bluuebunny/crossref_metadata_2025_split huggingface dataset:
The immune components ENHANCED DISEASE SUSCEPTIBILITY 1 and PHYTOALEXIN DEFICIENT 4 are required for cell death caused by overaccumulation of ceramides in Arabidopsis
Authors: Zeng Hong‐Yun , Liu Yu , Chen Ding‐Kang , Bao He‐Nan , Huang Li‐Qun , Yin Jian , Chen Yi‐Li , Xiao Shi , Yao Nan 
Published: June 2021

SUMMARYSphingolipids have key functions in plant membrane structure and signaling. Perturbations of plant sphingolipid metabolism often induce cell death and salicylic acid (SA) accumulation; SA accumulation, in turn, promotes sphingolipid metabolism and further cell death. However, the underlying molecular mechanisms remain unclear. Here, we show that the Arabidopsis thaliana lipase‐like protein ENHANCED DISEASE SUSCEPTIBILITY 1 (EDS1) and its partner PHYTOALEXIN DEFICIENT 4 (PAD4) participate in sphingolipid metabolism and associated cell death. The accelerated cell death 5 (acd5) mutants accumulate ceramides due to a defect in ceramide kinase and show spontaneous cell death. Loss of function of EDS1, PAD4 or SALICYLIC ACID INDUCTION DEFICIENT 2 (SID2) in the acd5 background suppressed the acd5 cell death phenotype and prevented ceramide accumulation. Treatment with the SA analogue benzothiadiazole partially restored sphingolipid accumulation in the acd5 pad4 and acd5 eds1 double mutants, showing that the inhibitory effect of the pad4‐1 and eds1‐2 mutations on acd5‐conferred sphingolipid accumulation partly depends on SA. Moreover, the pad4‐1 and eds1‐2 mutations substantially rescued the susceptibility of the acd5 mutant to Botrytis cinerea. Consistent with this, B. cinerea‐induced ceramide accumulation requires PAD4 or EDS1. Finally, examination of plants overexpressing the ceramide synthase gene LAG1 HOMOLOGUE2 suggested that EDS1, PAD4 and SA are involved in long‐chain ceramide metabolism and ceramide‐associated cell death. Collectively, our observations reveal that EDS1 and PAD4 mediate ceramide (especially long‐chain ceramide) metabolism and associated cell death, by SA‐dependent and SA‐independent pathways.
Mesophyll conductance variability of rice aquaporin knockout lines at different growth stages and growing environments
Authors: Huang Xianhong , Wang Zhixin , Huang Jianliang , Peng Shaobing , Xiong Dongliang 
Published: June 2021

SUMMARYThe plasma membrane subfamily of aquaporins [plasma membrane intrinsic proteins (PIPs)], which facilitates the CO2 diffusion across membranes, is proposed to play an important role in mesophyll conductance to CO2 (gm), a major limiting factor of photosynthesis. However, recent studies implied no causal relationship between gm and PIPs because they failed to repeat the previous observed differences in gm between PIP knockout lines and their wild‐type. The contrasting results on the role of PIPs in gm were interpreted as the different growth conditions among studies, which has never been tested. Here, we assessed whether the differences in gm between wild‐type and PIP knockout lines, Ospip1;1, Ospip1;2 and Ospip2;1, varied with growth condition (field versus pot condition) and growth stages in rice. Under field conditions, no differences were observed in plant performance, photosynthetic rate (A) and gm between PIP knockout lines and the wild‐type. However, in agreement with previous studies, two out of three knockout lines showed significant declines in tiller number, plant height, A and gm under pot conditions. Moreover, we found that the differences in A and gm between PIP knockout lines and the wild‐type varied with the growth stage of the plants. Our results showed that the differences in gm between PIP knockout lines and wild‐type were depending on the growth environments and stage of the plants, and further efforts are required to reveal the underlying mechanisms.
Multilingual legal practice and law student internships in Malaysia
Authors: Powell Richard , Saw Tiong Guan 
Published: June 2021

AbstractMediated through hierarchical domestic institutions and a global system of jurisprudence that tends to view older jurisdictions as more authentic or authoritative legal sources, the language of common law is seldom explored through a world Englishes lens, but Malaysian law has opened up possibilities for indigenised and pluricentric common law by its use of Malay alongside English. While some studies have examined bilingualism in Malaysian public courtrooms, few have looked into the less accessible spaces of law office practice. This study investigates bilingual legal practice through the experiences of law students undertaking professional internships at various institutions nationwide. Although some sectors lean toward one language more than the other, most students reported intense and dynamic patterns of bilingualism. The findings offer scope for research specifically into Malaysian legal English from a language contact perspective.
Prediction of Yield Strength of Selective Laser Melted Ti–6Al–4V Alloy Using Melt Pool Geometry
Authors: Mahdavi Mostafa , Liang Steven , Garmestani Hamid 
Published: June 2021

Abstract
Additive manufacturing (AM) method has attracted huge interest in the past decade due to its ability in building complicated geometries with a much lower cost than conventionally produced parts. In AM, the final mechanical properties can be controlled by the AM process parameters. In other words, the AM process parameters control the amount of energy that is transferred into the powder and consequently the resulting microstructure. In this study, the correlation between melt pool geometry and mechanical properties of selective laser melted (SLM) Ti–6Al–4V samples is investigated.
Derivation and Experimental Validation of the Equations of Motion of Magnetic Pendulums
Authors: Saeidi Hosseini R. S. , Heppler G. R. , Abdel-Rahman E. 
Published: June 2021

Abstract
A series of coaxial magnetic pendulums is studied as a simple physical surrogate for more general nonlinearly coupled almost-identical resonators that arise in quantum communications and the dynamics of social networks. The equations of motion for a series of coaxial magnetic pendulums are derived, and the solution is compared to experimental results. The equilibrium points and their stability are also determined.
A Simplified Fractional Order Modeling and Parameter Identification for Lithium-Ion Batteries
Authors: Liu Zheng , Qiu Yuan , Feng Jin , Chen Shaohang , Yang Chunshan 
Published: June 2021

Abstract
With the widespread development of new energy, the study of power lithium-ion batteries (LIBs) has broad prospects and great academic significance. The model and parameters are two essential prerequisites for LIB state estimation, which are used to provide a guarantee for the secure and convenient handling of LIBs. To obtain the reliable model and parameters, a simplified fractional order equivalent circuit model (FO-ECM) with high precision is presented in this article. The dynamic external electrical characteristic of LIBs is represented by the one-order FO-ECM, and then, the FO-ECM parameters are identified by the combination of Grunwald–Letnikov (G-L) definition-based factional order numerical calculation and noise compensation-based forgetting factor recursive least squares (FFRLS) method. The simplified FO-ECM can better characterize the nonlinear dynamic behaviors of LIBs, and the G-L definition-based FO-FFRLS algorithm can maintain good accuracy in the parameter estimation process. The results show that the simplified FO-ECM can improve the modeling precision and parameter identification performance compared with the common integer-order ECM in different test cycles.
Automatic Reservoir Model Identification Method based on Convolutional Neural Network
Authors: Liu Xuliang , Zha Wenshu , Qi Zhankui , Li Daolun , Xing Yan , He Lei 
Published: June 2021

Abstract
Well test analysis is a crucial technique to monitor reservoir performance, which is based on the theory of seepage mechanics, through the study of well test data, to identify reservoir models and estimate reservoir parameters. Reservoir model recognition is the first and essential step of well test analysis. It is usually judged by professionals’ experience, which results in low efficiency and accuracy. This paper is devoted to applying convolutional neural network (CNN) to well test analysis and proposes a new intelligent reservoir model identification method. Eight reservoir models studied in this paper include homogenous reservoirs with different outer boundaries such as infinite acting boundary, circular, single, angular, channel, U-shaped and rectangular sealing fault boundaries, and a radial composite reservoir with infinite acting boundary. Well testing data used in this paper, including actual field data and theoretical data, are generated by analytical solutions. To improve the classification accuracy of actual field data, noise processing was carried out on the data before training. The CNN that is most suitable for model recognition has been obtained through trial-and-error procedures. The availability of proposed CNN is proved with actual field cases of Daqing oil field, China. The method realizes the automatic identification of reservoir model with the total classification accuracy (TCA) of test data set of 98.68% and 95.18% for original data and noisy data, respectively.
Machine Learning Integration With Combustion Physics to Develop a Composite Predictive Model for Reactivity Controlled Compression Ignition Engine
Authors: Mishra Chinmaya , Subbarao P. M. V. 
Published: June 2021

Abstract
Phasing of combustion metrics close to the optimum values across operation range is necessary to avail benefits of reactivity controlled compression ignition (RCCI) engines. Parameters like start of combustion occurrence crank angle (CA) (θsoc), occurrence of burn rate fraction reaching 50% (θ50), mean effective pressure from indicator diagram (IMEP), etc. are described as combustion metrics. These metrics act as markers for the macroscopic state of combustion. Control of these metrics in RCCI engine is relatively complex due to the nature of ignition. As direct combustion control is challenging, alternative methods like combustion physics-derived models are a subject of research interest. In this work, a composite predictive model was proposed by integrating trained random forest (RF) machine learning and artificial neural networks (ANNs) to combustion physics-derived modified Livengood–Wu integral, parametrized double-Wiebe function, autoignition front propagation speed-based correlations, and residual gas fraction model. The RF machine learning established a correlative relationship between physics-based model coefficients and engine operating condition. The ANN developed a similar correlation between residual gas fraction parameters and engine operating condition. The composite model was deployed for the predictions of θsoc, θ50, and IMEP as RCCI engine combustion metrics. Experimental validation showed an error standard deviation (σ68.3,err) of 0.67°CA, 1.19°CA, 0.223 bar and symmetric mean absolute percentage error of 6.92%, 7.87%, and 4.01% for the predictions of θsoc, θ50, and IMEP, respectively, on cycle to cycle basis. Wide range applicability, lesser experiments for model calibration, low computational costs, and utility for control applications were the benefits of the proposed predictive model.
Study on Tribological Behavior of Zinc Phosphate Impregnated Graphite Under Oil Lubrication Condition
Authors: Chen Jianhang , Gao Siyang , Wang Peng , Xue Weihai , Li Shu , Duan Deli 
Published: June 2021

Abstract
The tribological behavior of zinc phosphate impregnated graphite (ZPIG) against nickel-based superalloy (GH4169) in oil environment was investigated, and the lubrication and wear mechanism were also determined in this study. Tribological tests were run under different tribological conditions using a ring-on-disk device. The results showed that, under any load conditions, zinc phosphate impregnated graphite had the lowest coefficient of friction (COF) and wear-rate at 200 rpm. Under the identical rotating speed condition, the minimum coefficient of friction and wear-rate were obtained when the load was 500 N and 1000 N. The lubrication mechanism, which could be reflected by the transfer layer of friction counterpart, was related to the coefficient of friction, wear-rate, and oil temperature to affect contact characteristics of two solid surfaces and formation ability of liquid film. The wear mechanism of zinc phosphate impregnated graphite under oil lubrication conditions was dominated by abrasive wear and material removal was achieved through the fracture mechanism.
Real-Time Image-Based Feedback Control of Laser Powder Bed Fusion
Authors: Shkoruta Aleksandr , Mishra Sandipan , Rock Stephen J. 
Published: June 2021

Abstract
This letter presents the design and experimental validation of a real-time image-based feedback control system for metal laser powder bed fusion (LPBF). A coaxial melt pool video stream is used to control laser power in real-time at 2 kHz. Modeling of the melt pool image response to changes in the input laser power is presented. Based on this identified model, a real-time feedback controller is implemented experimentally on a single track and part scales. On a single-track scale, the controller successfully tracks a time-varying melt pool reference. On a part-level scale, the controller successfully regulates the melt pool image signature to the desired reference value, reducing layer-to-layer signal variation and eliminating within-layer signal drift.
A Study on Using Image-Based Machine Learning Methods to Develop Surrogate Models of Stamp Forming Simulations
Authors: Zhou Haosu , Xu Qingfeng , Nie Zhenguo , Li Nan 
Published: June 2021

AbstractIn design for forming, it is becoming increasingly significant to develop surrogate models of high-fidelity finite element analysis (FEA) simulations of forming processes to achieve effective component feasibility assessment as well as process and component optimizations. However, surrogate models using traditional scalar-based machine learning methods (SBMLMs) fall short on accuracy and generalizability. This is because SBMLMs fail to harness the location information available from the simulations. To overcome this shortcoming, the theoretical feasibility and practical advantages of innovatively applying image-based machine learning methods (IBMLMs) in developing surrogate models of sheet stamp forming simulations are explored in this study. To demonstrate the advantages of IBMLMs, the effect of the location information on both design variables and simulated physical fields is first proposed and analyzed. Based on a sheet steel stamping case study, a Res-SE-U-Net IBMLM surrogate model of stamping simulations is then developed and compared with a baseline multilayer perceptron (MLP) SBMLM surrogate model. The results show that the IBMLM model is advantageous over the MLP SBMLM model in accuracy, generalizability, robustness, and informativeness. This article presents a promising methodology in leveraging IBMLMs as surrogate models to make maximum use of information from stamp forming FEA results. Future prospective studies that are inspired by this article are also discussed.
New Types of Three-Dimensional Vortices in the Heisenberg Model
Authors: Borisov A. B. , Dolgikh D. V. 
Published: June 2021

Abstract
The Heisenberg model for an isotropic magnet is considered in this work. A substitution that reduces the corresponding equations to equations with a simpler geometric interpretation is applied. One of the solutions of the latter describes a new magnetic structure comprised of two straight intersecting vortex filaments, which change the topological charge after intersection.
Life-threatening bronchopulmonary dysplasia: a British Paediatric Surveillance Unit Study
Authors: Naples Rebecca , Ramaiah Sridhar , Rankin Judith , Berrington Janet , Harigopal Sundeep 
Published: June 2021

ObjectivesTo assess the minimum incidence of life-threatening bronchopulmonary dysplasia (BPD), defined as need for positive pressure respiratory support or pulmonary vasodilators at 38 weeks corrected gestational age (CGA), in infants born <32 weeks gestation in the UK and Ireland; and to describe patient characteristics, management and outcomes to 1 year.MethodsProspective national surveillance study performed via the British Paediatric Surveillance Unit from June 2017 to July 2018. Data were collected in a series of three questionnaires from notification to 1 year of age.Results153 notifications met the case definition, giving a minimum incidence of 13.9 (95% CI: 11.8 to 16.3) per 1000 live births <32 weeks’ gestation. Median gestation was 26.1 (IQR 24.6–28) weeks, and birth weight 730 g (IQR 620–910 g). More affected infants were male (95 of 153, 62%; p<0.05). Detailed management and outcome data were provided for 94 infants. Fifteen died at median age 159 days (IQR 105–182) or 49.6 weeks CGA (IQR 43–53). Median age last receiving invasive ventilation was 50 days (IQR 22–98) and total duration of pressure support for surviving infants 103 (IQR 87–134) days. Fifty-seven (60.6%) received postnatal steroids and 22 (23.4%) pulmonary vasodilators. Death (16%) and/or major neurodevelopmental impairment (37.3%) or long-term ventilation (23.4%) were significantly associated with need for invasive ventilation near term and pulmonary hypertension.ConclusionsThis definition of life-threatening BPD identified an extremely high-risk subgroup, associated with serious morbidity and mortality. Wide variability in management was demonstrated, and future prospective study, particularly in key areas of postnatal steroid use and pulmonary hypertension management, is required.
Outcomes of eyes with retinal vein occlusion that are lost to follow-up after antivascular endothelial growth factor therapy
Authors: Salabati Mirataollah , Mahmoudzadeh Raziyeh , Wong Jae-Chiang , Patel Dillan , Patel Samir N , Obeid Anthony , Sivalingam Arunan , Vander James F , Garg Sunir J , Ho Allen C , Regillo Carl D , Hsu Jason 
Published: June 2021

Background/aimsTo evaluate the outcomes of eyes with macular oedema due to retinal vein occlusion (RVO) that are lost to follow-up (LTFU) after antivascular endothelial growth factor (VEGF) injections.MethodA retrospective, single-centre, consecutive case series of RVO patients receiving injections who were LTFU >6 months was conducted. Data were collected from the visit before LTFU; return visit; 3 months, 6 months and 12 months after return; and the final visit.ResultsNinety eyes of 83 patients were included. Fifty (55.5%) eyes had branch RVO and 40 (44.5%) had central RVO. Mean LTFU duration was 277.8 days with additional mean follow-up for 748.1 days after return. Mean logarithm of the minimum angle of resolution visual acuity (VA) (Snellen) at the visit before LTFU was 0.72 (20/105) which worsened on return [1.04 (20/219), p<0.001) and remained worse at all timepoints after return: 0.92 (20/166) at 3 months (p<0.001), 0.97 (20/187) at 6 months (p<0.001), 0.94 (20/174) at 12 months (p<0.001) and 1.01 (20/205) at final visit (p<0.001). Mean central foveal thickness (CFT) increased from 252 µm at the visit before LTFU to 396 µm at the return visit (p<0.001). No difference in CFT was noted by 3 months (258 µm, p=0.71), 6 months (241 µm, p=0.54) or 12 months after return (250 µm, p=0.95). CFT was thinner at the final visit (215 µm, p=0.018).ConclusionRVO patients receiving anti-VEGF injections who were LTFU experienced a decline in VA that did not return to the levels seen before LTFU despite improvement in CFT after restarting therapy, underscoring the importance of ongoing treatment.
White matter hyperintensity volume in pre-diabetes, diabetes and normoglycemia
Authors: Grosu Sergio , Lorbeer Roberto , Hartmann Felix , Rospleszcz Susanne , Bamberg Fabian , Schlett Christopher L , Galie Franziska , Selder Sonja , Auweter Sigrid , Heier Margit , Rathmann Wolfgang , Mueller-Peltzer Katharina , Ladwig Karl-Heinz , Peters Annette , Ertl-Wagner Birgit B , Stoecklein Sophia 
Published: June 2021

IntroductionAs white matter hyperintensities (WMHs) of the brain are associated with an increased risk of stroke, cognitive decline, and depression, elucidating the associated risk factors is important. In addition to age and hypertension, pre-diabetes and diabetes may play important roles in the development of WMHs. Previous studies have, however, shown conflicting results. We aimed to investigate the effect of diabetes status and quantitative markers of glucose metabolism on WMH volume in a population-based cohort without prior cardiovascular disease.Research design and methods400 participants underwent 3 T MRI. WMHs were manually segmented on 3D fluid-attenuated inversion recovery images. An oral glucose tolerance test (OGTT) was administered to all participants not previously diagnosed with diabetes to assess 2-hour serum glucose concentrations. Fasting glucose concentrations and glycated hemoglobin (HbA1c) levels were measured. Zero-inflated negative binomial regression analyses of WMH volume and measures of glycemic status were performed while controlling for cardiovascular risk factors and multiple testing.ResultsThe final study population comprised 388 participants (57% male; age 56.3±9.2 years; n=98 with pre-diabetes, n=51 with diabetes). Higher WMH volume was associated with pre-diabetes (p=0.001) and diabetes (p=0.026) compared with normoglycemic control participants after adjustment for cardiovascular risk factors. 2-hour serum glucose (p<0.001), but not fasting glucose (p=0.389) or HbA1c (p=0.050), showed a significant positive association with WMH volume after adjustment for cardiovascular risk factors.ConclusionOur results indicate that high 2-hour serum glucose concentration in OGTT, but not fasting glucose levels, may be an independent risk factor for the development of WMHs, with the potential to inform intensified prevention strategies in individuals at risk of WMH-associated morbidity.