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Journal articles on the topic 'Bio-modelling'

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Author: Grafiati

Published: 16 March 2023

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1

Davia, Miguel, Antonio Jimeno-Morenilla, and Faustino Salas. "Footwear bio-modelling: An industrial approach." Computer-Aided Design 45, no. 12 (December 2013): 1575–90. http://dx.doi.org/10.1016/j.cad.2013.08.006.

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2

Ciocchetta, Federica, and Maria Luisa Guerriero. "Modelling Biological Compartments in Bio-PEPA." Electronic Notes in Theoretical Computer Science 227 (January 2009): 77–95. http://dx.doi.org/10.1016/j.entcs.2008.12.105.

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3

Wodołażski, Artur, and Adam Smoliński. "Bio-Hydrogen Production in Packed Bed Continuous Plug Flow Reactor—CFD-Multiphase Modelling." Processes 10, no. 10 (September 20, 2022): 1907. http://dx.doi.org/10.3390/pr10101907.

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This research study investigates the modelling and simulation of biomass anaerobic dark fermentation in bio-hydrogen production in a continuous plug flow reactor. A CFD multiphase full transient model in long-term horizons was adopted to model dark fermentation biohydrogen production in continuous mode. Both the continuous discharge of biomass, which prevents the accumulation of solid parts, and the recirculation of the liquid phase ensure constant access to the nutrient solution. The effect of the hydraulic retention time (HRT), pH and the feed rate on the bio-hydrogen yield and production rates were examined in the simulation stage. Metabolite proportions (VFA: acetic, propionic, butyric) constitute important parameters influencing the bio-hydrogen production efficiency. The model of substrate inhibition on bio-hydrogen production from glucose by attached cells of the microorganism T. neapolitana applied to the modelling of the kinetics of bio-hydrogen production was used. The modelling and simulation of a continuous plug flow (bio)reactor in biohydrogen production is an important part of the process design, modelling and optimization of the biological H2 production pathway.

4

Urama, K. C., C. F. Dilks, S. M. Dunn, and R. C. Ferrier. "Socio-economic and bio-physical modelling of diffuse pollution: closing the gaps." River Systems 17, no. 1-2 (July 28, 2006): 175–99. http://dx.doi.org/10.1127/lr/17/2006/175.

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5

Ogundele, O. S., B. K. Alese, and O. O. Mathew. "A Bio-Inspired Concept for Information Security Modelling." International Journal of Green Computing 1, no. 1 (January 2010): 53–67. http://dx.doi.org/10.4018/jgc.2010010106.

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Bio-inspired models for information security were designed to demonstrate the performances by which biology achieves security. Existing research focuses on borrowing partial ideas from biological systems to resolve some facet of information security in a network environment, such as intrusion detection and fault tolerance. This work uses the bio-inspired concept of the body system to demonstrate an information security model that makes use of the immune system. The white blood cells (leucocytes) produce the antibodies (lymphocyte) that fight against all antigens (foreign materials) and kill them. The skin layer of the body contains keratin that prevents microorganisms from penetrating the body. The authors relate the processes in biological systems to information security using mechanisms of the immune system in molecular biology as the key paradigm. Theory of set and algebra were used to describe the relationship between the immune system and the information security model. A simple simulator was developed to demonstrate the operation of the designed bio-inspired model. Although the simulator was tested with assumed data, the work offered insight into how the immune system of biology can be adapted to design and implement a more secure information security system.

6

Nasir, Arooj, Dumitru Baleanu, Ali Raza, Pervez Anwar, Nauman Ahmed, Muhammad Rafiq, and Tahir Nawaz Cheema. "Bio-Inspired Modelling of Disease Through Delayed Strategies." Computers, Materials & Continua 73, no. 3 (2022): 5717–34. http://dx.doi.org/10.32604/cmc.2022.031879.

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7

Kabbej, Marouane, Valérie Guillard, Hélène Angellier-Coussy, Caroline Wolf, Nathalie Gontard, and Sébastien Gaucel. "3D Modelling of Mass Transfer into Bio-Composite." Polymers 13, no. 14 (July 9, 2021): 2257. http://dx.doi.org/10.3390/polym13142257.

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A three-dimensional model structure that allows considering interphase layer around permeable inclusions is developed to predict water vapor permeability in composite materials made of a matrix Poly(3-HydroxyButyrate-co-3-HydroxyValerate) (PHBV) including Wheat Straw Fiber (WSF) particles. About 500 two-phase structures corresponding to composites of different particles volume fractions (5.14−11.4−19.52 % v/v) generated using experimental particles’ size distribution have permitted to capture all the variability of the experimental material. These structures have served as a basis to create three-phase structures including interphase zone of altered polymer property surrounding each particle. Finite Element Method (FEM) applied on these structures has permitted to calculate the relative permeability (ratio between composite and neat matrix permeability P/Pm). The numerical results of the two-phase model are consistent with the experimental data for volume fraction lower than 11.4 %v/v but the large upturn of the experimental relative permeability for highest volume fraction is not well represented by the two-phase model. Among hypothesis made to explain model’s deviation, the presence of an interphase with its own transfer properties is numerically tested: numerical exploration made with the three-phase model proves that an interphase of 5 µm thick, with diffusivity of Di≥1×10−10 m2·s−1, would explain the large upturn of permeability at high volume fraction.

8

Lawrance, Ani, Mani Veera Santhoshi Gollapalli, S. Savithri, Ajit Haridas, and A. Arunagiri. "Modelling and simulation of food waste bio-drying." Chemosphere 294 (May 2022): 133711. http://dx.doi.org/10.1016/j.chemosphere.2022.133711.

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9

Kumar, Y. Ravi. "Bio-Modelling Using Rapid Prototyping by Fused Deposition." Advanced Materials Research 488-489 (March 2012): 1021–25. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1021.

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This work deals with planning the dental surgery by making bio-model of the jaw of the patient using rapid prototyping (RP) technique called fused deposition modelling (FDM). The bio-model is not only increasing the safety of dental surgery but also aiding diagnosis and treatment planning. Having an exact model of the patient’s jaw in hand would enable a surgeon to plan the surgery more precisely, as compared to one which is planned using 2D images obtained from CT scan, magnetic resonance imaging (MRI) or X-ray. A mock surgery has been performed on the bio-model by making holes using drill bits of the same size and material as the ones used in an actual surgery and after that the implants were placed and screwed into the holes drilled to secure their positions. This drill has been given the surgeon an exact idea of size of the implant and the orientation in which the implant has to be placed and also depth up to which the hole has to be drilled in order to avoid the damage of the Inferior Alveolar Canal.

10

Demongeot, Jacques, Florence Thuderoz, Thierry Pascal Baum, François Berger, and Olivier Cohen. "Bio-array images processing and genetic networks modelling." Comptes Rendus Biologies 326, no. 5 (May 2003): 487–500. http://dx.doi.org/10.1016/s1631-0691(03)00114-8.

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11

Di Sia, Paolo. "Advances in Analytical Modelling for Nano-Bio-Technology." Journal of Nanoscience with Advanced Technology 1, no. 1 (June 22, 2015): 17–19. http://dx.doi.org/10.24218/jnat.2015.04.

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12

Madhab, G. B., C. S. Kumar, and P. K. Mishra. "Modelling and control of a bio-inspired microgripper." International Journal of Manufacturing Technology and Management 21, no. 1/2 (2010): 160. http://dx.doi.org/10.1504/ijmtm.2010.034294.

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13

., Akpan, Nsemeke John, Dr John N. Ugbebor, and Dr (mrs) Ngozi Mbah Udeh. "Modelling Bio-Methane Production In Ruminant Livestock Farming." International Journal of Scientific and Research Publications (IJSRP) 13, no. 1 (January 24, 2023): 159–82. http://dx.doi.org/10.29322/ijsrp.13.01.2023.p13319.

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14

Singh, B. P., and P. K. Sahoo. "Modelling and simulation of a bio-fuelled conventional engine." International Journal of Ambient Energy 34, no. 4 (December 2013): 200–213. http://dx.doi.org/10.1080/01430750.2012.759148.

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15

Tripathi, D., and Osman A. Bég. "Mathematical modelling of peristaltic propulsion of viscoplastic bio-fluids." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 228, no. 1 (November 29, 2013): 67–88. http://dx.doi.org/10.1177/0954411913511584.

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16

Dinsdale, Daniel, and Matias Salibian-Barrera. "Modelling ocean temperatures from bio-probes under preferential sampling." Annals of Applied Statistics 13, no. 2 (June 2019): 713–45. http://dx.doi.org/10.1214/18-aoas1217.

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17

Wörner, Stefan, Boryana Racheva-Iotova, and Stoyan Stoyanov. "Modelling a Bio-Pharmaceutical Company as a Compound Option." IFAC Proceedings Volumes 34, no. 20 (September 2001): 231–36. http://dx.doi.org/10.1016/s1474-6670(17)33070-7.

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18

Rada, E. C., A. Franzinelli, M. Ragazzi, V. Panaitescu, and T. Apostol. "Modelling of PCDD/F release from MSW bio-drying." Chemosphere 68, no. 9 (August 2007): 1669–74. http://dx.doi.org/10.1016/j.chemosphere.2007.03.075.

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19

Chiappino, Simone, Pietro Morerio, Lucio Marcenaro, and Carlo S. Regazzoni. "Bio-inspired relevant interaction modelling in cognitive crowd management." Journal of Ambient Intelligence and Humanized Computing 6, no. 2 (February 15, 2014): 171–92. http://dx.doi.org/10.1007/s12652-014-0224-0.

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20

Di Giulio, S., C. Fabiani, G. Giubileo, and V. Violante. "The bio-artificial endocrine pancreas: modelling and performance evaluation." Journal of Membrane Science 36 (January 1988): 541–52. http://dx.doi.org/10.1016/0376-7388(88)80043-7.

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21

Kumari, A. Pavana, and N. Aruna Kumari. "Mathematical Modelling for The Selection of The Best Source for The Preparation of Bio-Diesel." International Journal of Scientific Research 3, no. 6 (June 1, 2012): 35–36. http://dx.doi.org/10.15373/22778179/june2014/182.

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22

Herrgård, Markus, Sumesh Sukumara, Miguel Campodonico, and Kai Zhuang. "A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals." Biochemical Society Transactions 43, no. 6 (November 27, 2015): 1151–56. http://dx.doi.org/10.1042/bst20150144.

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In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry.

23

Chaturvedi, Purnima, Rohit Kumar, and Sapna Ratan Shah. "Bio-Mechanical and Bio-Rheological Aspects of Sickle Red Cells in Microcirculation: A Mathematical Modelling Approach." Fluids 6, no. 9 (September 8, 2021): 322. http://dx.doi.org/10.3390/fluids6090322.

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Sickle cell disease (SCD) is an inherited monogenic disease characterized by distorted red blood cells that causes vaso-occlusion and vasculopathy. Presently, electrophoresis of haemoglobin and genotyping are used as routine tests for diagnosis of the SCD. These techniques require specialized laboratories and are expensive. The low-cost microfluidics-based diagnostic tool holds a great attention for screening of red blood cell (RBC) deformability. In the present study, lubrication theory has been applied in order to develop a biomechanical model of microcirculation with altered rheological properties of sickle blood in the capillary, which is smaller in size compared to the cell diameter, to explain the multifactorial nature and pathogenesis of vaso-occlusion in SCD. The governing equations have been solved analytically for realistic boundary conditions and simulated using MATLAB. We found that the axial velocity of the cell decreases with a decrease in deformability and compliance. The height of the lubricating film predicts deformation of the cell with respect to local pressure in the microcirculation. Leak back and drag force depend non-linearly on the deformed cell radius with varying viscosity of the plasma and Reynolds number. The modelling predictions of this study is in coherence with experimental results. The analyzed parameters provide unique insights with novel possibilities to design a microfluidics-based effective therapeutic intervention for SCD.

24

Veremieiev, Sergii, A. Brown, P. H. Gaskell, C. R. Glass, N. Kapur, and H. M. Thompson. "MODELLING THE FLOW OF DROPLETS OF BIO-PESTICIDE ON FOLIAGE." Interfacial Phenomena and Heat Transfer 2, no. 1 (2014): 1–14. http://dx.doi.org/10.1615/interfacphenomheattransfer.2014010162.

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25

Assis, Jorge, Lennert Tyberghein, Samuel Bosch, Heroen Verbruggen, Ester A. Serrão, and Olivier De Clerck. "Bio-ORACLE v2.0: Extending marine data layers for bioclimatic modelling." Global Ecology and Biogeography 27, no. 3 (December 29, 2017): 277–84. http://dx.doi.org/10.1111/geb.12693.

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26

Breukers, A., A. Oude Lansink, W. Van Der Werf, and R. Huirne. "Bio-economic modelling of potato brown rot in the Netherlands*." EPPO Bulletin 33, no. 3 (December 2003): 525–27. http://dx.doi.org/10.1111/j.1365-2338.2003.00673.x.

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27

Holloway, Garth, Donald Lacombe, and James P. LeSage. "Spatial Econometric Issues for Bio-Economic and Land-Use Modelling." Journal of Agricultural Economics 58, no. 3 (September 2007): 549–88. http://dx.doi.org/10.1111/j.1477-9552.2007.00127.x.

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28

Rafii-Tabar, H., and H. R. Sepangi. "Modelling meso-scale diffusion processes in stochastic fluid bio-membranes." Computational Materials Science 15, no. 4 (November 1999): 483–92. http://dx.doi.org/10.1016/s0927-0256(99)00034-8.

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29

Kragt, M. E., D. J. Pannell, A. McVittie, A. W. Stott, B. Vosough Ahmadi, and P. Wilson. "Improving interdisciplinary collaboration in bio-economic modelling for agricultural systems." Agricultural Systems 143 (March 2016): 217–24. http://dx.doi.org/10.1016/j.agsy.2015.12.020.

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30

Townsend, Toby J., Stephen J. Ramsden, and Paul Wilson. "Analysing reduced tillage practices within a bio-economic modelling framework." Agricultural Systems 146 (July 2016): 91–102. http://dx.doi.org/10.1016/j.agsy.2016.04.005.

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31

Li, Kang, Xia Hong, and George W. Irwin. "Life System Modelling, Simulation, and Bio-inspired Computing (LSMS 2007)." Neurocomputing 72, no. 1-3 (December 2008): 126–27. http://dx.doi.org/10.1016/j.neucom.2008.08.001.

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32

Sansone, Mario. "Bio-Mathematical Modelling in Tumor Evaluation Via Magnetic Resonance Imaging." Radiology - Open Journal 1, no. 2 (September 20, 2016): e11-e13. http://dx.doi.org/10.17140/roj-1-e003.

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33

Scholz, Miklas, and Robert J. Martin. "Control of bio-regenerated granular activated carbon by spreadsheet modelling." Journal of Chemical Technology & Biotechnology 71, no. 3 (March 1998): 253–61. http://dx.doi.org/10.1002/(sici)1097-4660(199803)71:3<253::aid-jctb834>3.0.co;2-y.

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34

Letov, N., and Y. F. Zhao. "VOLUMETRIC CELLS: A FRAMEWORK FOR A BIO-INSPIRED GEOMETRIC MODELLING METHOD TO SUPPORT HETEROGENEOUS LATTICE STRUCTURES." Proceedings of the Design Society: DESIGN Conference 1 (May 2020): 295–304. http://dx.doi.org/10.1017/dsd.2020.164.

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AbstractCurrent geometrical modelling approaches are unable to handle complex geometrical objects such as heterogeneous lattice structures. In this work, a framework for a novel bio-inspired geometric modelling method is proposed. The method can potentially support geometric modelling of heterogeneous lattice structures. The method utilises discretisation algorithms that are based on cell division processes encountered in nature. The method is verified on two 2D use-cases.

35

Massey, Roslyn, and Ravi Prakash. "Modeling the Double Layer Capacitance Effect in Electrolyte Gated FETs with Gel and Aqueous Electrolytes." Micromachines 12, no. 12 (December 17, 2021): 1569. http://dx.doi.org/10.3390/mi12121569.

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Potential implementation of bio-gel Electrolyte Double Layer capacitors (bio-gel EDLCs) and electrolyte-gated FET biosensors, two commonly reported configurations of bio-electrolytic electronic devices, requires a robust analysis of their complex internal capacitive behavior. Presently there is neither enough of the parameter extraction literature, nor an effective simulation model to represent the transient behavior of these systems. Our work aims to supplement present transient thin film transistor modelling techniques with the reported parameter extraction method, to accurately model both bio-gel EDLC and the aqueous electrolyte gated FET devices. Our parameter extraction method was tested with capacitors analogous to polymer-electrolyte gated FETs, electrolyte gated Field effect transistor (EGOFET) and Organic Electrolyte Gated Field Effect Transistor (OEGFET) capacitance stacks. Our method predicts the input/output electrical behavior of bio-gel EDLC and EGOFET devices far more accurately than conventional DLC techniques, with less than 5% error. It is also more effective in capturing the characteristic aqueous electrolyte charging behavior and maximum charging capability which are unique to these systems, than the conventional DLC Zubieta and the Two branch models. We believe this significant improvement in device simulation is a pivotal step towards further integration and commercial implementation of organic bio-electrolyte devices. The effective reproduction of the transient response of the OEGFET equivalent system also predicts the transient capacitive effects observed in our previously reported label-free OEGFET biosensor devices. This is the first parameter extraction method specifically designed for electrical parameter-based modelling of organic bio-electrolytic capacitor devices.

36

Renotte, C., A. Vande Wouwer, Ph Bogaerts, and M. Remy. "Neural Network Applications in Non-Linear Modelling of (Bio)Chemical Processes." Measurement and Control 34, no. 7 (September 2001): 197–201. http://dx.doi.org/10.1177/002029400103400702.

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In recent years, neural networks have attracted much attention for their potential to address a number of difficult problems in modelling and controlling nonlinear dynamic systems, especially in (bio) chemical engineering. The objective of this paper is to review some of the most widely used approaches to neural-network-based modelling, including plain black box as well as hybrid neural network — first principles modelling. Two specific application examples are used for illustration purposes: a simple tank level-control system is studied in simulation while a challenging bioprocess application is investigated based on experimental data. These applications allow some original concepts and techniques to be introduced.

37

Berelson, W. M., T. Townsend, D. Heggie, P. Ford, A. Longmore, G. Skyring, T. Kilgore, and G. Nicholson. "Modelling bio-irrigation rates in the sediments of Port Phillip Bay." Marine and Freshwater Research 50, no. 6 (1999): 573. http://dx.doi.org/10.1071/mf98076.

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The introduction of a deuterium-enriched tracer to benthic incubation chambers emplaced on the sea floor of Port Phillip Bay provides a method of modelling bio-irrigation within the sediments. Plots of deuterium v. incubation time reveal that all seven chambers, emplaced at four sites, indicate non-diffusive transport of pore-water solutes across the sediment–water interface. Modelling indicates that advection of overlying chamber water must occur to depths of 20–50 cm below the interface and at rates between 150 and 700 mL h–1. Multiple chambers deployed in the same region within the bay are consistent with respect to bio-irrigation depth and rate. This indicates that the distribution of infauna responsible for irrigation is quite consistent within regions defined by sediment type and depth. However, various regions in the bay show distinctly different irrigation rates; thus the distribution and/or activity of infauna is not constant throughout the bay. At the lower rate of pore-water advection, the entire water column in Port Phillip Bay passes through the sediments within 200 days. Dissolved caesium, injected into the chamber, is also an effective tracer of bio-irrigation although adsorption onto sediment particles increases the uncertainty of model results.

38

Deutsch, Andreas, Josué Manik Nava-Sedeño, Simon Syga, and Haralampos Hatzikirou. "BIO-LGCA: A cellular automaton modelling class for analysing collective cell migration." PLOS Computational Biology 17, no. 6 (June 15, 2021): e1009066. http://dx.doi.org/10.1371/journal.pcbi.1009066.

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Collective dynamics in multicellular systems such as biological organs and tissues plays a key role in biological development, regeneration, and pathological conditions. Collective tissue dynamics—understood as population behaviour arising from the interplay of the constituting discrete cells—can be studied with on- and off-lattice agent-based models. However, classical on-lattice agent-based models, also known as cellular automata, fail to replicate key aspects of collective migration, which is a central instance of collective behaviour in multicellular systems. To overcome drawbacks of classical on-lattice models, we introduce an on-lattice, agent-based modelling class for collective cell migration, which we call biological lattice-gas cellular automaton (BIO-LGCA). The BIO-LGCA is characterised by synchronous time updates, and the explicit consideration of individual cell velocities. While rules in classical cellular automata are typically chosen ad hoc, rules for cell-cell and cell-environment interactions in the BIO-LGCA can also be derived from experimental cell migration data or biophysical laws for individual cell migration. We introduce elementary BIO-LGCA models of fundamental cell interactions, which may be combined in a modular fashion to model complex multicellular phenomena. We exemplify the mathematical mean-field analysis of specific BIO-LGCA models, which allows to explain collective behaviour. The first example predicts the formation of clusters in adhesively interacting cells. The second example is based on a novel BIO-LGCA combining adhesive interactions and alignment. For this model, our analysis clarifies the nature of the recently discovered invasion plasticity of breast cancer cells in heterogeneous environments.

39

Mah, Yau Seng, Amy Ee Ling Wong, and Fang Yenn Teo. "Modelling of Grassed Road Divider as Bio-Retention System for Urban Road Drainage." Journal of Applied Science & Process Engineering 5, no. 2 (September 30, 2018): 266–76. http://dx.doi.org/10.33736/jaspe.909.2018.

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An evaluation on the applicability of bio-retention system in grassed road divider under high rainfall of equatorial region was conducted by developing computer-aided stormwater models using USEPA SWMM 5.1. The models simulated road runoffs with and without bio-retention systems. A single unit of bio-retention system tested here was 3 m in width, 6 m in length with 150 mm of ponding depth and 600 mm of soil/storage depth. Results indicated that soil types of loamy sand, sandy loam and loam showed similar performance in reducing runoff. With installation of bio-retention system, road runoff could be reduced 40-50% when subjected to 60 minutes of 2-, 5- and 10-year ARI rain events. The results obtained from the simulation were encouraging that bio-retention system in grassed road divider could function to augment the existing urban road drainage.

40

Shirmohammadi, Maryam, Prasad K. D. V. Yarlagadda, P. Gudimetla, and V. Kosse. "Mechanical Behaviours of Pumpkin Peel under Compression Test." Advanced Materials Research 337 (September 2011): 3–9. http://dx.doi.org/10.4028/www.scientific.net/amr.337.3.

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Abstract Mechanical damages such as bruising, collision and impact during food processing stages diminish quality and quantity of productions as well as efficiency of operations. Studying mechanical characteristics of food materials will help to enhance current industrial practices. Mechanical properties of fruits and vegetables describe how these materials behave under loading in real industrial operations. Optimizing and designing more efficient equipments require accurate and precise information of tissue behaviours. FE modelling of food industrial processes is an effective method of studying interrelation of variables during mechanical operation. In this study, empirical investigation has been done on mechanical properties of pumpkin peel. The test was a part of FE modelling and simulation of mechanical peeling stage of tough skinned vegetables. The compression test has been conducted on Jap variety of pumpkin. Additionally, stress strain curve, bio-yield and toughness of pumpkin skin have been calculated. The required energy for reaching bio-yield point was 493.75, 507.71 and 451.71 N.mm for 1.25, 10 and 20 mm/min loading speed respectively. Average value of force in bio-yield point for pumpkin peel was 310 N.

41

SO, Magnus, Mitsuharu TERASHIMA, Rajeev GOEL, and Hidenari YASUI. "Modelling the Bio-Clogging of Multispecies Biofilms in Sponge Carrier Media." Journal of Water and Environment Technology 13, no. 3 (2015): 263–78. http://dx.doi.org/10.2965/jwet.2015.263.

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42

Fang, Yinfeng, Jiani Yang, Dalin Zhou, and Zhaojie Ju. "Modelling EMG driven wrist movements using a bio-inspired neural network." Neurocomputing 470 (January 2022): 89–98. http://dx.doi.org/10.1016/j.neucom.2021.10.104.

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43

Lindawati, L., Y. Mardyani, N. D. Yanti, and M. Boer. "Assessing and managing demersal fisheries in Sunda Strait: Bio-economic modelling." IOP Conference Series: Earth and Environmental Science 860, no. 1 (October 1, 2021): 012062. http://dx.doi.org/10.1088/1755-1315/860/1/012062.

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44

N. Tande, Lifita, and Valerie Dupont. "Autothermal reforming of palm empty fruit bunch bio-oil: thermodynamic modelling." AIMS Energy 4, no. 1 (2016): 68–92. http://dx.doi.org/10.3934/energy.2016.1.68.

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45

Ammenberg, P., P. Flink, T. Lindell, D. Pierson, and N. Strombeck. "Bio-optical modelling combined with remote sensing to assess water quality." International Journal of Remote Sensing 23, no. 8 (January 2002): 1621–38. http://dx.doi.org/10.1080/01431160110071860.

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46

Imrith, Manoj Kumar, Satyadev Rosunee, and Roshan Unmar. "Bio-inspired knitted fabric development using 3D modelling and image processing." Journal of The Textile Institute 111, no. 8 (November 8, 2019): 1123–39. http://dx.doi.org/10.1080/00405000.2019.1686880.

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Tyberghein, Lennert, Heroen Verbruggen, Klaas Pauly, Charles Troupin, Frederic Mineur, and Olivier De Clerck. "Bio-ORACLE: a global environmental dataset for marine species distribution modelling." Global Ecology and Biogeography 21, no. 2 (March 24, 2011): 272–81. http://dx.doi.org/10.1111/j.1466-8238.2011.00656.x.

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Kumar, Y. Ravi. "Modelling and simulation of bio-medical components by selective laser sintering." International Journal of Rapid Manufacturing 2, no. 4 (2011): 234. http://dx.doi.org/10.1504/ijrapidm.2011.044701.

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Halbouni, A. Al, A. Giese, M. Flamme, and K. Goerner. "Applied modelling for bio and lean gas fired micro gas turbines." Progress in Computational Fluid Dynamics, An International Journal 6, no. 4/5 (2006): 235. http://dx.doi.org/10.1504/pcfd.2006.010032.

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Plou, J., P. Durán, J. Herguido, and J. A. Peña. "Hydrogen from bio-fuels by “steam-iron” process: Modelling and kinetics." International Journal of Hydrogen Energy 41, no. 42 (November 2016): 19349–56. http://dx.doi.org/10.1016/j.ijhydene.2016.05.127.

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