Accounting for randomness in measurement and sampling in studying cancer cell population dynamics

Knowing the expected temporal evolution of the proportion of different cell types in sample tissues gives an indication about the progression of the disease and its possible response to drugs. Such systems have been modelled using Markov processes. We here consider an experimentally realistic scenario in which transition probabilities are estimated from noisy cell population size measurements. Using aggregated data of FACS measurements, we develop MMSE and ML estimators and formulate two problems to find the minimum number of required samples and measurements to guarantee the accuracy of predicted population sizes. Our numerical results show that the convergence mechanism of transition probabilities and steady states differ widely from the real values if one uses the standard deterministic approach for noisy measurements. This provides support for our argument that for the analysis of FACS data one should consider the observed state as a random variable. The second problem we address is about the consequences of estimating the probability of a cell being in a particular state from measurements of small population of cells. We show how the uncertainty arising from small sample sizes can be captured by a distribution for the state probability.Inspec keywords: cancer, tumours, cellular biophysics, biomedical measurement, Gaussian distribution, maximum likelihood estimation, mean square error methods, hidden Markov models, fluorescence, random processes, convergence of numerical methodsOther keywords: cancer cell population dynamics, malignant tumours, tissue samples, normal tissue cells, disease, drugs, Markov process, cell population size measurement, hidden Markov model, noisy measurement, state transition probability, fluorescence‐activated cell sorting measurement, minimum mean square error estimator, maximum likelihood estimator, transition probability matrix, noise distributions, Gaussian distributions, MMSE, convergence mechanism, standard deterministic approach, stochastic phenomena, random variable     

A knowledge-based semantic approach for image collection summarization

Multimedia Tools and Applications - With the advent of digital cameras, the number of digital images is on the increase. As a result, image collection summarization systems are proposed to provide...     

A framework for multi-objective optimisation of 3D part-build orientation with a desired angular resolution in additive manufacturing processes

In additive manufacturing processes, the part build orientation (PBO) is one of the most important factors that can affect the characteristics of the quality product such as the amount of support structure and the surface roughness. In most previous methods, the optimal PBO cannot be determined with high precision and accuracy in 3D space. In this paper, to find the precise and accurate optimal PBO with a desired angular accuracy, a new Taguchi-based method, called the Zooming-Taguchi method, is proposed. The proposed simulation-based method can precisely find the optimal PBO in absence of the noise effects. In order to find the optimal PBO with the desired angular resolution, the zooming procedure is iteratively carried out on factor levels through a clustering strategy. Finally, to validate the proposed method, two case studies are considered and the obtained results are compared with conventional methods in the literature and the experimental results.     

A Comparison of MVDR and LCMV Beamformers’ Floating Point Implementations on FPGAs

Adaptive beamformers are designed with the aim of detection of noise and intentional destructive interference and then removing them from the desired signal. This is done by placing high attenuation in the direction of the destructive signal in the radiation pattern of antenna arrays without attenuating the signal from a known direction. Minimum variance distortionless response and linearly constrained minimum variance are among such algorithms in mobile communications. A short explanation of the theory and weights formulae of these beamformers will be given. Two designs for weights calculations in Simulink with the added library of DSP-Builder tool from Altera will be presented. Quadrature Rectangular decomposition with Modified Gram-Schmidt algorithm is used instead of the direct matrix inversion. All calculations are done in single floating point mode for the required high accuracy. Modelsim has been used for hardware simulation and measuring the required clock cycles. The target FPGA is Aria10 from Altera which has floating point DSP blocks for high-performance computations. Hardware resources usage, power consumption, maximum clock frequency and update rate for different matrix sizes of these two beamformers are compared and discussed. The results are also compared with some other relevant reported works.     

Reservoir Routing using Steady and Unsteady Flow through Rockfill Dams

In this paper a two-dimensional (2D) model for flow through rockfill dams is presented and its results have been compared to 1D model. The model is based on the 2D continuity equation. In the model, an exponential relationship between Reynolds number (R) and Darcy-Weisbach coefficient (f) is suggested and combined with the continuity equation. Coefficients of this relationship are estimated by using real data and a nonlinear optimization technique. Introducing inflow hydrograph to the reservoir and rockfill characteristics as input data and utilizing the above model the outflow hydrograph can be determined. The model has been calibrated and verified using real data. The results of the numerical solution have been shown to be more reliable than the 1D model. To demonstrate the model sensitivity to different parameters, a parametric sensitivity analysis has been conducted. Finally, a comparison between the steady- and unsteady-state results is introduced.     

Investigation into the fouling mechanism in a RO hollow fine-fibre module

As a service to readers who understand German, French or Spanish better than English, the abstract for the research article in this issue follow in these languages.     

Fouling of microfiltration membranes by biopolymers

Suppression of fouling due to biopolymers of relevance to the brewing industry has been investigated. The effects of three model biopolymers: casein (protein), catechin (polyphenol), and dextran (polysaccharide) on fouling of asymmetric 0.65 μm polyethersulfone membranes during direct-flow filtration have been studied. While dextran is successful in disrupting interactions between casein and catechin, the associated reduction in aggregate size does not always result in reduced fouling. Solution conditions such as pH and ionic strength modulate the tendency of the aggregates to adsorb onto the membrane surface. Thus, optimizing solution conditions to suppress adsorption of aggregates is essential for increasing the membrane filtration capacity.     

Determination of Lead,Cadmium, Copper,and Zinc Content in Commercial Iranian Vinegars Using Stripping Chronopotentiometry

The rapid stripping chronopotentiometry (SCP) method was used to determine copper, lead, cadmium, and zinc in different kinds of vinegars (date, white grape, red grape, and apple) produced in Iran. The results of SCP were compared with graphite furnace atomic absorption spectrometry (GFAAS) as a reference method. There were no significant differences (p > 0.5) between the two methods. The range of concentration (ng/ml) of the analytes for heavy metals in different kinds of vinegars was as follows: copper (12.79–1,129), lead (3.32–253), cadmium (non-detectable concentration to 78), and zinc (26.12–3,725). The results demonstrated that it is possible to accurately determine the copper, lead, cadmium, and zinc content by direct analysis of vinegar samples using SCP method. The metal concentrations in all samples were lower than the maximum allowable limits legislated by the Institute of Standards and Industrial Research of Iran.     

Modeling Thermal Conductivity of Iranian Flat Bread Using Artificial Neural Networks

The objective of this work was to develop Artificial Neural Network (ANN) based thermal conductivity (K) prediction model for Iranian flat breads. Experimental data needed for ANN models were obtained from a pilot-scale set-up. Breads were made from three different cultivars of wheat and were baked in an eclectic oven at three different baking temperatures (232°C, 249°C and 260°C). A data set of 205 conditions was used for developing ANN and empirical models. To model K using ANN, 16 different MLP (multilayer perceptron) configurations ranging from one to two hidden layers of neurons were investigated and their prediction performances were evaluated. The (4-3-5-1)-MLP network, that is a network having two hidden layers, with three neurons in its first hidden layer and five neurons in its second hidden layer, had the best results in predicting the thermal conductivity of flat bread. For this network, R², MRE, MAE and SE were 0.988, 0.6323, 1.66×10^{? 3}, and 8.56×10^?4, respectively. Overall, ANN models (with R² ≥ 0.95) performed superior than the empirical model (with R² = 0. 870).     

Long-Term Storage Effects on the Physical Properties of the Potato

Determination of physical properties of agricultural products, such as the potato, and their variations during long-term storage, is an important feature in achieving high product quality and consumer acceptance. Physical properties of potatoes (Agria, Satina, and Caesar cultivars), including surface area, volume, moisture content, weight, and three main diameters of tuber, were measured and then other properties, such as sphericity, roundness, geometric mean diameter, volume mean diameter, aspect ratio, effective diameter, and real density during storage time, were calculated. The measurements were done every 15 days for a period of 22 weeks and analyzed based on a completely randomized block design in ten replications. Significant differences were observed among three potato cultivars according to major diameter, shape characteristics, mass, volume, and surface area of tubers. In this relation, Satina was larger in size compared to the two other cultivars. However, the Agria cultivar was closer to a sphere in shape. Also, it was found that the surface area of each potato could be estimated based on its mass and volume by a power law equation with a high coefficient of determination. According to the results, real density of tubers increased as a function of storage time based on a polynomial equation with R² = 0.99. During storage time, moisture content of tubers decreased according to a linear model and was probably the major rationale for decrease in tuber size. Density, size, and moisture content are the major physical characteristics of potato tubers, which change dramatically during long-term storage. Considerable differences in physical properties of different cultivars persuade researchers to carry out further studies on other popular potato cultivars.