bluuebunny/crossref_metadata_2025_split huggingface dataset:
Beyond probabilities: A possibilistic framework to interpret ensemble predictions and fuse imperfect sources of information
Authors: Le Carrer Noémie , Ferson Scott 
Published: July 2021

AbstractEnsemble forecasting is widely used in medium‐range weather predictions to account for the uncertainty that is inherent in the numerical prediction of high‐dimensional, nonlinear systems with high sensitivity to initial conditions. Ensemble forecasting allows one to sample possible future scenarios in a Monte‐Carlo‐like approximation through small strategical perturbations of the initial conditions, and in some cases stochastic parametrization schemes of the atmosphere–ocean dynamical equations. Results are generally interpreted in a probabilistic manner by turning the ensemble into a predictive probability distribution. Yet, due to model bias and dispersion errors, this interpretation is often not reliable and statistical postprocessing is needed to reach probabilistic calibration. This is all the more true for extreme events which, for dynamical reasons, cannot generally be associated with a significant density of ensemble members. In this work we propose a novel approach: a possibilistic interpretation of ensemble predictions, taking inspiration from possibility theory. This framework allows us to integrate in a consistent manner other imperfect sources of information, such as the insight about the system dynamics provided by the analogue method. We thereby show that probability distributions may not be the best way to extract the valuable information contained in ensemble prediction systems, especially for large lead times. Indeed, shifting to possibility theory provides more meaningful results without the need to resort to additional calibration, while maintaining or improving skills. Our approach is tested on an imperfect version of the Lorenz '96 model, and results for extreme event prediction are compared against those given by a standard probabilistic ensemble dressing.
Advances in carbon isotope analysis of trapped methane and volatile hydrocarbons in crystalline rock cores
Authors: Sanz‐Robinson Jethro , Brisco Trevor , Warr Oliver , Jabeen Iffat , Lacrampe‐Couloume Georges , Hanley Jacob J. , Sherwood Lollar Barbara 
Published: July 2021

RationaleThe isotopic composition of hydrocarbons trapped in rocks on the microscale (fluid inclusions, mineral grain boundaries, microfractures) can provide powerful information on geological and biological processes but are an analytical challenge due to low concentrations. We present a new approach for the extraction and carbon isotopic analysis of methane (CH4) and hydrocarbons in trapped volatiles in crystalline rocks.MethodsAn off‐line crusher with cryogenic trapping and a custom‐made silica glass U‐trap were attached to an external injector port on a continuous flow gas chromatograph/combustion/isotope ratio mass spectrometer to demonstrate the accuracy, reproducibility, and sensitivity of δ13C measurements for CH4.ResultsThe method can isotopically characterize CH4 in crushed rock samples with concentrations as low as 3.5 × 10−9 mol/g of rock, and both sample and isotopic standards are analyzed with an accuracy and reproducibility of ±0.5‰. High H2O/CH4 ratios of 98 to 500 have no effect on measured δ13CCH4 values. The method is successfully applied to natural samples from the north range of Sudbury Basin, Ontario, Canada. The δ13C isotopic signatures of CH4 trapped microscopically in rock from the north range overlap significantly with that of CH4 contained in larger scale flowing fracture fluids from the same part of the Sudbury Basin, indicating a potential genetic link.ConclusionsA novel method for δ13CCH4 analysis was developed for the extraction of nanomole quantities of CH4 trapped microscopically in rocks. The technique has an accuracy and reproducibility comparable to that of on‐line crushing techniques but importantly provides the capability of crushing larger rock quantities (up to 100 g). The benefit is improved detection levels for trace hydrocarbon species. Such a capability will be important for future extension of such crushing techniques for measurement of 2H/1H for CH4, clumped isotopologues of CH4 and other trapped volatiles species, such as C2H6, C3H8, C4H10, CO2 and N2.
Convergence analysis of the modified adaptive extended Kalman filter for the parameter estimation of a brushless DC motor
Authors: Ding Jie , Chen Lijuan , Cao Zhengxin , Guo Honghao 
Published: July 2021

AbstractThis article concentrates on the parameter estimation of brushless DC motor, where the stator current and winding back electromotive force are taken as the motor states, while the stator resistance and inductance are taken into consideration and augmented into the state vector. Based on this augmented model, a modified adaptive extended Kalman filter is proposed which updates the process noise covariance matrix in real time with the current input‐output data, and takes the state estimates by the traditional extended Kalman filter as one‐step estimation for the calculation of the covariance matrix. The convergence analysis is given to verify the theoretical results. Finally, the simulation results show that the proposed algorithm can effectively improve the estimation accuracy.
Enhancing the mechanical and hydraulic properties of coarse quartz sand using a water‐soluble hydrogel based on bacterial alginate for novel application in agricultural contexts
Authors: Barrientos‐Sanhueza Cesar , Mondaca Pedro , Tamayo Miguel , Álvaro Juan E. , Díaz‐Barrera Alvaro , Cuneo Italo F. 
Published: July 2021

AbstractClimate change is generating severe changes in the physical behavior of soils (i.e., soil structure, mechanical resistance, and water conductivity), causing negative impacts on different agricultural systems and, therefore, threatening food security. To cope with this situation, hydrogels based on biopolymers have been proposed to modify the mechanical and hydraulic behavior of complex porous materials such as soils, yet most of them are nonsoluble, making their application at field level laborious. In this study, we investigated the effect of a water‐soluble hydrogel based on bacterial alginate on the mechanical and hydraulic behavior of coarse quartz sand. The results from unconfined uniaxial compression test showed that the strength of the sand treated with hydrogel increased by 94.5%, whereas hydraulic conductivity decreased 33%. Interestingly, we observed that bacterial alginate and hydrogel shifted the mechanics of the fluid phase toward a Darcy regime. The aggregate stability tests showed that coarse quartz sand treated with hydrogel displays larger mean weight diameter, reaching 1.5 mm compared with 0.12 mm of the control (i.e., coarse quartz sand). Finally, transmission light microscopy imaging of the hydrogel treatment revealed a new three‐dimensional matrix between the quartz sand particles, changing the microaggregates and macroaggregates and providing a modified structure of the sand material. Our findings suggest that the use of the water‐soluble hydrogel improves the mechanical and hydraulic behavior of coarse quartz sand, allowing better soil conservation against climate change‐related phenomena, and is also potentially applicable in agricultural systems facing water scarcity.
SARS-CoV-2 Research Using Human Pluripotent Stem Cells and Organoids
Authors: Deguchi Sayaka , Serrano-Aroca Ángel , Tambuwala Murtaza M. , Uhal Bruce D. , Brufsky Adam M. , Takayama Kazuo 
Published: July 2021

Abstract
Experimental cell models are indispensable for clarifying the pathophysiology of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and for developing therapeutic agents. To recapitulate the symptoms and drug response of COVID-19 patients in vitro, SARS-CoV-2 studies using physiologically relevant human embryonic stem (ES)/induced pluripotent stem (iPS) cell-derived somatic cells and organoids are ongoing. These cells and organoids have been used to show that SARS-CoV-2 can infect and damage various organs including the lung, heart, brain, intestinal tract, kidney, and pancreas. They are also being used to develop COVID-19 therapeutic agents, including evaluation of their antiviral efficacy and safety. The relationship between COVID-19 aggravation and human genetic backgrounds has been investigated using genetically modified ES/iPS cells and patient-derived iPS cells. This review summarizes the latest results and issues of SARS-CoV-2 research using human ES/iPS cell-derived somatic cells and organoids.
Unit information prior for adaptive information borrowing from multiple historical datasets
Authors: Jin Huaqing , Yin Guosheng 
Published: July 2021

AbstractIn clinical trials, there often exist multiple historical studies for the same or related treatment investigated in the current trial. Incorporating historical data in the analysis of the current study is of great importance, as it can help to gain more information, improve efficiency, and provide a more comprehensive evaluation of treatment. Enlightened by the unit information prior (UIP) concept in the reference Bayesian test, we propose a new informative prior called UIP from an information perspective that can adaptively borrow information from multiple historical datasets. We consider both binary and continuous data and also extend the new UIP to linear regression settings. Extensive simulation studies demonstrate that our method is comparable to other commonly used informative priors, while the interpretation of UIP is intuitive and its implementation is relatively easy. One distinctive feature of UIP is that its construction only requires summary statistics commonly reported in the literature rather than the patient‐level data. By applying our UIP to phase III clinical trials for investigating the efficacy of memantine in Alzheimer's disease, we illustrate its ability to adaptively borrow information from multiple historical datasets. The Python codes for simulation studies and the real data application are available at https://github.com/JINhuaqing/UIP.
SERS Quantification of Galunisertib Delivery in Colorectal Cancer Cells by Plasmonic‐Assisted Diatomite Nanoparticles
Authors: Managò Stefano , Tramontano Chiara , Delle Cave Donatella , Chianese Giovanna , Zito Gianluigi , De Stefano Luca , Terracciano Monica , Lonardo Enza , De Luca Anna Chiara , Rea Ilaria 
Published: July 2021

AbstractThe small molecule Galunisertib (LY2157299, LY) shows multiple anticancer activities blocking the transforming growth factor‐β1 receptor, responsible for the epithelial‐to‐mesenchymal transition (EMT) by which colorectal cancer (CRC) cells acquire migratory and metastatic capacities. However, frequent dosing of LY can produce highly toxic metabolites. Alternative strategies to reduce drug side effects can rely on nanoscale drug delivery systems that have led to a medical revolution in the treatment of cancer, improving drug efficacy and lowering drug toxicity. Here, a hybrid nanosystem (DNP‐AuNPs‐LY@Gel) made of a porous diatomite nanoparticle decorated with plasmonic gold nanoparticles, in which LY is retained by a gelatin shell, is proposed. The multifunctional capability of the nanosystem is demonstrated by investigating the efficient LY delivery, the enhanced EMT reversion in CRCs and the intracellular quantification of drug release with a sub‐femtogram resolution by surface‐enhanced Raman spectroscopy (SERS). The LY release trigger is the pH sensitivity of the gelatin shell to the CRC acidic microenvironment. The drug release is real‐time monitored at single‐cell level by analyzing the SERS signals of LY in CRC cells. The higher efficiency of LY delivered by the DNP‐AuNPs‐LY@Gel complex paves the way to an alternative strategy for lowering drug dosing and consequent side effects.
A Dynamic Calibration Method for Injection‐Dependent Charge Carrier Lifetime Measurements
Authors: Zhu Yan , Trupke Thorsten , Hameiri Ziv 
Published: July 2021

AbstractCharge carrier lifetime is an important parameter for semiconductor materials. This study proposes a dynamic calibration method for injection‐dependent carrier lifetime measurements. This method is based on the comparison between lifetime measurements under quasi‐steady‐state and non‐quasi‐steady‐state conditions. The proposed method is first demonstrated by numerical simulation. Experimental data are subsequently used to compare the proposed method with conventional calibration methods, demonstrating good agreement between the methods. Furthermore, the calibration method is found to be much less sensitive to measurement noise. When applied to photoluminescence‐based carrier lifetime measurements, the proposed method also provides the net bulk doping concentration.
Prediction of network security situation awareness based on an improved model combined with neural network
Authors: Yuan Li 
Published: July 2021

AbstractPeople always pay attention to the security of the network. This paper mainly analyzed the problem of network security situation prediction (NSSP). The radial basis function neural network was improved by the particle swarm optimization algorithm, and a modified particle swarm optimization‐radial basis function algorithm was obtained, which was used as the prediction model. Then, the data from National Internet Emergency Center were used as the experimental data, and the modified particle swarm optimization‐radial basis function algorithm was compared with radial basis function and particle swarm optimization‐radial basis function algorithms. The results showed that the modified particle swarm optimization‐radial basis function algorithm could achieve convergence in about 50 times of iterations, showing a high calculation efficiency and a short operation time, and the mean absolute percentage error value, mean square error value, and root‐mean‐square error value were small (2.13%, 0.0005, and 0.0224), showing that the algorithm had good prediction performance. The results verify the reliability of the modified particle swarm optimization‐radial basis function algorithm in NSSP, which is conducive to further improve network security.
Modeling damage behavior of concrete subjected to cyclic and multiaxial loading conditions
Authors: Monnamitheen Abdul Gafoor Ajmal Hasan , Dinkler Dieter 
Published: July 2021

AbstractConcrete exhibits a different deformation behavior in tension and compression when subjected to uniaxial and biaxial loads. It also reveals crack‐opening and crack‐closing effects under cyclic loads. This paper discusses a gradient‐enhanced continuum damage model to investigate the deformation and damage behavior of concrete subjected to cyclic and multiaxial loading conditions. An activating variable introduced in the model distinguishes the multiaxial stress states. A single damage criterion that relates the history variable to the equivalent strain limits the elastic domain. The evolution of internal variables confirms their thermodynamic consistency. The gradient enrichment of equivalent strains leads to proper localization of deformation. Comparison of numerical predictions with relevant experimental data and some previous models validates the capability of the model to describe softening/crack‐closure behavior under various loading. Application of the model to fracture problems demonstrates the ability of the model to describe damage initiation and propagation, and its localization.
Overview of campus‐wide essential learning outcomes pilot, implementation, and assessment at Stockton University, 2010–2021
Authors: Hood Carra Leah 
Published: July 2021

AbstractIn this article, the author discusses the multi‐year implementation of essential learning outcomes at Stockton University. The implementation process included strategies for generating faculty buy‐in, creation of a University‐wide steering committee, facilitating summer workshops, and planning for assessment.
Pedagogical intersections: ePortfolio practice and essential learning outcomes for 21st century success
Authors: Lehman Regina M. , Mills Michele D. , Gupta Richa , Calderon Olga 
Published: July 2021

AbstractePortfolio practice and assessment of essential learning outcomes (ELOs) are well established at LaGuardia Community College (LAGCC). The way in which these practices intersect is via the assessment of authentic student artifacts generated from assignments aligned with ELOs. Student artifacts are deposited into the Core ePortfolio for college‐wide assessment. Benchmark reading data is used to inform ePortfolio practice and pedagogy at the college‐wide and programmatic levels. General Education Core Competencies and Communication Abilities are established across the College and are an integral part of curricular frameworks in all majors. The Core Competencies—Inquiry and Problem Solving, Integrative Learning, and Global Learning—are expressed through the Oral, Written, and Digital Communication Abilities. ePortfolio practice lends itself to the examination of Integrative Learning and Digital Communication. Recognizing ePortfolio as a high‐impact practice, LAGCC developed the Core ePortfolio as a platform for student active engagement in self‐directed learning and reflection about themselves as learners over their entire curricular and co‐curricular experience. Faculty gain a deepened understanding of the student experience and the process of integrative learning.
Training set design in genomic prediction with multiple biparental families
Authors: Zhu Xintian , Leiser Willmar L. , Hahn Volker , Würschum Tobias 
Published: July 2021

AbstractGenomic selection is a powerful tool to reduce the cycle length and enhance the genetic gain of complex traits in plant breeding. However, questions remain about the optimum design and composition of the training set. In this study, we used 944 soybean [Glycine max (L.) Merr.] recombinant inbred lines from eight families derived through a partial–diallel mating design among five parental lines. The cross‐validated prediction accuracies for the six traits seed yield, 1,000‐seed weight, protein yield, plant height, protein content, and oil content were high, ranging from 0.79 to 0.87. We investigated among‐family predictions, making use of the special mating design with different degrees of relatedness among families. Generally, the prediction accuracy decreased from full‐sibs to half‐sib families to unrelated families. However, half‐sib and unrelated families also showed substantial variation in their prediction accuracy for a given family, which appeared to be caused at least in part by the shared segregation of quantitative trait loci in both the training and prediction sets. Combining several half‐sib families in composite training sets generally led to an increase in the prediction accuracy compared with the best family alone. The prediction accuracy increased with the size of the training set, but for comparable prediction accuracy, substantially more half‐sibs were required than full‐sibs. Collectively, our results highlight the potential of genomic selection for soybean breeding and, in a broader context, illustrate the importance of the targeted design of the training set.
End‐to‐end anastomosis of the common bile duct and cholecystoduodenostomy for the treatment of extrahepatic cholangiocarcinoma in an 11‐year‐old cat
Authors: Jifcovici Alexandra , Caraty Johan , Vincken Gaëlle , Bongartz Alexandre 
Published: July 2021

AbstractAn 11‐year‐old cat presented with a 10‐day history of anorexia and jaundice. Diagnostic examinations showed hyperbilirubinemia, dilatation of the bile ducts and a mural mass in the common bile duct. Cholecystoduodenostomy, mass resection and end‐to‐end anastomosis of the common bile duct were performed. Histopathology revealed a well‐differentiated cholangiocarcinoma. The cat improved clinically and had a good quality of life for 16 months prior to disease recurrence. Liver biopsy indicated metastasis of the primary tumour. Euthanasia was elected. Cholangiocarcinoma in cats is considered to have a poor prognosis with high rate of metastasis. Given the paucity of information in the veterinary literature and the lack of specific prognostic indicators, guidelines for feline cholangiocarcinoma management have not been fully established. This clinical case report describes an acceptable outcome after tumour resection and biliary diversion in an 11‐year‐old cat with extrahepatic cholangiocarcinoma and no pre‐existing metastases.
Engineering of Biological Pathways: Complex Formation and Signal Transduction
Authors: Junk Philipp , Kiel Christina 
Published: July 2021

AbstractThe rational in silico design of interface mutations within protein complexes is a synthetic biology tool that enables—when introduced into biological systems—the artificial rewiring of biological pathways. Here we describe the three-dimensional structure-based design of “rewiring” mutations using the FoldX force field. Specifically, we provide the protocol for the design and selection of interface mutations in three Ras-effector complex structures (PDB entries 3KUD, 4K81, and 6AMB). Ras mutations that impair binding to some but not all interacting partners are selected.
Modulus τ linking leptonic CP violation to baryon asymmetry in A4 modular invariant flavor model
Authors: Okada Hiroshi , Shimizu Yusuke , Tanimoto Morimitsu , Yoshida Takahiro 
Published: July 2021

Abstract
We propose an A4 modular invariant flavor model of leptons, in which both CP and modular symmetries are broken spontaneously by the vacuum expectation value of the modulus τ. The value of the modulus τ is restricted by the observed lepton mixing angles and lepton masses for the normal hierarchy of neutrino masses. The predictive Dirac CP phase δCP is in the ranges [0°, 50°], [170°, 175°] and [280°, 360°] for Re [τ] < 0, and [0°, 80°], [185°, 190°] and [310°, 360°] for Re [τ] > 0. The sum of three neutrino masses is predicted in [60, 84] meV, and the effective mass for the 0νββ decay is in [0.003, 3] meV. The modulus τ links the Dirac CP phase to the cosmological baryon asymmetry (BAU) via the leptogenesis. Due to the strong wash-out effect, the predictive baryon asymmetry YB can be at most the same order of the observed value. Then, the lightest right-handed neutrino mass is restricted in the range of M1 = [1.5, 6.5] × 1013 GeV. We find the correlation between the predictive YB and the Dirac CP phase δCP. Only two predictive δCP ranges, [5°, 40°] (Re [τ] > 0) and [320°, 355°] (Re [τ] < 0) are consistent with the BAU.
Spin polarization induced by the hydrodynamic gradients
Authors: Liu Shuai Y. F. , Yin Yi 
Published: July 2021

Abstract
We systematically analyze the effects of the derivatives of the hydrodynamic fields on axial Wigner function that describes the spin polarization vector in phase space. We have included all possible first-order derivative contributions that are allowed by symmetry and compute the associated transport functions at one-loop using the linear response theory. In addition to reproducing known effects due to the temperature gradient and vorticity, we have identified a number of potentially significant contributions that are overlooked previously. In particular, we find that the shear strength, the symmetric and traceless part of the flow gradient, will induce a quadrupole for spin polarization in the phase space. Our results, together with hydrodynamic gradients obtained from hydrodynamic simulations, can be employed as a basis for the interpretation of the Λ (anti-Λ) spin polarization measurement in heavy-ion collisions.