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Journal articles on the topic 'Monitoring growth'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Zeferino, Angélica M. B., Antônio A. Barros Filho, Heloisa Bettiol, and Marco A. Barbieri. "Monitoring growth." Jornal de Pediatria 79, no. 7 (May 15, 2003): 23–32. http://dx.doi.org/10.2223/jped.995.

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2

Dixon, R. A., David Morley, Paul Shears, and ChristopherE Lennox. "GROWTH MONITORING." Lancet 327, no. 8473 (January 1986): 152–53. http://dx.doi.org/10.1016/s0140-6736(86)92285-3.

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3

Hall;, D. M. B. "Growth monitoring." Archives of Disease in Childhood 82, no. 1 (January 1, 2000): 10–15. http://dx.doi.org/10.1136/adc.82.1.10.

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4

HEALY, M. J. R. "Growth monitoring." Archives of Disease in Childhood 82, no. 5 (May 1, 2000): 428i—428. http://dx.doi.org/10.1136/adc.82.5.428i.

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5

MORLEY, D. "Growth monitoring." Archives of Disease in Childhood 84, no. 1 (January 1, 2001): 89c—89. http://dx.doi.org/10.1136/adc.84.1.89c.

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6

Bentley, MargaretE, RebeccaJ Stoltzfus, LauraE Caulfield, David Brewster, DavidA Ross, Paul Garner, and David Morley. "Growth monitoring." Lancet 342, no. 8873 (September 1993): 749–50. http://dx.doi.org/10.1016/0140-6736(93)91745-8.

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7

Duran, Ibrahim, Kyriakos Martakis, Christina Stark, Marcel Ballmann, Stefanie Hamacher, Eckhard Schoenau, Oliver Semler, and Martin Hellmich. "Suitability of growth standards for growth monitoring in children with genetic diseases." Anthropologischer Anzeiger 76, no. 1 (March 28, 2019): 15–28. http://dx.doi.org/10.1127/anthranz/2019/0932.

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8

Kuruba, Padmaja, and V. Madhusudhan. "Smart Growth Monitoring System in Agriculture Using IoT." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12-SPECIAL ISSUE (December 31, 2019): 620–30. http://dx.doi.org/10.5373/jardcs/v11sp12/20193258.

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9

DAVIES, M. K. "Infant growth monitoring." Archives of Disease in Childhood 84, no. 5 (May 1, 2001): 386. http://dx.doi.org/10.1136/adc.84.5.386.

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10

Hall, D. M. B. "Monitoring children's growth." BMJ 311, no. 7005 (September 2, 1995): 583–84. http://dx.doi.org/10.1136/bmj.311.7005.583.

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11

Hindmarsh, P. C. "Monitoring children's growth." BMJ 312, no. 7023 (January 13, 1996): 122. http://dx.doi.org/10.1136/bmj.312.7023.122a.

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12

Brook, C. G. D. "Monitoring of growth." Lancet 340, no. 8819 (September 1992): 612. http://dx.doi.org/10.1016/0140-6736(92)92147-8.

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13

Advanced Scientific Instrumentation. "Crack growth monitoring." NDT & E International 24, no. 1 (February 1991): 56. http://dx.doi.org/10.1016/0963-8695(91)90806-e.

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14

Joseph, Leema. "Innovative Growth Monitoring Chart." International Journal of Nursing Care 1, no. 2 (2013): 39. http://dx.doi.org/10.5958/j.2320-8651.1.2.030.

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15

GEREIN, NANCY. "Is growth monitoring worthwhile?" Health Policy and Planning 3, no. 3 (1988): 181–94. http://dx.doi.org/10.1093/heapol/3.3.181.

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16

Welch, D. E., L. M. Hively, and R. F. Holdaway. "Nonlinear crack growth monitoring." International Journal of Fatigue 23 (2001): 463–70. http://dx.doi.org/10.1016/s0142-1123(01)00145-1.

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17

Carsley, Sarah E., Karen Tu, and Catherine Birken. "Implementing growth monitoring recommendations." Canadian Medical Association Journal 187, no. 18 (December 7, 2015): 1391.1–1391. http://dx.doi.org/10.1503/cmaj.1150073.

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18

Blethen, Sandra L. "Monitoring Growth Hormone Treatment." Endocrinologist 6, no. 5 (September 1996): 369–74. http://dx.doi.org/10.1097/00019616-199609000-00004.

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19

Greaves, J. P., and L. Hendrata. "Breastfeeding and growth monitoring." International Journal of Gynecology & Obstetrics 31 (1990): 121–23. http://dx.doi.org/10.1016/0020-7292(90)90089-4.

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20

Reutsky, Vadim N., Ben Harte, Borzdov Eimf, and Yuri N. Palyanov. "Monitoring diamond crystal growth, a combined experimental and SIMS study." European Journal of Mineralogy 20, no. 3 (May 29, 2008): 365–74. http://dx.doi.org/10.1127/0935-1221/2008/0020-1816.

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21

Cole, T. J. "Growth monitoring with the British 1990 growth reference." Archives of Disease in Childhood 76, no. 1 (January 1, 1997): 47–49. http://dx.doi.org/10.1136/adc.76.1.47.

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22

Henry, Judith J. "Routine growth monitoring and assessment of growth disorders." Journal of Pediatric Health Care 6, no. 5 (September 1992): 291–301. http://dx.doi.org/10.1016/0891-5245(92)90095-l.

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23

Hermanussen, Michael. "Difficulties in standardising growth monitoring." Acta Paediatrica 107, no. 7 (May 21, 2018): 1113–15. http://dx.doi.org/10.1111/apa.14371.

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24

Villar, José, and José M. Belizán. "Technology Assessment: Monitoring Fetal Growth." International Journal of Technology Assessment in Health Care 1, no. 4 (October 1985): 833–41. http://dx.doi.org/10.1017/s0266462300001811.

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The field of perinatal medicine has been experiencing dramatic changes recently, mostly due to technological breakthroughs in antepartum and intrapartum care. Concomitantly, a substantial decline in perinatal morbidity and mortality has been observed. Whether these two phenomena are causally related has yet to be demonstrated. In fact, a recent report has suggested that this may not be the case (18).

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25

Agwu, J. C. "Community growth monitoring in practice." Archives of Disease in Childhood 89, no. 4 (April 1, 2004): 394—a—394. http://dx.doi.org/10.1136/adc.2002.022764.

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26

Brescia Jr., Peter J. "Monitoring Cell Growth in Microplates." Genetic Engineering & Biotechnology News 31, no. 7 (April 2011): 26–27. http://dx.doi.org/10.1089/gen.31.7.11.

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27

Ghafari, Joseph G., Frances S. Shofer, Larry L. Laster, Diane L. Markowitz, Susan Silverton, and Solomon H. Katz. "Monitoring growth during orthodontic treatment." Seminars in Orthodontics 1, no. 3 (September 1995): 165–75. http://dx.doi.org/10.1016/s1073-8746(95)80020-4.

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28

Voss, L. D. "Changing practice in growth monitoring." BMJ 318, no. 7180 (February 6, 1999): 344–45. http://dx.doi.org/10.1136/bmj.318.7180.344.

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29

Wagner, V., D. Drews, N. Esser, D. R. T. Zahn, J. Geurts, and W. Richter. "Raman monitoring of semiconductor growth." Journal of Applied Physics 75, no. 11 (June 1994): 7330–33. http://dx.doi.org/10.1063/1.356644.

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30

Owusu, W. Bruce, and Anna Lartey. "Growth Monitoring: Experience from Ghana." Food and Nutrition Bulletin 14, no. 2 (June 1992): 1–3. http://dx.doi.org/10.1177/156482659201400214.

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Mothers’ understanding of growth charts is an essential component of growth-monitoring programmes. This study investigated mothers’ interpretation of growth charts as they attended child welfare clinics in the greater Accra region of Ghana. Eight hundred seventy-five mothers were interviewed using questionnaires and sample growth charts. Factors impeding attendance at the clinics included business, forgetting, travel, and lack of knowledge. Nearly 40% of the mothers had no idea of the meaning or purpose of growth charts. Efforts to enhance the awareness of mothers and children's caretakers must be intensified.

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31

More, Judy. "Monitoring infants' and children's growth." Practice Nursing 20, no. 7 (July 2009): 364–67. http://dx.doi.org/10.12968/pnur.2009.20.7.43188.

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32

George, Sabu, Michael Latham, Nancy Gerein, and Jenny Cervinskas. "The practice of growth monitoring." Lancet 340, no. 8824 (October 1992): 918. http://dx.doi.org/10.1016/0140-6736(92)93335-k.

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33

Ghosh, Shanti. "Growth monitoring - Lessons from India." Indian Journal of Pediatrics 55, S1 (May 1988): S67—S73. http://dx.doi.org/10.1007/bf02810392.

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34

Agosto, Arianna, Alexandra Campmas, Paolo Giudici, and Andrea Renda. "Monitoring COVID‐19 contagion growth." Statistics in Medicine 40, no. 18 (May 11, 2021): 4150–60. http://dx.doi.org/10.1002/sim.9020.

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35

Li, Huaimin, Weipan Lin, Fangrong Pang, Xiaoping Jiang, Weixing Cao, Yan Zhu, and Jun Ni. "Monitoring Wheat Growth Using a Portable Three-Band Instrument for Crop Growth Monitoring and Diagnosis." Sensors 20, no. 10 (May 20, 2020): 2894. http://dx.doi.org/10.3390/s20102894.

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An instrument developed to monitor and diagnose crop growth can quickly and non-destructively obtain crop growth information, which is helpful for crop field production and management. Focusing on the problems with existing two-band instruments used for crop growth monitoring and diagnosis, such as insufficient information available on crop growth and low accuracy of some growth indices retrieval, our research team developed a portable three-band instrument for crop-growth monitoring and diagnosis (CGMD) that obtains a larger amount of information. Based on CGMD, this paper carried out studies on monitoring wheat growth indices. According to the acquired three-band reflectance spectra, the combined indices were constructed by combining different bands, two-band vegetation indices (NDVI, RVI, and DVI), and three-band vegetation indices (TVI-1 and TVI-2). The fitting results of the vegetation indices obtained by CGMD and the commercial instrument FieldSpec HandHeld2 was high and the new instrument could be used for monitoring the canopy vegetation indices. By fitting each vegetation index to the growth index, the results showed that the optimal vegetation indices corresponding to leaf area index (LAI), leaf dry weight (LDW), leaf nitrogen content (LNC), and leaf nitrogen accumulation (LNA) were TVI-2, TVI-1, NDVI (R730, R815), and NDVI (R730, R815), respectively. R2 values corresponding to LAI, LDW, LNC and LNA were 0.64, 0.84, 0.60, and 0.82, respectively, and their relative root mean square error (RRMSE) values were 0.29, 0.26, 0.17, and 0.30, respectively. The addition of the red spectral band to CGMD effectively improved the monitoring results of wheat LAI and LDW. Focusing the problem of vegetation index saturation, this paper proposed a method to construct the wheat-growth-index spectral monitoring models that were defined according to the growth periods. It improved the prediction accuracy of LAI, LDW, and LNA, with R2 values of 0.79, 0.85, and 0.85, respectively, and the RRMSE values of these growth indices were 0.22, 0.23, and 0.28, respectively. The method proposed here could be used for the guidance of wheat field cultivation.

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36

Vanniamparambil, Prashanth Abraham, Ivan Bartoli, Kavan Hazeli, Jefferson Cuadra, Eric Schwartz, Raghavendra Saralaya, and Antonios Kontsos. "An integrated structural health monitoring approach for crack growth monitoring." Journal of Intelligent Material Systems and Structures 23, no. 14 (June 2012): 1563–73. http://dx.doi.org/10.1177/1045389x12447987.

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37

Ceulemans, R. J. "PLANT GROWTH OPTIMISATION BY PHOTOSYNTHETIC MONITORING." Acta Horticulturae, no. 174 (December 1985): 309–12. http://dx.doi.org/10.17660/actahortic.1985.174.39.

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38

de Onis, Mercedes, Trudy M. A. Wijnhoven, and Adelheid W. Onyango. "Worldwide practices in child growth monitoring." Journal of Pediatrics 144, no. 4 (April 2004): 461–65. http://dx.doi.org/10.1016/j.jpeds.2003.12.034.

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39

Daniels, Stephen R. "Monitoring children for growth and overweight." Journal of Pediatrics 144, no. 4 (April 2004): A2. http://dx.doi.org/10.1016/j.jpeds.2004.03.009.

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40

Cooke , Richard J. "Postnatal Growth Monitoring in Preterm Infants." Neonatology 114, no. 2 (2018): 181–83. http://dx.doi.org/10.1159/000489554.

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41

Romijn, Remco, and Jeroen Groenenboom. "Acoustic monitoring of hydraulic fracture growth." First Break 15, no. 9 (September 1997): 295–303. http://dx.doi.org/10.1046/j.1365-2397.1997.00671.x.

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42

Smolders, Erik, Roel Merckx, Frans Schoovaerts, and Karel Vlassak. "Continuous shoot growth monitoring in hydroponics." Physiologia Plantarum 83, no. 1 (September 1991): 83–92. http://dx.doi.org/10.1034/j.1399-3054.1991.830113.x.

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43

Schlebrowski, T., H. Bahre, M. Böke, and J. Winter. "Monitoring particle growth in deposition plasmas." Plasma Sources Science and Technology 22, no. 6 (November 28, 2013): 065014. http://dx.doi.org/10.1088/0963-0252/22/6/065014.

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44

Feng, Yuan, Luo Xiao, Cai Li, Stephanie T. Chen, and Eric O. Ohuma. "Correlation models for monitoring fetal growth." Statistical Methods in Medical Research 29, no. 10 (March 23, 2020): 2795–813. http://dx.doi.org/10.1177/0962280220905623.

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Ultrasound growth measurements are monitored to evaluate if a fetus is growing normally compared with a defined standard chart at a specified gestational age. Using data from the Fetal Growth Longitudinal Study of the INTERGROWTH-21st project, we have modelled the longitudinal dependence of fetal head circumference, biparietal diameter, occipito-frontal diameter, abdominal circumference, and femur length using a two-stage approach. The first stage involved finding a suitable transformation of the raw fetal measurements (as the marginal distributions of ultrasound measurements were non-normal) to standardized deviations (Z-scores). In the second stage, a correlation model for a Gaussian process is fitted, yielding a correlation for any pair of observations made between 14 and 40 weeks. The correlation structure of the fetal Z-score can be used to assess whether the growth, for example, between successive measurements is satisfactory. The paper is accompanied by a Shiny application, see https://lxiao5.shinyapps.io/shinycalculator/ .

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45

Hall, D. M. B. "Growth Monitoring: The Next Five Years." Journal of Medical Screening 2, no. 3 (September 1995): 174–78. http://dx.doi.org/10.1177/096914139500200317.

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46

Patrice Jelliffe, E. F., and D. B. Jelliffe. "Algorithms, Growth Monitoring, and Nutritional Intervention." Journal of Tropical Pediatrics 33, no. 6 (December 1, 1987): 290–95. http://dx.doi.org/10.1093/tropej/33.6.290.

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47

Wall, Alison. "Early childhood nutrition and growth monitoring." Primary Health Care 18, no. 7 (September 14, 2008): 16–18. http://dx.doi.org/10.7748/phc2008.09.18.7.16.c6698.

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48

Argyle, Jenny, Allan H. Seheult, and David A. Wooff. "Correlation models for monitoring child growth." Statistics in Medicine 27, no. 6 (2008): 888–904. http://dx.doi.org/10.1002/sim.2973.

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49

Moon, R. J., P. Wilson, F. J. Kirkham, and J. H. Davies. "Growth monitoring following traumatic brain injury." Archives of Disease in Childhood 94, no. 9 (November 26, 2008): 699–701. http://dx.doi.org/10.1136/adc.2008.145235.

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50

Groenenboom, Jeroen, and Dirkjan B. van Dam. "Monitoring hydraulic fracture growth: Laboratory experiments." GEOPHYSICS 65, no. 2 (March 2000): 603–11. http://dx.doi.org/10.1190/1.1444756.

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We carry out small‐scale hydraulic fracture experiments to investigate the physics of hydraulic fracturing. The laboratory experiments are combined with time‐lapse ultrasonic measurements with active sources using both compressional and shear‐wave transducers. For the time‐lapse measurements we focus on ultrasonic measurement changes during fracture growth. As a consequence we can detect the hydraulic fracture and characterize its shape and geometry during growth. Hence, this paper deals with fracture characterization using time‐lapse acoustic data. During fracture growth the acoustic waves generate diffractions at the tip of the fracture. The direct compressional and shear diffractions are used to locate the position of the tip of the fracture. More detailed analysis of these diffractions can be used to obtain information on the geometry and configuration of the fracture tip, including the creation of a zone that is not penetrated by fluid. Furthermore, it appears that the acoustic diffraction is generated mainly at the fluid front and only weakly at the dry tip. In addition, the wavefield that has been transmitted through the hydraulic fracture is measured. Shear‐wave transmissions are shadowed because the shear modulus vanishes inside the fluid‐filled fracture. From this observation we conclude that the fracture is mechanically open. In other words, no friction occurs related to the movement of fracture faces that are in mechanical contact. Compressional transmissions show a distinctive dispersion relative to the measurement in the unfractured medium. This dispersion can be used to determine the width (or aperture) of the fracture by fitting the measured dispersion with the theoretical prediction as a function of the unknown fracture width. We show that the width profile of the fracture can be reconstructed by using a set of transmission records with different source and receiver locations. By performing a validation experiment, we show that the width determination method is reliable, although the estimated fracture width is only a few percent of the incident wavelength. The strength of the method relies on time‐lapse measurements combined with fitting the changes in the measured waveforms during the experiment. The combination of diffractions and transmissions helps us visualize the dynamic process of hydraulic fracture growth. Hence, acoustic measurements with active sources prove their usefulness for fracture characterization.

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