Stochastic Model for Tumor Control Probability: Effects of Cell Cycle and (A)symmetric Proliferation

Estimating the required dose in radiotherapy is of crucial importance since the administrated dose should be sufficient to eradicate the tumor and at the same time should inflict minimal damage on normal cells. The probability that a given dose and schedule of ionizing radiation eradicates all the tumor cells in a given tissue is called the tumor control probability (TCP), and is often used to compare various treatment strategies used in radiation therapy. In this paper, we aim to investigate the effects of including cell-cycle phase on the TCP by analyzing a stochastic model of a tumor comprised of actively dividing cells and quiescent cells with different radiation sensitivities. We derive an exact phase-diagram for the steady-state TCP of the model and show that at high, clinically-relevant doses of radiation, the distinction between active and quiescent tumor cells (i.e. accounting for cell-cycle effects) becomes of negligible importance in terms of its effect on the TCP curve. However, for very low doses of radiation, these proportions become significant determinants of the TCP. Moreover, we use a novel numerical approach based on the method of characteristics for partial differential equations, validated by the Gillespie algorithm, to compute the TCP as a function of time. We observe that our results differ from the results in the literature using similar existing models, even though similar parameters values are used, and the reasons for this are discussed.Comment: 12 pages, 5 figure

Phenotypic heterogeneity in modeling cancer evolution

The unwelcome evolution of malignancy during cancer progression emerges through a selection process in a complex heterogeneous population structure. In the present work, we investigate evolutionary dynamics in a phenotypically heterogeneous population of stem cells (SCs) and their associated progenitors. The fate of a malignant mutation is determined not only by overall stem cell and differentiated cell growth rates but also differentiation and dedifferentiation rates. We investigate the effect of such a complex population structure on the evolution of malignant mutations. We derive exact analytic results for the fixation probability of a mutant arising in each of the subpopulations. The analytic results are in almost perfect agreement with the numerical simulations. Moreover, a condition for evolutionary advantage of a mutant cell versus the wild type population is given in the present study. We also show that microenvironment-induced plasticity in invading mutants leads to more aggressive mutants with higher fixation probability. Our model predicts that decreasing polarity between stem and differentiated cells turnover would raise the survivability of non-plastic mutants; while it would suppress the development of malignancy for plastic mutants. We discuss our model in the context of colorectal/intestinal cancer (at the epithelium). This novel mathematical framework can be applied more generally to a variety of problems concerning selection in heterogeneous populations, in other contexts such as population genetics, and ecology.Comment: 28 pages, 7 figures, 2 table

A Markov Model for Dynamic Behavior of Toa-Based Ranging in Indoor Localization

The existence of undetected direct path ( UDP) conditions causes occurrence of unexpected large random ranging errors which pose a serious challenge to precise indoor localization using time of arrival ( ToA). Therefore, analysis of the behavior of the ranging error is essential for the design of precise ToA-based indoor localization systems. In this paper, we propose a novel analytical framework for the analysis of the dynamic spatial variations of ranging error observed by a mobile user based on an application of Markov chain. the model relegates the behavior of ranging error into four main categories associated with four states of the Markov process. the parameters of distributions of ranging error in each Markov state are extracted from empirical data collected from a measurement calibrated ray tracing ( RT) algorithm simulating a typical office environment. the analytical derivation of parameters of the Markov model employs the existing path loss models for the first detected path and total multipath received power in the same office environment. Results of simulated errors from the Markov model and actual errors from empirical data show close agreement

Optimal Seismic Design of Steel Plate Shear Walls Using Metaheuristic Algorithms

In this paper three well-known metaheuristic algorithms comprising of Colliding Bodies Optimization, Enhanced Colliding Bodies Optimization, and Particle Swarm Optimization are employed for size and performance optimization of steel plate shear wall systems. Low seismic and high seismic optimal designs of these systems are performed according to the provisions of AISC 360 and AISC 341. In one part of the low seismic example, a moment frame and Steel Plate Shear Wall (SPW) strength are compared. Performance optimization of the Special Plate Shear Wall (SPSW) for size optimized system is one of the objectives of the high seismic example. Finally, base shear sensitivity analysis on optimal high seismic design of SPSW and size optimization of a 6-story to a 12-story SPSW are performed to have a comprehensive view on the optimal design of steel plate shear walls

The Effect of Audit Quality Adjustment on the Relationship between Earnings Management and Return on Equity in Listed Companies in Tehran Stock Exchange

In developed economies, the audit process is very important measure of capital and political stability. This is despite the fact that in developing countries likes Iran. The audited financial statements of the most important tools for ensuring the transparency of financial information, which is to increase the predictive power of accounting information, such as financial ratios earnings per share is.Therefore, the quality of accounting information quality increases and future returns of the grounding of the information obtained will be closer to reality. The measures related to earnings management may lead to the disclosure of financial information to be false, because it is not provided in accordance with the actual conditions. Audit process as a moderator variable reduction measures related to earnings management. This paper examines the relationship between audit quality and earnings management among firms listed in Tehran Stock Exchange paid.And towards that goal, all of the companies listed in Tehran Stock Exchange in the financial statements (balance sheet, profit and loss account) and provide the required information for the years 2010 to 2014 were studied. In total, 70 companies were selected from different industries. To test the hypothesis of multivariate regression analysis (stepwise) was used for significance using the t and F statistics were performed, as well as camera-Watson test for autocorrelation test model is used. The results suggest that, between stock returns are positive and significant relationship with audit quality management benefit. Keywords: audit quality, return on equity, earnings managemen

A New Nodal Stress Recovery Technique in Finite Element Method Using Colliding Bodies Optimization Algorithm

In Finite Element Method (FEM), the stress components are calculated within the elements firstly, and then these components are recovered to the nodes. For the recovery process, there are several well-known methods in which the increase of their accuracy imposes additional costs into the problem. In this paper, a new nodal stress recovery technique is proposed in which Colliding Bodies Optimization (CBO) Algorithm fits an appropriative function for nodal stress fields. The CBO employs this function to compute the stress components in the nodal coordinates. Therefore, a particular model to stress fields and its components will be available. It can be considered as a connection between analytical approaches and numerical methods, providing benefits of both categories. Finally, the accuracy, efficiency, and applicability of the new technique are investigated employing three diverse examples

Optimization of Slope Critical Surfaces Considering Seepage and Seismic Effects Using Finite Element Method and Five Meta-Heuristic Algorithms

One of the most crucial geotechnical engineering problems is the stability of slopes that are still attracting scientists and engineers. In this study, five recently developed meta-heuristic methods are utilized to determine the Critical Failure Surface (CFS) and its corresponding Factor of Safety (FOS). Through the FOS calculations, the Finite Element Method (FEM) is employed to convert the strong form of the main differential equation to a weak form. Additional to the general loading, seismic forces and seepage effect are considered, as well. Finally, the proposed optimization procedure is applied to numerical benchmark examples, and results are compared with other methods