided into 2 cohorts. Cohort I included 99 early PD patients (disease duration, 1.5 ± 1.0 years) and 41 healthy volunteers analyzed at baseline (V1), where 79 PD patients and 32 healthy volunteers were rescanned after 2.0 ± 0.2 years of follow‐up (V2). Cohort II included 41 progressing PD patients (disease duration, 9.3 ± 3.7 years) and 23 healthy volunteers at V1, where 30 PD patients were rescanned after 2.4 ± 0.5 years of follow‐up. Subjects were scanned at 3 T MRI using 3‐dimensional T1‐weighted and neuromelanin‐sensitive imaging. Regions of interest were delineated manually to calculate SN volumes, volumes corrected by total intracranial volume, signal‐to‐noise ratio, and contrast‐to‐noise ratio.ResultsResults showed (1) significant reduction in volume and volume corrected by total intracranial volume between visits, greater in progressing PD than nonsignificant changes in healthy volunteers; (2) no significant effects of visit for signal intensity (signal‐to‐noise ratio); (3) significant interaction in volume between group and visit; (4) greater volume corrected by total intracranial volume at baseline in female patients and greater decrease in volume and increase in the contrast‐to‐noise ratio in progressing female PD patients compared with male patients; and (5) correlations between neuromelanin SN changes and disease severity and duration.ConclusionsWe observed a progressive and measurable decrease in neuromelanin‐based SN signal and volume in PD, which might allow a direct noninvasive assessment of progression of SN loss and could represent a target biomarker for disease‐modifying treatments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
Effective diagnostic model construction based on discriminative breast ultrasound image regions using deep feature extraction
Authors: Yu Hailong , Sun Hang , Li Jing , Shi Liying , Bao Nan , Li Hong , Qian Wei , Zhou Shi 
Published: March 2021

PurposeThis research aims to analyze the diagnostic contribution of different discriminative regions of the breast ultrasound image and develop a more effective diagnosis method taking advantage of the discriminative regions' complementarity.MethodsFirst, the discriminative regions of the original breast ultrasound image as the inner region of the lesion, the marginal zone of the lesion, and the posterior echo region of the lesion were defined. The pretrained Inception‐V3 network was used to analyze the diagnostic contribution of these discriminative regions. Then, the network was applied to extract the deep features of the original image and the other three discriminative region images. Since there are many features, principal components analysis (PCA) was used to reduce the dimensionality of the extracted deep features. The selected deep features from different discriminative regions were fused to original image features and sent to the stacking ensemble learning classifier for classification experiments. In this study, 479 cases of breast ultrasound images, including 356 benign lesions and 123 malignant ones, were collected retrospectively and randomly divided into the training and validation set.ResultsExperimental results show that by using Inception‐V3, the diagnostic performance of each discriminative region is different, and the diagnostic accuracy and the area under the ROC curve (AUC) of the lesion marginal zone image (78.3%, 0.798) are higher than those of the lesion inner region image (73.3%, 0.763) and the posterior echo region image (71.7%, 0.688), but lower than those of the original image (80.0%, 0.817). Furthermore, the best classification performance was obtained when all the four types of deep features (from the original image and three discriminative region images) were fused, and the ensemble learning for classification evaluation was employed. Compared with the original image, the classification accuracy and AUC increased from 80.83%, 0.818 to 85.00%, 0.872, and the classification sensitivity and specificity varied from 0.710, 0.798 to 0.871, 0.787.ConclusionsThe inner region of the lesion, the marginal zone of the lesion, and the posterior echo region of the lesion play significant roles in the diagnosis of the breast ultrasound image. Deep feature fusion of these three kinds of images and the original image can effectively improve the accuracy of diagnosis.
Three‐dimensional image volumes from two‐dimensional digitally reconstructed radiographs: A deep learning approach in lower limb CT scans
Authors: Almeida Diogo F. , Astudillo Patricio , Vandermeulen Dirk 
Published: March 2021

PurposeThree‐dimensional (3D) reconstructions of the human anatomy have been available for surgery planning or diagnostic purposes for a few years now. The different image modalities usually rely on several consecutive two‐dimensional (2D) acquisitions in order to reconstruct the 3D volume. Hence, such acquisitions are expensive, time‐demanding and often expose the patient to an undesirable amount of radiation. For such reasons, along the most recent years, several studies have been proposed that extrapolate 3D anatomical features from merely 2D exams such as x rays for implant templating in total knee or hip arthroplasties.MethodThe presented study shows an adaptation of a deep learning‐based convolutional neural network to reconstruct 3D volumes from a mere 2D digitally reconstructed radiograph from one of the most extensive lower limb computed tomography datasets available. This novel approach is based on an encoder‐decoder architecture with skip connections and a multidimensional Gaussian filter as data augmentation technique.ResultsThe results achieved promising values when compared against the ground truth volumes, quantitatively yielding an average of 0.77 ± 0.05 structured similarity index.ConclusionsA novel deep learning‐based approach to reconstruct 3D medical image volumes from a single x‐ray image was shown in the present study. The network architecture was validated against the original scans presenting SSIM values of 0.77 ± 0.05 and 0.78 ± 0.06, respectively for the knee and the hip crop.
Apparent exchange rate imaging: On its applicability and the connection to the real exchange rate
Authors: Ludwig Dominik , Laun Frederik Bernd , Ladd Mark Edward , Bachert Peter , Kuder Tristan Anselm 
Published: March 2021

PurposeWater exchange between the intracellular and extracellular space can be measured using apparent exchange rate (AXR) imaging. The aim of this study was to investigate the relationship between the measured AXR and the geometry of diffusion restrictions, membrane permeability, and the real exchange rate, as well as to explore the applicability of AXR for typical human measurement settings.MethodsThe AXR measurements and the underlying exchange rates were simulated using the Monte Carlo method with different geometries, size distributions, packing densities, and a broad range of membrane permeabilities. Furthermore, the influence of SNR and sequence parameters was analyzed.ResultsThe estimated AXR values correspond to the simulated values and show the expected proportionality to membrane permeability, except for fast exchange (ie, ) and small packing densities. Moreover, it was found that the duration of the filter gradient must be shorter than . In cell size and permeability distributions, AXR depends on the average surface‐to‐volume ratio, permeability, and the packing density. Finally, AXR can be reliably determined in the presence of orientation dispersion in axon‐like structures with sufficient gradient sampling (ie, 30 gradient directions).ConclusionCurrently used experimental settings for in vivo human measurements are well suited for determining AXR, with the exception of single‐voxel analysis, due to limited SNR. The detection of changes in membrane permeability in diseased tissue is nonetheless challenging because of the AXR dependence on further factors, such as packing density and geometry, which cannot be disentangled without further knowledge of the underlying cell structure.
Black‐Asian Solidarities and the Impasses of “How‐To” Anti‐racisms
Authors: Rubio Elizabeth Hanna 
Published: March 2021

AbstractDuring the 2020 summer of global uprisings in defense of Black life, widely circulated anti‐racist reading lists created heightened demand for books that promised to teach readers how to examine their internalized racism. Situated in U.S. racial liberalism’s extensive literary genealogy, anti‐racist “how‐to” literature has historically swooped in during moments of heightened racialized confusion to restore narratives of American exceptionalism. This literature sustains the tenuous promise that racism is something that one can challenge in interpersonal relationships and by following specific steps toward individualized behavior correction. Building on a broader body of work that has critiqued liberal anti‐racisms for detracting from abolitionst struggles against racialized injustice, this article specifically frames the limitations that “how‐to anti‐racisms” place on transgressive multiracial coalition building. Through ethnographic analysis of discourses and practices that move through various sites of contemporary Black‐Asian American activist encounters, I build on Black and radical women of color feminist theorizations of solidarity to show how “how‐tos” destabilize coalition building by overdetermining resolutions to conflict. I argue that in “settling” anti‐racism into a repertoire of predetermined steps, how‐to‐ism constrains the contradiction, anger, and uncertainty that is fundamental to forging the radical accountability central to abolitionist work.
“Stepping in the Gap to Make Family”: Care Calculation and Grandparent Caregiving in Detroit, Michigan
Authors: Richards Fayana 
Published: March 2021

AbstractScholars have long recognized the role that older Black American women play in providing care for their own grandchildren, nieces, nephews, and even non‐kin, arguing that kinship and caregiving relationships have been shaped by historical and structural factors. In this article, I consider intensive grandchild caregiving among Black American grandparents, primarily grandmothers, living in Detroit, Michigan. I highlight how the decision and process of providing care involves a “care calculation” where grandmothers evaluate their decision to caregive against existing financial, emotional, and bodily resources. In doing so, I argue that grandparent caregiving should be understood as a responsive and intentional process, where the decision to care for grandchildren and the performance of care work is more than simply responding to a set of certain circumstances and/or obligations based on biological kinship relations.
Potential Effects of Bigheaded Carps on Four Laurentian Great Lakes Food Webs
Authors: Rutherford Edward S. , Zhang Hongyan , Kao Yu-Chun , Mason Doran M. , Shakoor Ali , Bouma-Gregson Keith , Breck Jason T. , Lodge David M. , Chadderton W. Lindsay 
Published: March 2021

Abstract
Bigheaded carps (BHCs; Silver Carp Hypophthalmichthys molitrix and Bighead Carp H. nobilis) are economically and culturally important in Asia and Europe but are considered highly invasive throughout the Mississippi River watershed and pose a threat to the food web and fisheries of the Laurentian Great Lakes. We used the Ecopath with Ecosim model framework to evaluate potential risk of BHC population growth and food web effects in four Great Lakes habitats, including mesotrophic waters of Saginaw Bay (Lake Huron) and Lake Erie and the oligotrophic main basins of Lakes Michigan and Huron. We simulated BHC population growth and food web effects under different scenarios of BHC production rates, prey vulnerability to BHCs, and availability of age-0 BHCs to predation by salmonines. In the main basins of Lakes Michigan and Huron, the projected BHC population growth was low or negative, with a projected final BHC biomass of 0.5–1.1 times the initial introductory biomass (2% of total fish biomass for each BHC species), and BHCs had negligible effects on most food web groups across all scenarios. In contrast, in Saginaw Bay and Lake Erie, the projected BHC biomass was 2.5–12.5 times higher than the initial biomass across all scenarios, and the largest increases occurred under scenarios of high prey vulnerability to BHCs and high BHC production rates. High projected BHC biomass in Saginaw Bay and Lake Erie had negative effects on zooplankton and planktivorous fish groups and mixed effects on piscivores but had relatively negligible effects on most other food web groups across all scenarios. Our results are consistent with reported BHC effects on food webs in the Mississippi River and its tributaries and inform efforts to prevent BHC invasion of the Great Lakes.
Corrigendum 2 to: A geometric view of Krylov subspace methods on singular systems
Authors: Hayami Ken , Sugihara Kota 
Published: March 2021

AbstractIn [Hayami K, Sugihara M. Numer Linear Algebra Appl. 2011; 18:449–469], the authors analyzed the convergence behavior of the generalized minimal residual (GMRES) method for the least squares problem , where A ∈ Rn × n may be singular and , by decomposing the algorithm into the range and its orthogonal complement components. However, we found that the proof of the fact that GMRES gives a least squares solution if was not complete. In this article, we will give a complete proof.
Condition numbers for the truncated total least squares problem and their estimations
Authors: Meng Qing‐Le , Diao Huai‐An , Bai Zheng‐Jian 
Published: March 2021

AbstractIn this paper, we present explicit expressions for the mixed and componentwise condition numbers of the truncated total least squares (TTLS) solution of under the genericity condition, where A is a m × n real data matrix and is a real m‐vector. Moreover, we reveal that normwise, componentwise, and mixed condition numbers for the TTLS problem can recover the previous corresponding counterparts for the total least squares (TLS) problem when the truncated level of the TTLS problem is n. When A is a structured matrix, the structured perturbations for the structured truncated TLS (STTLS) problem are investigated and the corresponding explicit expressions for the structured normwise, componentwise, and mixed condition numbers for the STTLS problem are obtained. Furthermore, the relationships between the structured and unstructured normwise, componentwise, and mixed condition numbers for the STTLS problem are studied. We devise reliable condition estimation algorithms for the TTLS problem by utilizing small‐sample statistical condition estimation techniques. The proposed condition estimation algorithms employ the singular value decomposition (SVD) of the augmented matrix to reduce the computational complexity, where both unstructured and structured normwise, mixed, and componentwise condition estimations are considered. The proposed condition estimation algorithms can be integrated into the SVD‐based direct solver for the small and medium size TTLS problem to give the error estimation for the numerical TTLS solution. Numerical experiments are reported to illustrate the reliability of the proposed condition estimation algorithms.
An XFEM multilayered heaviside enrichment for fracture propagation with reduced enhanced degrees of freedom
Authors: Bybordiani Milad , Latifaghili Amir , Soares Delfim , Godinho Luis , Dias‐da‐Costa Daniel 
Published: March 2021

SummaryThe development of advanced numerical techniques such as eXtended/Generalized Finite Elements Methods (XFEM/GFEM) has provided means for accurate prediction of material failure. However, the present theories mostly rely on a global formulation, where the system of equations is subject to progressive dimension increase with crack evolution. In this regard, an independent multilayered enrichment is proposed for the XFEM/GFEM family of methods where a few elements in close proximity are assigned to an enrichment layer independent of the remaining ones. The enhanced degrees of freedom can be condensed out at the layer level, which leads to system dimensions, sparsity, and bandness identical to those of the underlying finite elements. Nodal and elemental enrichment methods are shown to be particular limit cases of present approach. The robustness of the proposed approach is first demonstrated in element‐level examples. The use of only few adjacent elements in a group enrichment is shown to suffice for acceptable results while the order of the condition number of the final stiffness matrix resembles the underlying uncracked finite element counterpart. Finally, using several structural examples, the accuracy and robustness of the method is shown in terms of force–displacement response, stress fields, and traction continuity in nonlinear problems.