Search Results - modified LM algorithm

A modified LM algorithm for tensor complementarity problems over the circular cone

Authors: Huai Zhang Yi-Fen Ke Changfeng Ma

Source: Journal of Computational and Applied Mathematics. 398:113689

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology

ANN Synthesis Models Trained with Modified GA-LM Algorithm for ACPWs with Conductor Backing and Substrate Overlaying.

Authors: Zhongbao Wang Shaojun Fang Shiqiang Fu

Source: ETRI Journal. Oct2012, Vol. 34 Issue 5, p696-705. 10p.

Subject Terms: Artificial neural networks, Genetic algorithms, Electrical conductors, Substrates (Materials science), Waveguides, Electromagnetism

A Progressive Peak-Finding and Weak Peak-Preserving LM Algorithm for Isotope Separation in Miniature Mass Spectrometers.

Authors: Wang Z Li A Xu W et al.

Source: Rapid communications in mass spectrometry : RCM [Rapid Commun Mass Spectrom] 2025 Sep 15; Vol. 39 (17), pp. e10073.

Publication Type: Journal Article

Journal Info: Publisher: John Wiley And Sons Ltd Country of Publication: England NLM ID: 8802365 Publication Model: Print Cited Medium: Internet ISSN: 1097-0231 (Electronic) Linking ISSN: 09514198 NLM ISO Abbreviation: Rapid Commun Mass Spectrom Subsets: PubMed not MEDLINE; MEDLINE

A modified Levenberg–Marquardt algorithm for simultaneous estimation of multi-parameters of boundary heat flux by solving transient nonlinear inverse heat conduction problems

Authors: Wang Shengdong Miao Cui Xiao-Wei Gao et al.

Source: International Journal of Heat and Mass Transfer. 97:908-916

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://www.infona.pl/resource/bwmeta1.element.elsevier-77c64d30-2d5e-3692-8fe5-dd3567cde225
https://www.sciencedirect.com/science/article/pii/S0017931015317932

Datafall: a policy-driven algorithm for decentralized placement and reorganization of replicated data

Flexibility enhancement to the modified fast convolution algorithm

Reduced complexity and increased flexibility modified fast convolution algorithm

ACCELERATING THE MODIFIED LEVENBERG-MARQUARDT METHOD FOR NONLINEAR EQUATIONS

Authors: FAN, JINYAN

Source: Mathematics of Computation, 2014 May 01. 83(287), 1173-1187.

Access URL: https://www.jstor.org/stable/24488277

Modified Huangqi Shengmai Yin enhances ruminal microbiome and metabolites activity in dairy cows with subclinical mastitis.

Authors: Zhang, Chenyibo Zhang, Baoling Li, Yuqiong et al.

Source: Frontiers in Veterinary Science. 2025, p1-12. 12p.

A novel L1C.5 RFLP-1-4-4 recombinant porcine reproductive and respiratory syndrome virus between wild-type virus and a modified-live virus vaccine is highly pathogenic to piglets.

Authors: Gao, Xue Zhou, Jun Kang, Runmin et al.

Source: Frontiers in Veterinary Science. 2025, p1-15. 15p.

Does a preterm labor-assessment algorithm improve preterm labor-related knowledge, clinical practice confidence, and educational satisfaction?: a quasi-experimental study.

Authors: Hee-Young Choi Jeung-lm Kim

Source: Korean Journal of Women Health Nursing. Sep2023, Vol. 29 Issue 3, p219-228. 10p.

Subject Terms: College students, Confidence, Clinical trials, Analysis of variance, Nursing, Health occupations students, Research methodology, Satisfaction, Nursing practice, Pre-tests & post-tests, T-test (Statistics), Students, Research funding, Repeated measures design, Descriptive statistics, Nursing students, Premature labor, Nursing assessment, Algorithms, Educational outcomes

THE MODIFIED LEVENBERG-MARQUARDT METHOD FOR NONLINEAR EQUATIONS WITH CUBIC CONVERGENCE

Authors: FAN, JINYAN

Source: Mathematics of Computation, 2012 Jan 01. 81(277), 447-466.

Access URL: https://www.jstor.org/stable/23075235

THE MODIFIED LEVENBERG-MARQUARDT METHOD FOR NONLINEAR EQUATIONS WITH CUBIC CONVERGENCE.

Source: Mathematics of Computation; Jun2011, Vol. 81 Issue 277, p447-466, 20p

Subject Terms: NUMERICAL solutions to nonlinear differential equations, STOCHASTIC convergence, MATHEMATICAL functions, ALGORITHMS, MATHEMATICAL proofs, NUMERICAL analysis

Applying Bayesian Regularization for Acceleration of Levenberg-Marquardt based Neural Network Training.

Authors: Suliman, Azizah Omarov, Batyrkhan S.

Source: International Journal of Interactive Multimedia & Artificial Intelligence; Jun2018, Vol. 5 Issue 1, p68-72, 5p

Subject Terms: ARTIFICIAL neural networks, NEURAL circuitry, MARQUARDT algorithm

Parallel chaotic bi-objective evolutionary algorithms for scalable feature subset selection via migration strategy.

Authors: Vivek, Yelleti Ravi, Vadlamani Krishna, P. Radha

Source: Applied Soft Computing. Jan2026:Part A, Vol. 186, pN.PAG-N.PAG. 1p.

Subject Terms: Multi-objective optimization, Evolutionary algorithms, Optimization algorithms, Parallel programming, Receiver operating characteristic curves, Feature selection, Big data, Stochastic analysis

A Real-Time Prediction Method for Heat Flux in Continuous Casting Mold with Optical Fibers.

Authors: Jin, Yonggang Luo, Sen Meng, Xiaoliang et al.

Source: Metallurgical & Materials Transactions. Part B; Apr2025, Vol. 56 Issue 2, p1865-1878, 14p

Subject Terms: CONTINUOUS casting, OPTICAL measurements, HEAT conduction, HEAT flux, OPTICAL fibers

Developing Intelligent Wearable Algorithms (DIWAH)

Contributors: Patrick Bergman, Assostand Professor

Source: Design of an Intelligent Wearable to Assess Physical Activity and Health Related Outcomes - the DIWAH Study
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Wright SP, Hall Brown TS, Collier SR, Sandberg K. How consumer physical activity monitors could transform human physiology research. Am J Physiol Regul Integr Comp Physiol. 2017 Mar 1;312(3):R358-R367. doi: 10.1152/ajpregu.00349.2016. Epub 2017 Jan 4.
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Wong CK, Mentis HM, Kuber R. The bit doesn't fit: Evaluation of a commercial activity-tracker at slower walking speeds. Gait Posture. 2018 Jan;59:177-181. doi: 10.1016/j.gaitpost.2017.10.010. Epub 2017 Oct 9.
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Keadle SK, Lyden KA, Strath SJ, Staudenmayer JW, Freedson PS. A Framework to Evaluate Devices That Assess Physical Behavior. Exerc Sport Sci Rev. 2019 Oct;47(4):206-214. doi: 10.1249/JES.0000000000000206.
Muhlen JM, Stang J, Lykke Skovgaard E, Judice PB, Molina-Garcia P, Johnston W, Sardinha LB, Ortega FB, Caulfield B, Bloch W, Cheng S, Ekelund U, Brond JC, Grontved A, Schumann M. Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network. Br J Sports Med. 2021 Jul;55(14):767-779. doi: 10.1136/bjsports-2020-103148. Epub 2021 Jan 4.
Gillinov S, Etiwy M, Wang R, Blackburn G, Phelan D, Gillinov AM, Houghtaling P, Javadikasgari H, Desai MY. Variable Accuracy of Wearable Heart Rate Monitors during Aerobic Exercise. Med Sci Sports Exerc. 2017 Aug;49(8):1697-1703. doi: 10.1249/MSS.0000000000001284.
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Westerterp KR. Doubly labelled water assessment of energy expenditure: principle, practice, and promise. Eur J Appl Physiol. 2017 Jul;117(7):1277-1285. doi: 10.1007/s00421-017-3641-x. Epub 2017 May 15.
Arvidsson D, Fridolfsson J, Borjesson M. Measurement of physical activity in clinical practice using accelerometers. J Intern Med. 2019 Aug;286(2):137-153. doi: 10.1111/joim.12908. Epub 2019 Apr 16.
Liu F, Wanigatunga AA, Schrack JA. Assessment of Physical Activity in Adults Using Wrist Accelerometers. Epidemiol Rev. 2022 Jan 14;43(1):65-93. doi: 10.1093/epirev/mxab004.
Rastogi T, Backes A, Schmitz S, Fagherazzi G, van Hees V, Malisoux L. Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review. Syst Rev. 2020 Nov 7;9(1):259. doi: 10.1186/s13643-020-01515-2.
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Phillips LJ, Petroski GF, Markis NE. A Comparison of Accelerometer Accuracy in Older Adults. Res Gerontol Nurs. 2015 Sep-Oct;8(5):213-9. doi: 10.3928/19404921-20150429-03. Epub 2015 May 7.
Sheng, B., Moosman, O. M., Del Pozo-Cruz, B., Del Pozo-Cruz, J., Alfonso-Rosa, R. M. & Zhang, Y. A comparison of different machine learning algorithms, types and placements of activity monitors for physical activity classification. Measurement 154, 107480 (2020).
Montoye AHK, Pivarnik JM, Mudd LM, Biswas S, Pfeiffer KA. Validation and Comparison of Accelerometers Worn on the Hip, Thigh, and Wrists for Measuring Physical Activity and Sedentary Behavior. AIMS Public Health. 2016 May 20;3(2):298-312. doi: 10.3934/publichealth.2016.2.298. eCollection 2016.
Montoye AHK, Westgate BS, Fonley MR, Pfeiffer KA. Cross-validation and out-of-sample testing of physical activity intensity predictions with a wrist-worn accelerometer. J Appl Physiol (1985). 2018 May 1;124(5):1284-1293. doi: 10.1152/japplphysiol.00760.2017. Epub 2018 Jan 25.
Ahmadi MN, Chowdhury A, Pavey T, Trost SG. Laboratory-based and free-living algorithms for energy expenditure estimation in preschool children: A free-living evaluation. PLoS One. 2020 May 20;15(5):e0233229. doi: 10.1371/journal.pone.0233229. eCollection 2020.
Stewart T, Narayanan A, Hedayatrad L, Neville J, Mackay L, Duncan S. A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults. Med Sci Sports Exerc. 2018 Dec;50(12):2595-2602. doi: 10.1249/MSS.0000000000001717.
Willetts M, Hollowell S, Aslett L, Holmes C, Doherty A. Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants. Sci Rep. 2018 May 21;8(1):7961. doi: 10.1038/s41598-018-26174-1.
Narayanan A, Desai F, Stewart T, Duncan S, Mackay L. Application of Raw Accelerometer Data and Machine-Learning Techniques to Characterize Human Movement Behavior: A Systematic Scoping Review. J Phys Act Health. 2020 Mar 1;17(3):360-383. doi: 10.1123/jpah.2019-0088.
Galán-Mercant, A., Ortiz, A., Herrera-Viedma, E., Tomas, M. T., Fernandes, B. & Moral-Munoz, J. A. Assessing physical activity and functional fitness level using convolutional neural networks. Knowledge-Based Systems 185 (2019).
Hamid A, Duncan MJ, Eyre ELJ, Jing Y. Predicting children's energy expenditure during physical activity using deep learning and wearable sensor data. Eur J Sport Sci. 2021 Jun;21(6):918-926. doi: 10.1080/17461391.2020.1789749. Epub 2020 Jul 16.
van Kuppevelt D, Heywood J, Hamer M, Sabia S, Fitzsimons E, van Hees V. Segmenting accelerometer data from daily life with unsupervised machine learning. PLoS One. 2019 Jan 9;14(1):e0208692. doi: 10.1371/journal.pone.0208692. eCollection 2019.
Jones PJ, Catt M, Davies MJ, Edwardson CL, Mirkes EM, Khunti K, Yates T, Rowlands AV. Feature selection for unsupervised machine learning of accelerometer data physical activity clusters - A systematic review. Gait Posture. 2021 Oct;90:120-128. doi: 10.1016/j.gaitpost.2021.08.007. Epub 2021 Aug 13.
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Wijkman M, Carlsson M, Darwiche G, Nystrom FH. A pilot study of hypertension management using a telemedicine treatment approach. Blood Press Monit. 2020 Feb;25(1):18-21. doi: 10.1097/MBP.0000000000000413.

Modified binary salp swarm algorithm in EEG signal classification for epilepsy seizure detection.

Authors: Morteza Ghazali, Seyed Alizadeh, Mousa Mazloum, Jalil et al.

Source: Biomedical Signal Processing & Control. Sep2022, Vol. 78, pN.PAG-N.PAG. 1p.

Subject Terms: Signal classification, Discrete wavelet transforms, Epilepsy, Artificial neural networks, Electroencephalography, Diagnosis of epilepsy

Modifiers of Disease Severity in Cerebral Cavernous Malformations

Authors: University of New Mexico University of Chicago National Institute of Neurological Disorders and Stroke (NINDS) et al.

Source: Modifiers of Disease Severity and Progression in Cerebral Cavernous Malformations
Akers AL, Ball KL, Clancy M, Comi AM, Faughnan ME, Gopal-Srivastava R, Jacobs TP, Kim H, Krischer J, Marchuk DA, McCulloch CE, Morrison L, Moses M, Moy CS, Pawlikowska L, Young WL. Brain Vascular Malformation Consortium: Overview, Progress and Future Directions. J Rare Disord. 2013 Apr 1;1(1):5.
Flemming KD, Smith E, Marchuk D, Derry WB. Familial Cerebral Cavernous Malformations. 2003 Feb 24 [updated 2023 Jul 27]. In: Adam MP, Feldman J, Mirzaa GM, Pagon RA, Wallace SE, Amemiya A, editors. GeneReviews(R) [Internet]. Seattle (WA): University of Washington, Seattle; 1993-2025. Available from http://www.ncbi.nlm.nih.gov/books/NBK1293/
Choquet H, Pawlikowska L, Lawton MT, Kim H. Genetics of cerebral cavernous malformations: current status and future prospects. J Neurosurg Sci. 2015 Sep;59(3):211-20. Epub 2015 Apr 22.
Zafar A, Quadri SA, Farooqui M, Ikram A, Robinson M, Hart BL, Mabray MC, Vigil C, Tang AT, Kahn ML, Yonas H, Lawton MT, Kim H, Morrison L. Familial Cerebral Cavernous Malformations. Stroke. 2019 May;50(5):1294-1301. doi: 10.1161/STROKEAHA.118.022314. No abstract available.
Hart BL, Mabray MC, Morrison L, Whitehead KJ, Kim H. Systemic and CNS manifestations of inherited cerebrovascular malformations. Clin Imaging. 2021 Jul;75:55-66. doi: 10.1016/j.clinimag.2021.01.020. Epub 2021 Jan 20.
Choquet H, Pawlikowska L, Nelson J, McCulloch CE, Akers A, Baca B, Khan Y, Hart B, Morrison L, Kim H; Brain Vascular Malformation Consortium (BVMC) Study. Polymorphisms in inflammatory and immune response genes associated with cerebral cavernous malformation type 1 severity. Cerebrovasc Dis. 2014;38(6):433-40. doi: 10.1159/000369200. Epub 2014 Dec 3.
Choquet H, Nelson J, Pawlikowska L, McCulloch CE, Akers A, Baca B, Khan Y, Hart B, Morrison L, Kim H. Association of cardiovascular risk factors with disease severity in cerebral cavernous malformation type 1 subjects with the common Hispanic mutation. Cerebrovasc Dis. 2014;37(1):57-63. doi: 10.1159/000356839. Epub 2013 Dec 21.
Golden M, Saeidi S, Liem B, Marchand E, Morrison L, Hart B. Sensitivity of patients with familial cerebral cavernous malformations to therapeutic radiation. J Med Imaging Radiat Oncol. 2015 Feb;59(1):134-6. doi: 10.1111/1754-9485.12269. Epub 2015 Jan 7.
Hart BL, Taheri S, Rosenberg GA, Morrison LA. Dynamic contrast-enhanced MRI evaluation of cerebral cavernous malformations. Transl Stroke Res. 2013 Oct;4(5):500-6. doi: 10.1007/s12975-013-0285-y. Epub 2013 Sep 21.
Petersen TA, Morrison LA, Schrader RM, Hart BL. Familial versus sporadic cavernous malformations: differences in developmental venous anomaly association and lesion phenotype. AJNR Am J Neuroradiol. 2010 Feb;31(2):377-82. doi: 10.3174/ajnr.A1822. Epub 2009 Oct 15.
Choquet H, Trapani E, Goitre L, Trabalzini L, Akers A, Fontanella M, Hart BL, Morrison LA, Pawlikowska L, Kim H, Retta SF. Cytochrome P450 and matrix metalloproteinase genetic modifiers of disease severity in Cerebral Cavernous Malformation type 1. Free Radic Biol Med. 2016 Mar;92:100-109. doi: 10.1016/j.freeradbiomed.2016.01.008. Epub 2016 Jan 19.
Golden MJ, Morrison LA, Kim H, Hart BL. Increased number of white matter lesions in patients with familial cerebral cavernous malformations. AJNR Am J Neuroradiol. 2015 May;36(5):899-903. doi: 10.3174/ajnr.A4200. Epub 2015 Jan 2.
Zou X, Hart BL, Mabray M, Bartlett MR, Bian W, Nelson J, Morrison LA, McCulloch CE, Hess CP, Lupo JM, Kim H. Automated algorithm for counting microbleeds in patients with familial cerebral cavernous malformations. Neuroradiology. 2017 Jul;59(7):685-690. doi: 10.1007/s00234-017-1845-8. Epub 2017 May 22.
Strickland CD, Eberhardt SC, Bartlett MR, Nelson J, Kim H, Morrison LA, Hart BL. Familial Cerebral Cavernous Malformations Are Associated with Adrenal Calcifications on CT Scans: An Imaging Biomarker for a Hereditary Cerebrovascular Condition. Radiology. 2017 Aug;284(2):443-450. doi: 10.1148/radiol.2017161127. Epub 2017 Mar 20.
Akers A, Al-Shahi Salman R, A Awad I, Dahlem K, Flemming K, Hart B, Kim H, Jusue-Torres I, Kondziolka D, Lee C, Morrison L, Rigamonti D, Rebeiz T, Tournier-Lasserve E, Waggoner D, Whitehead K. Synopsis of Guidelines for the Clinical Management of Cerebral Cavernous Malformations: Consensus Recommendations Based on Systematic Literature Review by the Angioma Alliance Scientific Advisory Board Clinical Experts Panel. Neurosurgery. 2017 May 1;80(5):665-680. doi: 10.1093/neuros/nyx091.
Tang AT, Choi JP, Kotzin JJ, Yang Y, Hong CC, Hobson N, Girard R, Zeineddine HA, Lightle R, Moore T, Cao Y, Shenkar R, Chen M, Mericko P, Yang J, Li L, Tanes C, Kobuley D, Vosa U, Whitehead KJ, Li DY, Franke L, Hart B, Schwaninger M, Henao-Mejia J, Morrison L, Kim H, Awad IA, Zheng X, Kahn ML. Endothelial TLR4 and the microbiome drive cerebral cavernous malformations. Nature. 2017 May 18;545(7654):305-310. doi: 10.1038/nature22075. Epub 2017 May 10.
Morrison MA, Payabvash S, Chen Y, Avadiappan S, Shah M, Zou X, Hess CP, Lupo JM. A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning. Neuroimage Clin. 2018 Aug 4;20:498-505. doi: 10.1016/j.nicl.2018.08.002. eCollection 2018.
Mabray MC, Caprihan A, Nelson J, McCulloch CE, Zafar A, Kim H, Hart BL, Morrison L. Effect of Simvastatin on Permeability in Cerebral Cavernous Malformation Type 1 Patients: Results from a Pilot Small Randomized Controlled Clinical Trial. Transl Stroke Res. 2020 Jun;11(3):319-321. doi: 10.1007/s12975-019-00737-4. Epub 2019 Oct 23. No abstract available.
Tang AT, Sullivan KR, Hong CC, Goddard LM, Mahadevan A, Ren A, Pardo H, Peiper A, Griffin E, Tanes C, Mattei LM, Yang J, Li L, Mericko-Ishizuka P, Shen L, Hobson N, Girard R, Lightle R, Moore T, Shenkar R, Polster SP, Rodel CJ, Li N, Zhu Q, Whitehead KJ, Zheng X, Akers A, Morrison L, Kim H, Bittinger K, Lengner CJ, Schwaninger M, Velcich A, Augenlicht L, Abdelilah-Seyfried S, Min W, Marchuk DA, Awad IA, Kahn ML. Distinct cellular roles for PDCD10 define a gut-brain axis in cerebral cavernous malformation. Sci Transl Med. 2019 Nov 27;11(520):eaaw3521. doi: 10.1126/scitranslmed.aaw3521.
Tandberg SR, Bocklage T, Bartlett MR, Morrison LA, Nelson J, Hart BL. Vertebral Intraosseous Vascular Malformations in a Familial Cerebral Cavernous Malformation Population: Prevalence, Histologic Features, and Associations With CNS Disease. AJR Am J Roentgenol. 2020 Feb;214(2):428-436. doi: 10.2214/AJR.19.21492. Epub 2019 Dec 11.
Manole AK, Forrester VJ, Zlotoff BJ, Hart BL, Morrison LA. Cutaneous findings of familial cerebral cavernous malformation syndrome due to the common Hispanic mutation. Am J Med Genet A. 2020 May;182(5):1066-1072. doi: 10.1002/ajmg.a.61519. Epub 2020 Feb 26.
Campbell R, Petranovich CL, Cheek S, Morrison L, Hart B. Subjective Cognitive Concerns and Attitudes toward Genetic Testing Are Associated with Depressive Symptoms and Quality of Life after Genetic Testing for the Cerebral Cavernous Malformation Common Hispanic Mutation (CCM1). J Behav Brain Sci. 2020 Feb;10(2):118-127. doi: 10.4236/jbbs.2020.102007. Epub 2020 Feb 25.
Mabray MC, Starcevich J, Hallstrom J, Robinson M, Bartlett M, Nelson J, Zafar A, Kim H, Morrison L, Hart BL. High Prevalence of Spinal Cord Cavernous Malformations in the Familial Cerebral Cavernous Malformations Type 1 Cohort. AJNR Am J Neuroradiol. 2020 Jun;41(6):1126-1130. doi: 10.3174/ajnr.A6584. Epub 2020 May 28.
Polster SP, Sharma A, Tanes C, Tang AT, Mericko P, Cao Y, Carrion-Penagos J, Girard R, Koskimaki J, Zhang D, Stadnik A, Romanos SG, Lyne SB, Shenkar R, Yan K, Lee C, Akers A, Morrison L, Robinson M, Zafar A, Bittinger K, Kim H, Gilbert JA, Kahn ML, Shen L, Awad IA. Permissive microbiome characterizes human subjects with a neurovascular disease cavernous angioma. Nat Commun. 2020 May 27;11(1):2659. doi: 10.1038/s41467-020-16436-w.
Weinsheimer S, Nelson J, Abla AA, Ko NU, Tsang C, Okoye O, Zabramski JM, Akers A, Zafar A, Mabray MC, Hart BL, Morrison L, McCulloch CE, Kim H; Brain Vascular Malformation Consortium Cerebral Cavernous Malformation Investigator Group *. Intracranial Hemorrhage Rate and Lesion Burden in Patients With Familial Cerebral Cavernous Malformation. J Am Heart Assoc. 2023 Feb 7;12(3):e027572. doi: 10.1161/JAHA.122.027572. Epub 2023 Jan 25.
Fox CK, Nelson J, McCulloch CE, Weinsheimer S, Pawlikowska L, Hart B, Mabray MC, Zafar A, Morrison L, Zabramski JM, Akers A, Kim H. Seizure Incidence Rates in Children and Adults With Familial Cerebral Cavernous Malformations. Neurology. 2021 Sep 20;97(12):e1210-e1216. doi: 10.1212/WNL.0000000000012569.
Choksi F, Weinsheimer S, Nelson J, Pawlikowska L, Fox CK, Zafar A, Mabray MC, Zabramski J, Akers A, Hart BL, Morrison L, McCulloch CE, Kim H. Assessing the association of common genetic variants in EPHB4 and RASA1 with phenotype severity in familial cerebral cavernous malformation. Mol Genet Genomic Med. 2021 Oct;9(10):e1794. doi: 10.1002/mgg3.1794. Epub 2021 Sep 7.
Wetzel-Strong SE, Weinsheimer S, Nelson J, Pawlikowska L, Clark D, Starr MD, Liu Y, Kim H, Faughnan ME, Nixon AB, Marchuk DA. Pilot investigation of circulating angiogenic and inflammatory biomarkers associated with vascular malformations. Orphanet J Rare Dis. 2021 Sep 3;16(1):372. doi: 10.1186/s13023-021-02009-7.

Neuro-genetic aided design of modified H-ZSM-5 catalyst for catalytic conversion of methanol to gasoline range hydrocarbons

Authors: Niaei, Aligholi Badiki, Tohid Mahmuodi Nabavi, Seyed Reza et al.

Source: Journal of the Taiwan Institute of Chemical Engineers. Mar2013, Vol. 44 Issue 2, p247-256. 10p.

Subject Terms: Gasoline, Catalysts, Methanol, Hydrocarbons, Genetic algorithms, Chemical kinetics