bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical approximation of a nonisothermal two‐dimensional general rate model of reactive liquid chromatography
Authors: Uche Ugochukwu David , Qamar Shamsul , Seidel‐Morgenstern Andreas 
Published: December 2019

AbstractA nonlinear and nonisothermal two‐dimensional general rate model is formulated and approximated numerically to allow quantitatively analyzing the effects of temperature variations on the separations and reactions in liquid chromatographic reactors of cylindrical geometry. The model equations form a nonlinear system of convection‐diffusion‐reaction partial differential equations coupled with algebraic equations for isotherms and reactions. A semidiscrete high‐resolution finite volume method is modified to approximate the system of partial differential equations. The coupling between the thermal waves and concentration fronts is demonstrated through numerical simulations, and important parameters are pointed out that influence the reactor performance. To evaluate the precision of the model predictions, consistency checks are successfully carried out proving the accuracy of the predictions. The results allow to quantify the influence of thermal effects on the performance of the fixed beds for different typical values of enthalpies of adsorption and reaction and axial and radial Peclet numbers for mass and heat transfer. Furthermore, they provide useful insight into the sensitivity of nonisothermal chromatographic reactor operation.
Accelerating iterative coordinate descent using a stored system matrix
Authors: Hsieh Scott S. , Hoffman John M. , Noo Frederic 
Published: December 2019

PurposeThe computational burden associated with model‐based iterative reconstruction (MBIR) is still a practical limitation. Iterative coordinate descent (ICD) is an optimization approach for MBIR that has sometimes been thought to be incompatible with modern computing architectures, especially graphics processing units (GPUs). The purpose of this work is to accelerate the previously released open‐source FreeCT_ICD to include GPU acceleration and to demonstrate computational performance with ICD that is comparable with simultaneous update approaches.MethodsFreeCT_ICD uses a stored system matrix (SSM), which precalculates the forward projector in the form of a sparse matrix and then reconstructs on a rotating coordinate grid to exploit helical symmetry. In our GPU ICD implementation, we shuffle the sinogram memory ordering such that data access in the sinogram coalesce into fewer transactions. We also update NS voxels in the xy‐plane simultaneously to improve occupancy. Conventional ICD updates voxels sequentially (NS = 1). Using NS > 1 eliminates existing convergence guarantees. Convergence behavior in a clinical dataset was therefore studied empirically.ResultsOn a pediatric dataset with sinogram size of 736 × 16 × 13860 reconstructed to a matrix size of 512 × 512 × 128, our code requires about 20 s per iteration on a single GPU compared to 2300 s per iteration for a 6‐core CPU using FreeCT_ICD. After 400 iterations, the proposed and reference codes converge within 2 HU RMS difference (RMSD). Using a wFBP initialization, convergence within 10 HU RMSD is achieved within 4 min. Convergence is similar with NS values between 1 and 256, and NS = 16 was sufficient to achieve maximum performance. Divergence was not observed until NS > 1024.ConclusionsWith appropriate modifications, ICD may be able to achieve computational performance competitive with simultaneous update algorithms currently used for MBIR.
Calibration‐free beam hardening reduction in x‐ray CBCT using the epipolar consistency condition and physical constraints
Authors: Würfl Tobias , Hoffmann Mathis , Aichert André , Maier Andreas K. , Maaß Nicole , Dennerlein Frank 
Published: December 2019

BackgroundThe beam hardening effect is a typical source of artifacts in x‐ray cone beam computed tomography (CBCT). It causes streaks in reconstructions and corrupted Hounsfield units toward the center of objects, widely known as cupping artifacts.PurposeWe present a novel efficient projection data‐based method for reduction of beam‐hardening artifacts and incorporate physical constraints on the shape of the compensation functions. The method is calibration‐free and requires no additional knowledge of the scanning setup.MethodThe mathematical model of the beam hardening effect caused by a single material is analyzed. We show that the effect of beam hardening on the resulting functions on the line integral measurements are monotonous and concave functions of the ideal data. This holds irrespective of any limiting assumptions on the energy dependency of the material, the detector response or properties of the x‐ray source. A regression model for the beam hardening effect respecting these theoretical restrictions is proposed. Subsequently, we present an efficient method to estimate the parameters of this model directly in projection domain using an epipolar consistency condition. Computational efficiency is achieved by exploiting the linearity of an intermediate function in the formulation of our optimization problem.ResultsOur evaluation shows that the proposed physically constrained ECC algorithm is effective even in challenging measured data scenarios with additional sources of inconsistency.ConclusionsThe combination of mathematical consistency condition and a compensation model that is based on the properties of x‐ray physics enables us to improve image quality of measured data retrospectively and to decrease the need for calibration in a data‐driven manner.
One network to solve all ROIs: Deep learning CT for any ROI using differentiated backprojection
Authors: Han Yoseob , Ye Jong Chul 
Published: December 2019

PurposeComputed tomography for the reconstruction of region of interest (ROI) has advantages in reducing the x‐ray dose and the use of a small detector. However, standard analytic reconstruction methods such as filtered back projection (FBP) suffer from severe cupping artifacts, and existing model‐based iterative reconstruction methods require extensive computations. Recently, we proposed a deep neural network to learn the cupping artifacts, but the network was not generalized well for different ROIs due to the singularities in the corrupted images. Therefore, there is an increasing demand for a neural network that works well for any ROI size.MethodTwo types of neural networks are designed. The first type learns ROI size‐specific cupping artifacts from FBP images, whereas the second type network is for the inversion of the truncated Hilbert transform from the truncated differentiated backprojection (DBP) data. Their generalizabilities for different ROI sizes, pixel sizes, detector pitch and starting angles for a short scan are then investigated.ResultsExperimental results show that the new type of neural networks significantly outperform existing iterative methods for all ROI sizes despite significantly lower runtime complexity. In addition, performance improvement is consistent across different acquisition scenarios.ConclusionsSince the proposed method consistently surpasses existing methods, it can be used as a general CT reconstruction engine for many practical applications without compromising possible detector truncation.
A two‐dimensional feasibility study of deep learning‐based feature detection and characterization directly from CT sinograms
Authors: De Man Quinten , Haneda Eri , Claus Bernhard , Fitzgerald Paul , De Man Bruno , Qian Guhan , Shan Hongming , Min James , Sabuncu Mert , Wang Ge 
Published: December 2019

Machine Learning, especially deep learning, has been used in typical x‐ray computed tomography (CT) applications, including image reconstruction, image enhancement, image domain feature detection and image domain feature characterization. To our knowledge, this is the first study on machine learning for feature detection and analysis directly based on CT projection data. Specifically, we present neural network methods for blood vessel detection and characterization in the sinogram domain avoiding any partial volume, beam hardening, or motion artifacts introduced during reconstruction. First, we estimate sinogram domain vessel maps using a residual encoder–decoder convolutional neural network (REDCNN). Next, we estimate the vessel centerline and we extract the vessel‐only sinogram from the original sinogram, eliminating any background information. Finally, we use a fully connected neural network to estimate the vessel lumen cross‐sectional area from the vessel‐only sinogram. We trained and tested the proposed methods using CatSim simulations, real CT measurements of vessel phantoms, and clinical data from the NIH CT image database. We achieved encouraging initial results showing the feasibility of CT analysis in the sinogram domain. In principle, sinogram domain analysis should be possible for many other and more complicated clinical CT analysis tasks. Further studies are needed for this sinogram domain analysis approach to become practical for clinical applications.
Randomized controlled trial of a clinical decision support system for painful polyneuropathy
Authors: Reynolds Evan L. , Burke James F. , Banerjee Mousumi , Callaghan Brian C. 
Published: December 2019

AbstractIntroductionDespite the existence of guidelines, painful neuropathy is often inappropriately treated. We sought to determine the effectiveness of a clinical decision support system on guideline‐recommended medication use.MethodsWe randomized neurology providers, stratified by subspecialty, to a best practice alert (BPA) linked to a Smartset or a BPA alone when seeing patients with neuropathy. The primary outcome was the proportion of patients with uncontrolled nerve pain prescribed a guideline‐recommended medication. Generalized estimating equations were used to assess effectiveness.ResultsSeventy‐five neurology providers (intervention 38, control 37) treated 2697 patients with neuropathy (intervention 1026, control 671). Providers did not acknowledge the BPA in 1928 (71.5%) visits. Only four of eight intervention arm neurologists who treated patients with uncontrolled nerve pain opened the Smartset. The intervention was not associated with guideline‐recommended medication use (odds ratio 0.52, 0.18‐1.48; intervention 52%, control 54.8%).DiscussionOur intervention did not improve prescribing practices for painful neuropathy. Physicians typically ignored the BPAs/Smartset; therefore, future studies should mandate their use or employ alternate strategies.
Regions of the brain activated in bladder filling vs rectal distention in healthy adults: A meta‐analysis of neuroimaging studies
Authors: Halani Priyanka Kadam , Andy Uduak U. , Rao Hengyi , Arya Lily A. 
Published: December 2019

AbstractAimsAdults with pelvic floor disorders commonly present with overlapping bladder and bowel symptoms; however, the relationship between urinary and defecatory dysfunction is not well understood. Our aim was to compare and determine if overlapping brain regions are activated during bladder filling and rectal distention in healthy adults.MethodsWe conducted separate Pubmed searches for neuroimaging studies investigating the effects of rectal distention and bladder filling on brain activation in healthy subjects. Coordinates of activated regions were extracted with cluster‐level threshold P < .05 and compared using the activation likelihood estimate approach. Results from the various studies were pooled and a contrast analysis was performed to identify any common areas of activation between bladder filling and rectal distension.ResultsWe identified 96 foci of activation from 14 neuroimaging studies on bladder filling and 182 foci from 17 studies on rectal distension in healthy adults. Regions activated during bladder filling included right insula, right and left thalamus, and right periaqueductal grey. Regions activated during rectal distention included right and left insula, right and left thalamus, left postcentral gyrus, and right inferior parietal lobule. Contrast analysis revealed common activation of the right insula with both rectal distention and bladder filling.ConclusionBladder filling and rectal distention activate several separate areas of the brain involved in sensory processing in healthy adults. The common activation of the insula, the region responsible for interoception, in these two conditions may offer an explanation for the coexistence of bladder and defecatory symptoms in pelvic floor disorders.
Synergistic effects of rubber band infused graphene nanocomposite on morphology, spectral, and dynamic mechanical properties
Authors: Kamaruddin Nurul Hazierah , Marlinda Ab Rahman , Said Mardhiah , Abd Wahab Fadilah , Tong Goh Boon , Hamizi Nor Aliya , Chowdhury Zaira Zaman , Sagadevan Suresh , Johan Mohd Rafie 
Published: December 2019

AbstractRubber band/graphene (RBG) nanocomposites are formed by infusing graphene nanosheet into a rubber band (RB) and subsequently evaporating the solvent. The RB was first pretreated by soaking in toluene solvent in a mild sonication for 3 h before the swollen RB was immersed in graphene dispersion for different time periods of 12 and 20 h. Employing this technique, graphene nanosheets will be attached in the RB matrix to increase the mechanical properties of these nanocomposites. The peaks shifting of RBG composites noted from Fourier‐transform infrared and Raman analyses due to the stress transfer that indicates reinforcement of the graphene nanosheet. Also, dynamic mechanical testing is most useful for studying the viscoelastic behavior of the nanocomposites, which exhibits increasing storage modulus in the following order, RB < RBG‐12h < RBG‐20h and higher shifting of tan δ peak temperature for RBG‐12h and RBG‐20h. The main factor is due to the introduction of graphene content in the RB matrix. The improvement of RB/graphene composite in terms of their mechanical, electrical, and structural properties demonstrated promising candidates for low heat build‐up materials, improved wear resistance and thermal stability, increase significant gas impermeability, and electricity conductivity.
Proteomics Analysis of Candida albicans dnm1 Haploid Mutant Unraveled the Association between Mitochondrial Fission and Antifungal Susceptibility
Authors: Truong Thuyen , Zeng Guisheng , Lim Teck Kwang , Cao Tong , Pang Li Mei , Lee Yew Mun , Lin Qingsong , Wang Yue , Seneviratne Chaminda Jayampath 
Published: December 2019

AbstractCandida albicans is a major fungal pathogen, accounting for approximately 15% of healthcare infections with associated mortality as high as 40% in the case of systemic candidiasis. Antifungal agents for C. albicans infections are limited, and rising resistance is an inevitable problem. Therefore, understanding the mechanism behind antifungal responses is among the top research focuses in combating Candida infections. Herein, the recently developed C. albicans haploid model is employed to examine the association between mitochondrial fission, regulated by Dnm1, and the pathogen's response to antifungals. Proteomic analysis of dnm1Δ and its wild‐type haploid parent, GZY803, reveal changes in proteins associated with mitochondrial structures and functions, cell wall, and plasma membrane. Antifungal susceptibility testing revealed that dnm1Δ is more susceptible to SM21, a novel antifungal, than GZY803. Analyses of reactive oxygen species release, antioxidant response, lipid peroxidation, and membrane damages uncover an association between dnm1Δ and the susceptibility to SM21. Dynasore‐induced mitochondrial inhibition in SC5314 diploids corroborate the findings. Interestingly, Dynasore‐primed SC5314 cultures exhibit increased susceptibility to all antifungals tested. These data suggest an important contribution of mitochondrial fission in antifungal susceptibility of C. albicans. Hence, mitochondrial fission can be a potential target for combined therapy in anti‐C. albicans treatment.
A review and meta‐analysis of the epidemiology and clinical presentation of coxsackievirus A6 causing hand‐foot‐mouth disease in China and global implications
Authors: Zhao Tian‐Shuo , Du Juan , Sun Da‐Peng , Zhu Quan‐Rong , Chen Lin‐Yi , Ye Chen , Wang Shuai , Liu Ya‐Qiong , Cui Fuqiang , Lu Qing‐Bin 
Published: December 2019

SummaryCoxsackievirus A6 (CV‐A6) has been associated with increasingly occurred sporadic hand‐foot‐mouth disease (HFMD) cases and outbreak events in many countries. In order to understand epidemiological characteristics of CV‐A6, we collected the information describing HFMD caused by CV‐A6 to describe the detection rate, severe rate and onychomadesis rate, which is defined as one or more nails defluvium, caused by CV‐A6 from 2007 to 2017. The results showed that there was an outbreak of CV‐A6 every other year, and overall trend of the epidemic of CA6‐associated HFMD was increasing in China. The detection rate of CV‐A6 in other countries was 32.0% (95% CI: 25.0%~40.0%) before 2013 and 28.0% (95% CI: 20.0%~36.0%) after 2013, respectively. Although the severe rate of HFMD caused by CV‐A6 was low (0.10%, 95% CI: 0.01%~0.20%), CV‐A6 can cause a high incidence of onychomadesis (28.0%, 95%CI: 21.9%‐34.3%). Thus, it would be worthwhile to research and develop an effective multivalent vaccine for CV‐A6 to achieve a more powerful prevention of HMFD.
“We're taking their brilliant minds”: Science teacher expertize, meta‐discourse, and the challenges of teacher–scientist collaboration
Authors: Shanahan Marie‐Claire , Bechtel Robert 
Published: December 2019

AbstractPrograms that bring teachers and scientists together have continued to achieve attention as important potential contributions to science education. Often, however, those programs place teachers in the position of learner or apprentice to the scientists. This study examines a teacher–scientist partnership program (two project sites, two teachers and one scientist at each) that explicitly sought to challenge that model, bringing science teachers into science labs to share their expertize in a collaborative project. Using a framework that probes both the actors’ and analysts’ perspectives on expertize, this study examines whether the promise of the program's goal for mutual learning through collaboration can be met. Analysis of interviews and collaborative products focused on evidence of contributory and interactional expertize to understand if the project was able to bring together a group that was likely to be able to collaborate successfully. Metadiscourse was then probed to gain a deeper understanding of the ways in which they spoke of the expertize of their collaborators. Findings suggest that creating collaborative teams with ideal expertize matches is challenging and that collaborative efforts are complicated by the historic status of scientific and teaching expertizes especially in relation to outreach or knowledge translation projects.
The epsilon expansion meets semiclassics
Authors: Badel Gil , Cuomo Gabriel , Monin Alexander , Rattazzi Riccardo 
Published: December 2019

AbstractWe study the scaling dimension$$ {\Delta}_{\phi^n} $$Δϕnof the operator 𝜙nwhere 𝜙 is the fundamental complex field of the U(1) model at the Wilson-Fisher fixed point ind= 4− ε. Even for a perturbatively small fixed point couplingλ∗, standard perturbation theory breaks down for sufficiently largeλ∗n. Treatingλ∗nas fixed for smallλ∗we show that$$ {\Delta}_{\phi^n} $$Δϕncan be successfully computed through a semiclassical expansion around a non-trivial trajectory, resulting in$$ {\Delta}_{\phi^n}=\frac{1}{\lambda_{\ast }}{\Delta}_{-1}\left({\lambda}_{\ast }n\right)+{\Delta}_0\left({\lambda}_{\ast }n\right)+{\lambda}_{\ast }{\Delta}_1\left({\lambda}_{\ast }n\right)+\dots $$Δϕn=1λ∗Δ−1λ∗n+Δ0λ∗n+λ∗Δ1λ∗n+…We explicitly compute the first two orders in the expansion, ∆−1(λ∗n) and ∆0(λ∗n). The result, when expanded at smallλ∗n, perfectly agrees with all available diagrammatic com- putations. The asymptotic at largeλ∗nreproduces instead the systematic large charge expansion, recently derived in CFT. Comparison with Monte Carlo simulations ind= 3 is compatible with the obvious limitations of takingε= 1, but encouraging.
Ricci-Based Gravity theories and their impact on Maxwell and nonlinear electromagnetic models
Authors: Delhom Adria , Olmo Gonzalo J. , Orazi Emanuele 
Published: December 2019

Abstract
We extend the correspondence between metric-affine Ricci-Based Gravity the- ories and General Relativity (GR) to the case in which the matter sector is represented by linear and nonlinear electromagnetic fields. This complements previous studies focused on fluids and scalar fields. We establish the general algorithm that relates the matter fields in the GR and RBG frames and consider some applications. In particular, we find that the so-called Eddington-inspired Born-Infeld gravity theory coupled to Maxwell electromag- netism is in direct correspondence with GR coupled to Born-Infeld electromagnetism. We comment on the potential phenomenological implications of this relation.
The 4-CB algebra and solvable lattice models
Authors: Belavin Vladimir , Gepner Doron , Li Jian-Rong , Tessler Ran 
Published: December 2019

Abstract
We study the algebras underlying solvable lattice models of the type fusion interaction round the face (IRF). We propose that the algebras are universal, depending only on the number of blocks, which is the degree of polynomial equation obeyed by the Boltzmann weights. Using the Yang-Baxter equation and the ansatz for the Baxterization of the models, we show that the three blocks models obey a version of Birman-Murakami­Wenzl (BMW) algebra. For four blocks, we conjecture that the algebra, which is termed 4-CB (Conformal Braiding) algebra, is the BMW algebra with a different skein relation, along with one additional relation, and we provide evidence for this conjecture. We connect these algebras to knot theory by conjecturing new link invariants. The link invariants, in the case of four blocks, depend on three arbitrary parameters. We check our result for G2 model with the seven dimensional representation and for SU(2) with the isospin 3/2 representation, which are both four blocks theories.
Fakeons, unitarity, massive gravitons, and the cosmological constant
Authors: Anselmi Damiano 
Published: December 2019

AbstractWe give a simple proof of perturbative unitarity in gauge theories and quantum gravity using a special gauge that allows us to separate the physical poles of the free propagators, which are quantized by means of the Feynman prescription, from the poles that belong to the gauge-trivial sector, which are quantized by means of the fakeon prescription. The proof applies to renormalizable theories, including the ultraviolet complete theory of quantum gravity with fakeons formulated recently, as well as low-energy (nonrenormalizable) theories. We clarify a number of subtleties related to the study of scattering processes in the presence of a cosmological constant Λ. The scattering ampli- tudes, defined by expanding the metric around flat space, obey the optical theorem up to corrections due to Λ, which are negligible for all practical purposes. Problems of interpretation would arise if such corrections became important. In passing, we obtain local, unitary (and “almost” renormalizable) theories of massive gravitons and gauge fields, which violate gauge invariance and general covariance explicitly.