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Journal articles on the topic 'NAR model'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Lu, Fei. "Data-Driven Model Reduction for Stochastic Burgers Equations." Entropy 22, no. 12 (2020): 1360. http://dx.doi.org/10.3390/e22121360.

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We present a class of efficient parametric closure models for 1D stochastic Burgers equations. Casting it as statistical learning of the flow map, we derive the parametric form by representing the unresolved high wavenumber Fourier modes as functionals of the resolved variable’s trajectory. The reduced models are nonlinear autoregression (NAR) time series models, with coefficients estimated from data by least squares. The NAR models can accurately reproduce the energy spectrum, the invariant densities, and the autocorrelations. Taking advantage of the simplicity of the NAR models, we investiga

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Ma, Qingwen, Sihan Liu, Xinyu Fan, Chen Chai, Yangyang Wang, and Ke Yang. "A Time Series Prediction Model of Foundation Pit Deformation Based on Empirical Wavelet Transform and NARX Network." Mathematics 8, no. 9 (2020): 1535. http://dx.doi.org/10.3390/math8091535.

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Large deep foundation pits are usually in a complex environment, so their surface deformation tends to show a stable rising trend with a small range of fluctuation, which brings certain difficulty to the prediction work. Therefore, in this study we proposed a nonlinear autoregressive exogenous (NARX) prediction method based on empirical wavelet transform (EWT) pretreatment is proposed for this feature. Firstly, EWT is used to conduct adaptive decomposition of the measured deformation data and extract the modal signal components with characteristic differences. Secondly, the main components aff

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Saxby, Claire. "NAR launches new Advance Access publication model." Nucleic Acids Research 34, no. 14 (2006): 3833. http://dx.doi.org/10.1093/nar/gkl523.

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Huang, Shih-Feng, Hsin-Han Chiang, and Yu-Jun Lin. "A network autoregressive model with GARCH effects and its applications." PLOS ONE 16, no. 7 (2021): e0255422. http://dx.doi.org/10.1371/journal.pone.0255422.

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In this study, a network autoregressive model with GARCH effects, denoted by NAR-GARCH, is proposed to depict the return dynamics of stock market indices. A GARCH filter is employed to marginally remove the GARCH effects of each index, and the NAR model with the Granger causality test and Pearson’s correlation test with sharp price movements is used to capture the joint effects caused by other indices with the most updated market information. The NAR-GARCH model is designed to depict the joint effects of nonsynchronous multiple time series in an easy-to-implement and effective way. The returns

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Wang, You, Ruxue Jia, Fang Dai, and Yunxia Ye. "Traffic Flow Prediction Method Based on Seasonal Characteristics and SARIMA-NAR Model." Applied Sciences 12, no. 4 (2022): 2190. http://dx.doi.org/10.3390/app12042190.

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Traffic flow is used as an essential indicator to measure the performance of the road network and a pivotal basis for road classification. However, the combined prediction model of traffic flow based on seasonal characteristics has been given little attention at present. Because the seasonal autoregressive integrated moving average model (SARIMA) has superior linear fitting characteristics, it is often used to process seasonal time series. In contrast, the non-autoregressive dynamic neural network (NAR) has a vital memory function and nonlinear interpretation capabilities. They are suitable fo

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López-Almada, Gabriela, J. Abraham Domínguez-Avila, Rosario Maribel Robles-Sánchez, et al. "Naringenin Decreases Retroperitoneal Adiposity and Improves Metabolic Parameters in a Rat Model of Western Diet-Induced Obesity." Metabolites 15, no. 2 (2025): 109. https://doi.org/10.3390/metabo15020109.

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Background: Obesity is a multifactorial disease with detrimental effects on health and quality of life; unregulated satiety plays a crucial role in food intake and obesity development. Naringenin (NAR) has shown beneficial effects on lipid and carbohydrate metabolism, although its impact on adiposity and satiety remains unclear. This study reports a Western diet (WD)-induced obesity model in rats, wherein 100 mg/kg of NAR was administered as an anti-obesity agent for 8 weeks; oxidative stress, lipid profile, and satiety biomarkers were then studied, as well as in silico interaction between NAR

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Karr, Jonathan R., Jayodita C. Sanghvi, Derek N. Macklin, Abhishek Arora, and Markus W. Covert. "WholeCellKB: model organism databases for comprehensive whole-cell models." Nucleic Acids Research 41, no. D1 (2012): D787—D792. http://dx.doi.org/10.1093/nar/gks1108.

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Taherdangkoo, Reza, Alexandru Tatomir, Mohammad Taherdangkoo, Pengxiang Qiu, and Martin Sauter. "Nonlinear Autoregressive Neural Networks to Predict Hydraulic Fracturing Fluid Leakage into Shallow Groundwater." Water 12, no. 3 (2020): 841. http://dx.doi.org/10.3390/w12030841.

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Hydraulic fracturing of horizontal wells is an essential technology for the exploitation of unconventional resources, but led to environmental concerns. Fracturing fluid upward migration from deep gas reservoirs along abandoned wells may pose contamination threats to shallow groundwater. This study describes the novel application of a nonlinear autoregressive (NAR) neural network to estimate fracturing fluid flow rate to shallow aquifers in the presence of an abandoned well. The NAR network is trained using the Levenberg–Marquardt (LM) and Bayesian Regularization (BR) algorithms and the result

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WANG, K. W., C. DENG, J. P. LI, Y. Y. ZHANG, X. Y. LI, and M. C. WU. "Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network." Epidemiology and Infection 145, no. 6 (2017): 1118–29. http://dx.doi.org/10.1017/s0950268816003216.

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SUMMARYTuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for the prevention and control of TB. This study proposes a hybrid model combining autoregressive integrated moving average (ARIMA) with a nonlinear autoregressive (NAR) neural network for forecasting the incidence of TB from January 2007 to March 2016. Prediction performance was compared between the hybrid model and the ARIMA model. The best-fit hybrid model was combined with an ARIMA (3,1,0) × (0,1,1)12 and NAR neural network with four delays

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Song, Jintao, Yongchao Chen, and Jie Yang. "A Novel Outlier Detection Method of Long-Term Dam Monitoring Data Based on SSA-NAR." Wireless Communications and Mobile Computing 2022 (August 30, 2022): 1–11. http://dx.doi.org/10.1155/2022/6569367.

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Outlier generally exists in dam monitoring data which may seriously affect the accuracy of dam safety evaluation results. Aiming at the outlier detection of dam monitoring data, a novel dynamic detection method of dam outlier data based on SSA-NAR is proposed. This combined method does not depend on the effect quantity and influence quantity relationship of traditional dam safety theory and only uses the time series of effect quantity to mine the variation, which can avoid the impact of missing or abnormal of the influence quantity. The Nonlinear Autoregression (NAR) is a classical time series

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Dada, Anelize, Rita de Cássia Vilhena da Silva, Mariana Zanovello, et al. "Comparative Analysis of the Protective Effect of Naringenin on Cardiovascular Parameters of Normotensive and Hypertensive Rats Subjected to the Myocardial Infarction Model." Pharmaceuticals 17, no. 10 (2024): 1324. http://dx.doi.org/10.3390/ph17101324.

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Background: Cardiovascular diseases rank as the top global cause of mortality, particularly acute myocardial infarction (MI). MI arises from the blockage of a coronary artery, which disrupts blood flow and results in tissue death. Among therapeutic approaches, bioactives from medicinal plants emerge as promising for the development of new medicines. Objectives: This study explored the effects of naringenin (NAR 100 mg/kg), a flavonoid found in citrus fruits, in normotensive (NTR) and spontaneously hypertensive (SHR) rats, both subjected to isoproterenol (ISO 85 mg/kg)-induced MI. Results: Post

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Kopp, J. "The SWISS-MODEL Repository of annotated three-dimensional protein structure homology models." Nucleic Acids Research 32, no. 90001 (2004): 230D—234. http://dx.doi.org/10.1093/nar/gkh008.

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Karami, Yasaman, Julien Rey, Guillaume Postic, Samuel Murail, Pierre Tufféry, and Sjoerd J. de Vries. "DaReUS-Loop: a web server to model multiple loops in homology models." Nucleic Acids Research 47, W1 (2019): W423—W428. http://dx.doi.org/10.1093/nar/gkz403.

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AbstractLoop regions in protein structures often have crucial roles, and they are much more variable in sequence and structure than other regions. In homology modeling, this leads to larger deviations from the homologous templates, and loop modeling of homology models remains an open problem. To address this issue, we have previously developed the DaReUS-Loop protocol, leading to significant improvement over existing methods. Here, a DaReUS-Loop web server is presented, providing an automated platform for modeling or remodeling loops in the context of homology models. This is the first web ser

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Li, Li, Ru Liu, Jing He, et al. "Naringin Regulates Microglia BV-2 Activation and Inflammation via the JAK/STAT3 Pathway." Evidence-Based Complementary and Alternative Medicine 2022 (May 19, 2022): 1–10. http://dx.doi.org/10.1155/2022/3492058.

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Objective. Microglial BV-2 cells are activated in the brain following insomnia. Naringin (NAR) is a polymethoxylated flavonoid that is also commonly found in citrus fruits and is known for its antioxidant potential. However, the effect of NAR on microglial cells has rarely been studied in the brain of an organism after insomnia. This study aimed to investigate the effects and potential mechanisms of action of NAR on microglial cell activation and inflammation. Methods. BV-2 cells were obtained from the China Center for Type Culture Collection and randomly divided into five treatment groups: co

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Zhang, Xueqing, Yibin Zeng, Hui Li, et al. "A Modified NAR Scoring Model Incorporating Immune Infiltration Characteristics to Better Predict Long-Term Survival Following Neoadjuvant Radiotherapy in Rectal Cancer." Life 13, no. 11 (2023): 2106. http://dx.doi.org/10.3390/life13112106.

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(1) Background: The neoadjuvant rectal (NAR) score has been developed as a prognostic tool for survival in locally advanced rectal cancer (LARC). However, the NAR score only incorporates weighted cT, ypT, and ypN categories. This long-term follow-up study aims to modify a novel prognostic scoring model and identify a short-term endpoint for survival. (2) Methods: The prognostic factors for overall survival (OS) were explored through univariate and multivariate analyses. Based on Cox regression modeling, nomogram plots were constructed. Area under the curve (AUC) and concordance indices were us

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Liu, Sheng Peng, and Ye Zhang. "City Fire Forecasts and Analysis Based on Nonlinear Auto-Regressive Time-Series Model." Applied Mechanics and Materials 241-244 (December 2012): 1550–55. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.1550.

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The forecasting to future developments of the city fire time series is a challenging task that has been addressed by many researchers due to the importance. In this paper, a Nonlinear Auto-Regressive (NAR) prediction model is applied to forecast the city fire data based on support vector regression. The performances of the NAR prediction model in city fire forecasting are compared with the BP neural network method. The experimental results show that the proposed model performs best.

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Zhou, Wei, Xiao Zhu, Jun Wang, and Yan Ran. "A New Error Prediction Method for Machining Process Based on a Combined Model." Mathematical Problems in Engineering 2018 (July 16, 2018): 1–8. http://dx.doi.org/10.1155/2018/3703861.

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Machining process is characterized by randomness, nonlinearity, and uncertainty, leading to the dynamic changes of machine tool machining errors. In this paper, a novel model combining the data processing merits of metabolic grey model (MGM) with that of nonlinear autoregressive (NAR) neural network is proposed for machining error prediction. The advantages and disadvantages of MGM and NAR neural network are introduced in detail, respectively. The combined model first utilizes MGM to predict the original error data and then uses NAR neural network to forecast the residual series of MGM. An exp

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Fujihara, C. K., D. M. Limongi, R. Falzone, M. S. Graudenz, and R. Zatz. "Pathogenesis of glomerular sclerosis in subtotally nephrectomized analbuminemic rats." American Journal of Physiology-Renal Physiology 261, no. 2 (1991): F256—F264. http://dx.doi.org/10.1152/ajprenal.1991.261.2.f256.

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The Nagase analbuminemic rat (NAR), a mutant of the Sprague-Dawley (SD) strain, exhibits persistent hypercholesterolemia, thrombocytosis, and enhanced platelet aggregation, abnormalities possibly involved in the genesis of glomerular sclerosis (GS). Previous observations suggest that these rats never develop aging GS. We studied the development of GS in NAR after 5/6 nephrectomy (Nx). Fifteen days after Nx, marked glomerular hypertension was observed in NAR, compared with only mild elevations in SD rats. Glomerular hypertrophy was more marked in SD rats than in NAR. Enalapril normalized glomer

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John, B. "Comparative protein structure modeling by iterative alignment, model building and model assessment." Nucleic Acids Research 31, no. 14 (2003): 3982–92. http://dx.doi.org/10.1093/nar/gkg460.

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Li, Yong, Yiyuan Pan, Lin Gao, et al. "Naringenin Protects against Acute Pancreatitis in Two Experimental Models in Mice by NLRP3 and Nrf2/HO-1 Pathways." Mediators of Inflammation 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/3232491.

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Background. Naringenin (Nar) is a type of flavonoid and has been shown to have anti-inflammatory and antioxidative properties. However, the effects of Nar on acute pancreatitis (AP) have not been well studied. In this study, we aimed to investigate the function of Nar in a mouse model of AP. Methods. Mild acute pancreatitis (MAP) was induced by caerulein (Cae), and severe acute pancreatitis (SAP) was induced by L-arginine in mice. Nar was administered intraperitoneally at doses of 25, 50, or 100 mg/kg following MAP induction and at a dose of 100 mg/kg following SAP induction. The serum levels

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Long, Bing, Xiangnan Li, Xiaoyu Gao, and Zhen Liu. "Prognostics Comparison of Lithium-Ion Battery Based on the Shallow and Deep Neural Networks Model." Energies 12, no. 17 (2019): 3271. http://dx.doi.org/10.3390/en12173271.

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Prognostics of the remaining useful life (RUL) of lithium-ion batteries is a crucial role in the battery management systems (BMS). An artificial neural network (ANN) does not require much knowledge from the lithium-ion battery systems, thus it is a prospective data-driven prognostic method of lithium-ion batteries. Though the ANN has been applied in prognostics of lithium-ion batteries in some references, no one has compared the prognostics of the lithium-ion batteries based on different ANN. The ANN generally can be classified to two categories: the shallow ANN, such as the back propagation (

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Tian, Kai, Yi Xu, Jihong Guan, and Shuigeng Zhou. "Network as Regularization for Training Deep Neural Networks: Framework, Model and Performance." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 6013–20. http://dx.doi.org/10.1609/aaai.v34i04.6063.

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Despite powerful representation ability, deep neural networks (DNNs) are prone to over-fitting, because of over-parametrization. Existing works have explored various regularization techniques to tackle the over-fitting problem. Some of them employed soft targets rather than one-hot labels to guide network training (e.g. label smoothing in classification tasks), which are called target-based regularization approaches in this paper. To alleviate the over-fitting problem, here we propose a new and general regularization framework that introduces an auxiliary network to dynamically incorporate gui

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Walther, Jürgen, Pablo D. Dans, Alexandra Balaceanu, Adam Hospital, Genís Bayarri, and Modesto Orozco. "A multi-modal coarse grained model of DNA flexibility mappable to the atomistic level." Nucleic Acids Research 48, no. 5 (2020): e29-e29. http://dx.doi.org/10.1093/nar/gkaa015.

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Abstract We present a new coarse grained method for the simulation of duplex DNA. The algorithm uses a generalized multi-harmonic model that can represent any multi-normal distribution of helical parameters, thus avoiding caveats of current mesoscopic models for DNA simulation and representing a breakthrough in the field. The method has been parameterized from accurate parmbsc1 atomistic molecular dynamics simulations of all unique tetranucleotide sequences of DNA embedded in long duplexes and takes advantage of the correlation between helical states and backbone configurations to derive atomi

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Kummong, Ratree, and Siriporn Supratid. "Long-term forecasting system using wavelet – nonlinear autoregressive neural network conjunction model." Journal of Modelling in Management 14, no. 4 (2019): 948–71. http://dx.doi.org/10.1108/jm2-11-2018-0184.

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Purpose An accurate long-term multi-step forecast provides crucial basic information for planning and reinforcing managerial decision-support. However, nonstationarity and nonlinearity, normally consisted of several types of managerial data can seriously ruin the forecasting computation. This paper aims to propose an effective long-term multi-step forecasting conjunction model, namely, wavelet–nonlinear autoregressive neural network (WNAR) conjunction model. The WNAR combines discrete wavelet transform (DWT) and nonlinear autoregressive neural network (NAR) to cope with such nonstationarity an

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Castrignano, T. "The PMDB Protein Model Database." Nucleic Acids Research 34, no. 90001 (2006): D306—D309. http://dx.doi.org/10.1093/nar/gkj105.

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Rueda-Bayona, Juan Gabriel, Juan José Cabello Eras, and Alexis Sagastume Gutiérrez. "Modeling Wind Speed with a Long-Term Horizon and High-Time Interval with a Hybrid Fourier-Neural Network Model." Mathematical Modelling of Engineering Problems 8, no. 3 (2021): 431–40. http://dx.doi.org/10.18280/mmep.080313.

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The limited availability of local climatological stations and the limitations to predict the wind speed (WS) accurately are significant barriers to the expansion of wind energy (WE) projects worldwide. A methodology to forecast accurately the WS at the local scale can be used to overcome these barriers. This study proposes a methodology to forecast the WS with high-resolution and long-term horizons, which combines a Fourier model and a nonlinear autoregressive network (NAR). Given the nonlinearities of the WS variations, a NAR model is used to forecast the WS based on the variability identifie

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van der Meer, Dieudonne, Syd Barthorpe, Wanjuan Yang, et al. "Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models." Nucleic Acids Research 47, no. D1 (2018): D923—D929. http://dx.doi.org/10.1093/nar/gky872.

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Jin, Xuezhu, Xin Chen, Song Wang, and Yan Leng. "Investigation of narciclasine’s role in dietary interventions for nonalcoholic fatty liver disease." Italian Journal of Food Science 37, no. 1 (2025): 441–49. https://doi.org/10.15586/ijfs.v37i1.2835.

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Nonalcoholic fatty liver disease (NAFLD), a condition caused by a buildup of fat in liver cells because of wrong choices and nutrition intake patterns over time, is a common chronic metabolic disorder among individuals today. Narciclasine (Nar), a compound present in Haemanthus coccineus L., has been noted for its strong anti-inflammatory effects. However, its impact on regulating metabolic imbalances associated with NAFLD requires further investigation. In this research investigation using mice with NAFLD induced by a high-fat diet (HFD) and a cell model stimulated with fatty acids (FFAs), th

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Eggenhofer, Florian, Ivo L. Hofacker, and Christian Höner zu Siederdissen. "RNAlien – Unsupervised RNA family model construction." Nucleic Acids Research 44, no. 17 (2016): 8433–41. http://dx.doi.org/10.1093/nar/gkw558.

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Kolker, Eugene, Roger Higdon, Winston Haynes, et al. "MOPED: Model Organism Protein Expression Database." Nucleic Acids Research 40, no. D1 (2011): D1093—D1099. http://dx.doi.org/10.1093/nar/gkr1177.

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Forties, Robert A., Justin A. North, Sarah Javaid, et al. "A quantitative model of nucleosome dynamics." Nucleic Acids Research 39, no. 19 (2011): 8306–13. http://dx.doi.org/10.1093/nar/gkr422.

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Milner, Joel J., Edi Cecchini, and Peter J. Dominy. "A kinetic model for subtractive hybridization." Nucleic Acids Research 23, no. 1 (1995): 176–87. http://dx.doi.org/10.1093/nar/23.1.176.

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Konishi, T. "A thermodynamic model of transcriptome formation." Nucleic Acids Research 33, no. 20 (2005): 6587–92. http://dx.doi.org/10.1093/nar/gki967.

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Cobb, Jennifer A., and Lotte Bjergbaek. "RecQ helicases: lessons from model organisms." Nucleic Acids Research 34, no. 15 (2006): 4106–14. http://dx.doi.org/10.1093/nar/gkl557.

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Agah, A. "A multi-enzyme model for pyrosequencing." Nucleic Acids Research 32, no. 21 (2004): e166-e166. http://dx.doi.org/10.1093/nar/gnh159.

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Zhang, Zhihan, Hui Liu, Xiang Hu, et al. "Heat Shock Protein 70 Mediates the Protective Effect of Naringenin on High-Glucose-Induced Alterations of Endothelial Function." International Journal of Endocrinology 2022 (August 1, 2022): 1–10. http://dx.doi.org/10.1155/2022/7275765.

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Endothelial dysfunction plays a pivotal role in the development and progression of diabetic vascular complications. Naringenin (Nar) is a flavanone bioactive isolated from citrus fruits known to have in vitro and in vivo antidiabetic properties. However, whether Nar affects endothelial function remains unclear in diabetes or under high-glucose (HG) condition. Using an in vitro model of hyperglycemia in human umbilical vein endothelial cells (HUVECs), we found that Nar administration markedly attenuated HG-induced alterations of endothelial function, evidenced by the mitigation of oxidative str

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Jin, Hua, Yue Zhao, Yinlian Yao, et al. "Intratracheal Administration of Stem Cell Membrane-Cloaked Naringin-Loaded Biomimetic Nanoparticles Promotes Resolution of Acute Lung Injury." Antioxidants 13, no. 3 (2024): 282. http://dx.doi.org/10.3390/antiox13030282.

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Cytokine storm and ROS overproduction in the lung always lead to acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) in a very short time. Effectively controlling cytokine storm release syndrome (CRS) and scavenging ROS are key to the prevention and treatment of ALI/ARDS. In this work, the naringin nanoparticles (Nar-NPs) were prepared by the emulsification and evaporation method; then, the mesenchymal stem cell membranes (CMs) were extracted and coated onto the surface of the Nar-NPs through the hand extrusion method to obtain the biomimetic CM@Nar-NPs. In vitro, the CM@Nar

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Zhang, Lei. "Chaotic System Design Based on Recurrent Artificial Neural Network for the Simulation of EEG Time Series." International Journal of Cognitive Informatics and Natural Intelligence 13, no. 1 (2019): 25–35. http://dx.doi.org/10.4018/ijcini.2019010103.

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Electroencephalogram (EEG) signals captured from brain activities demonstrate chaotic features, and can be simulated by nonlinear dynamic time series outputs of chaotic systems. This article presents the research work of chaotic system generator design based on artificial neural network (ANN), for studying the chaotic features of human brain dynamics. The ANN training performances of Nonlinear Auto-Regressive (NAR) model are evaluated for the generation and prediction of chaotic system time series outputs, based on varying the ANN architecture and the precision of the generated training data.

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Lova, Stelly Martha, and Faisal Faisal. "Menjadi Guru Adaptif dengan Pendekatan C-NAR di Sekolah Dasar." Paedagogi: Jurnal Kajian Ilmu Pendidikan (e-journal) 9, no. 1 (2023): 149. http://dx.doi.org/10.24114/paedagogi.v9i1.48202.

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Penelitian ini bertujuan untuk mendeskripsikan implementasi Collaborative Nested Action Research (C-NAR) sebagai upaya menghasilkan guru adaptif di Sekolah Dasar (SD). Penelitin ini merupakan penelitian tindakan kelas berkelanjutan dengan pendekatan C-NAR. Dalam pelaksanaannya, selain guru melakukan perbaikan perkelanjutan dalam pembelajaran, dosen dan guru pamong melakukan perbaikan berkelanjutan dalam pembimbingan. Teknik pengumpulan data dilakukan melalui observasi dan wawancara. Instrumen yang digunakan dalam penelitian adalah lembar observasi dan pedoman wawancara. Data penelitian dianali

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Rivoira, María A., Alfredo Rigalli, Lucía Corball, Nori Tolosa de Talamoni, and Valeria Rodríguez. "Naringin prevents bone damage in the experimental metabolic syndrome induced by a fructose-rich diet." Applied Physiology, Nutrition, and Metabolism 47, no. 4 (2022): 395–404. http://dx.doi.org/10.1139/apnm-2021-0473.

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We analyzed the effect of naringin (NAR), a flavonoid from citric fruits, on bone quality and biomechanical properties, as well as the redox state of bone marrow in rats fed a fructose-rich diet (FRD), an experimental model to mimic human metabolic syndrome. NAR blocked the increase in the number of osteoclasts and adipocytes and the decrease in the number of osteocytes and osteocalcin (+) cells caused by FRD. Trabecular number was significantly higher in the FRD+NAR group. FRD induced a decrease in the femoral trabecular and cortical bone mineral density, which was blocked by NAR. The fractur

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Sioofy Khoojine, Arash, Mahdi Shadabfar, Vahid Reza Hosseini, and Hadi Kordestani. "Network Autoregressive Model for the Prediction of COVID-19 Considering the Disease Interaction in Neighboring Countries." Entropy 23, no. 10 (2021): 1267. http://dx.doi.org/10.3390/e23101267.

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Predicting the way diseases spread in different societies has been thus far documented as one of the most important tools for control strategies and policy-making during a pandemic. This study is to propose a network autoregressive (NAR) model to forecast the number of total currently infected cases with coronavirus disease 2019 (COVID-19) in Iran until the end of December 2021 in view of the disease interactions within the neighboring countries in the region. For this purpose, the COVID-19 data were initially collected for seven regional nations, including Iran, Turkey, Iraq, Azerbaijan, Arme

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Fuller, Thomas. "28 IOHA National accreditation recognition certification program development template and guideline." Annals of Work Exposures and Health 68, Supplement_1 (2024): 1. http://dx.doi.org/10.1093/annweh/wxae035.013.

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Abstract The National Accreditation Recognition (NAR) Committee establishes a process and criteria to recognize national occupational hygiene associations who offer certification examinations for the profession. The goal is to promote global respect for and recognition of Occupational Hygiene Certification Programs which meet or exceed the IOHA Model Certification Program requirements. Although some preliminary guidance is provided to potential applicants on the NAR Committee webpage, the development of required procedures and documents can be a daunting endeavor. This session will provide a g

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Reshetnikov, Roman V., Anastasia V. Stolyarova, Arthur O. Zalevsky, et al. "A coarse-grained model for DNA origami." Nucleic Acids Research 46, no. 3 (2017): 1102–12. http://dx.doi.org/10.1093/nar/gkx1262.

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Steinberg, Sergey V., and Lev L. Kisselev. "Mosaic tile model for tRNA-enzyme recognition." Nucleic Acids Research 21, no. 8 (1993): 1941–47. http://dx.doi.org/10.1093/nar/21.8.1941.

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Kiefer, F., K. Arnold, M. Kunzli, L. Bordoli, and T. Schwede. "The SWISS-MODEL Repository and associated resources." Nucleic Acids Research 37, Database (2009): D387—D392. http://dx.doi.org/10.1093/nar/gkn750.

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Carrera, Javier, Guillermo Rodrigo, and Alfonso Jaramillo. "Model-based redesign of global transcription regulation." Nucleic Acids Research 37, no. 5 (2009): e38-e38. http://dx.doi.org/10.1093/nar/gkp022.

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Benkert, Pascal, Michael Künzli, and Torsten Schwede. "QMEAN server for protein model quality estimation." Nucleic Acids Research 37, suppl_2 (2009): W510—W514. http://dx.doi.org/10.1093/nar/gkp322.

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Long, Manyuan, and Michael Deutsch. "Intron—exon structures of eukaryotic model organisms." Nucleic Acids Research 27, no. 15 (1999): 3219–28. http://dx.doi.org/10.1093/nar/27.15.3219.

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Abstract:

Abstract To investigate the distribution of intron—exon structures of eukaryotic genes, we have constructed a general exon database comprising all available introncontaining genes and exon databases from 10 eukaryotic model organisms: Homo sapiens, Mus musculus, Gallus gallus, Rattus norvegicus, Arabidopsis thaliana, Zea mays, Schizosaccharomyces pombe, Aspergillus, Caenorhabditis elegans and Drosophila . We purged redundant genes to avoid the possible bias brought about by redundancy in the databases. After discarding those questionable introns that do not contain correct splice sites, the fi

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Huang, L. C., E. A. Wood, and Michael MCox. "A bacterial model system for chromosomal targeting." Nucleic Acids Research 19, no. 3 (1991): 443–48. http://dx.doi.org/10.1093/nar/19.3.443.

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Huang, L. C., E. A. Wood, and M. M. Cox. "A bacterial model system for chromosomal targeting." Nucleic Acids Research 19, no. 8 (1991): 1978. http://dx.doi.org/10.1093/nar/19.8.1978.

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