Mathematical modelling and numerical simulations of actin dynamics in the eukaryotic cell

The aim of this article is to study cell deformation and cell movement by considering both the mechanical and biochemical properties of the cortical network of actin filaments and its concentration. Actin is a polymer that can exist either in fil- amentous form (F-actin) or in monometric form (G-actin) (Chen et al. 2000) and the filamentous form is arranged in a paired helix of two protofilaments (Ananthakrish- nan et al. 2006). By assuming that cell deformations are a result of the cortical actin dynamics in the cell cytoskeleton, we consider a continuum mathematical model that couples the mechanics of the network of actin filaments with its bio-chemical dy- namics. Numerical treatment of the model is carried out using the moving grid finite element method (Madzvamuse et al. 2003). Furthermore, by assuming slow deforma- tions of the cell, we use linear stability theory to validate the numerical simulation results close to bifurcation points. Far from bifurcation points, we show that the math- ematical model is able to describe the complex cell deformations typically observed in experimental results. Our numerical results illustrate cell expansion, cell contrac- tion, cell translation and cell relocation as well as cell protrusions. In all these results, the contractile tonicity formed by the association of actin filaments to the myosin II motor proteins is identified as a key bifurcation parameter

A numerical approach to studying cell dynamics

The focus of this thesis is to propose and implement a highly efficient numerical method to study cell dynamics. Three key phases are covered: mathematical modelling, linear stability analytical theory and numerical simulations using the moving grid finite element method. This aim is to study cell deformation and cell movement by considering both the mechanical and biochemical properties of the cortical network of actin filaments and its concentration. These deformations are assumed to be a result of the cortical actin dynamics through its interaction with a protein known as myosin II in the cell cytoskeleton. The mathematical model that we consider is a continuum model that couples the mechanics of the network of actin filaments with its bio-chemical dynamics. Numerical treatment of the model is carried out using the moving grid finite element method. By assuming slow deformations of the cell boundary, we verify the numerical simulation results using linear stability theory close to bifurcation points. Far from bifurcation points, we show that the model is able to describe the deformation of cells as a function of the contractile tonicity of the complex formed by the association of actin filaments with the myosin II motor proteins. Our results show complex cell deformations and cell movements such as cell expansion, contraction, translation and protrusions in accordance with experimental observations. The migratory behaviour of cells plays a crucial role in many biological events such as immune response, wound healing, development of tissues, embryogenesis, inflammation and the formation of tumours

A Framework for Intelligent Inventory Prediction in Small and Medium- Scale Enterprise

The aim of this research is to apply an intelligent technique to predict optimal inventory quantity in small and medium-scale enterprise. This is in view of the fact that the conventional models such as the EOQ model use only deterministic while some decision variables are non- deterministic in nature. Forecasted average demand of items for ten months in a small-scale retail outlet was collected and trained using an Artificial Neural Networks (ANN) of 5 neurons in the input layer with eight neurons in the first hidden layer and four neurons in the second hidden layer. Two feed-forward training algorithms of quasi-newton and quick propagation were employed in the training with the results of fuzzy logic technology found in the literature as the target output. Results obtained show that the quasi-newton algorithm covaries stronger with the fuzzy logic results than the quick propagation results. The objective and subjective feelings of the inventory manager were also captured to optimise the results of the training. The study is at a framework stage and will proceed to implementation level when more datasets are collected. Data collection in a small-scale outlet is a daunting task as record keeping is hardly done. The inclusion of non-deterministic circumstances such as emotional and objective feelings of the inventory manager to predict inventory is novel considering the fact that studies in the available intelligent inventory prediction have not employed such variables in their predictions. Keywords: Artificial Neural networks, Fuzzy logic, Quasi newton, Quick propagation, EOQ, Inventory, Forecast. DOI: 10.7176/EJBM/13-2-03 Publication date: January 31st 202

A framework for intelligent inventory prediction in small and medium- scale enterprise.

The aim of this research is to apply an intelligent technique to predict optimal inventory quantity in small and medium-scale enterprise. This is in view of the fact that the conventional models such as the EOQ model use only deterministic while some decision variables are non-deterministic in nature. Forecasted average demand of items for ten months in a small-scale retail outlet was collected and trained using an Artificial Neural Networks (ANN) of 5 neurons in the input layer with eight neurons in the first hidden layer and four neurons in the second hidden layer. Two feed-forward training algorithms of quasi-newton and quick propagation were employed in the training with the results of fuzzy logic technology found in the literature as the target output. Results obtained show that the quasi-newton algorithm covaries stronger with the fuzzy logic results than the quick propagation results. The objective and subjective feelings of the inventory manager were also captured to optimise the results of the training. The study is at a framework stage and will proceed to implementation level when more datasets are collected. Data collection in a small-scale outlet is a daunting task as record keeping is hardly done. The inclusion of non-deterministic circumstances such as emotional and objective feelings of the inventory manager to predict inventory is novel considering the fact that studies in the available intelligent inventory prediction have not employed such variables in their predictions

Synthesis, Characterization And Activity Of Titanium Dioxide Based (Ca, Ce, W)-Ti02 Photocatalysts For Degradation Of Dye And Pesticide

Pengindustrian global berhadapan dengan berbagai cabaran. Pelepasan yang tidak diingini melibatkan produk dan bahan cemar yang karsinogen dan toksik ke dalam persekitaran oleh industri tekstil Global industrialization is not without its attendant challenges. The release of unwanted by-products and pollutants which are carcinogenic and toxic into the environment by textile

Synthesis, characterization and activity of titanium dioxide based- (Ca, Ce, W)-TiO2 photocatalysts for degradation of dye and pesticide.

Pengindustrian global berhadapan dengan berbagai cabaran. Pelepasan yang tidak diingini melibatkan produk dan bahan cemar yang karsinogen dan toksik ke dalam persekitaran oleh industri tekstil, kimia dan pemprosesan adalah berkadar langsung kepada pertumbuhan industri. Global industrialization is not without its attendant challenges. The release of unwanted by-products and pollutants which are carcinogenic and toxic into the environment by textiles, chemicals and processing industries is directly proportional to industrial growth

Waste Frying Oil as a Feedstock for Biodiesel Production

This study was initiated to blend the biodiesel produced from waste frying oil (WFO) with petroleum diesel in three different proportions (B20, B50 and B80), and the dual fuels were tested on compression ignition engine to evaluate their emission characteristics. The biodiesel produced from WFO was achieved via heterogeneous catalyzed transesterification using anthill-eggshell-Ni-Co mixed oxide composite catalyst at reaction temperature of 70°C, reaction time of 2 h, catalyst loading of 3 wt% and methanol to oil molar ratio of 12:1. Various analyses carried out on the prepared WFO-based biodiesel confirmed that it is of good quality and also meet the ASTM standard. The blended fuel containing 20% by volume biodiesel content (B20) emitted 1050 and 14,000 ppm of CO and CO2, respectively, which were lower than those emitted by B0, B50 and B80. It can be concluded that blending the diesel with appropriate volume of biodiesel not only improves its quality but also lowers greenhouse gases emission

Evaluation of Yield Productivity and Economic Returns of Some Yam (Dioscorea esculenta Poir) Genotypes Grown in a Kaolinitc Ultisol

A two-year (2008 and 2009) study was carried out at the University of Uyo Teaching and Research Farm, Use-Offot to evaluate yield productivity of eight yam genotypes (TDr 200/3/7A, M2/75/3, M2/25/1, M2/50/5x, 99/AMO/053, 99/AMO/094, 95/18894, and local -Eteme).and  their economic returns to management. Randomized Complete Block Design with three replicates was used. Results of the study indicated significant differences in all the yield and yield components of the different yam genotypes considered in both years., Cost of production in 2009 was 2% above the cost of production in 2008 due to increase in cost of land preparation. The cost -benefit ratio of all the genotypes were above 10.00 except in local variety, Eteme with values of 4.9 and 6.3 in  2008 and 2009, respectively. The average cost- benefit ratio of 14.25 recorded in TDr 95/18894 suggesting strongly that the genotype is more adaptable to Uyo, agro- ecology than others. Keywords; yield productivity, economic returns, yam, genotype