An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.     

Optimization of Steam Reforming of Methane in a Hydrogen-Filtering Membrane Module with a Nickel Catalyst and a Palladium-Alloy Foil

Theoretical Foundations of Chemical Engineering - A model is proposed for steam reforming of methane in a catalytic reactor, the working section of which includes two cylindrical chambers separated...     

Flame Retardant Strategies and the Physical Barrier Effect of Nanoparticles to Improve the Thermal Performance of a Polymer

Theoretical Foundations of Chemical Engineering - An analysis of various types of flame retardants in polymer nanocomposites is presented. The mechanisms of action of fire retardants and their...     

Extrinsic parameter's adjustment and potential implications in Plasmodium falciparum malaria diagnosis

Malaria is a major public health concern, affecting over 3.2 billion people in 91 countries. The advent of digital microscopy and Machine learning with the aim of automating Plasmodium falciparum diagnosis extensively depends on the extracted image features. The color of the cells, plasma, and stained artifacts influence the topological, geometrical, and statistical parameters being used to extract image features. During microscopic image acquisition, custom adjustments to the condenser and color temperature controls often have an influence on the extracted statistical features. But, our human visual system sub-consciously adjusts the color and retains the originality in a different lighting environment. Despite the use of appropriate image preprocessing, findings from the literature indicate that statistical feature variations exist, allowing the risk of P. falciparum misinterpretation. In order to eliminate this pervasive variation, the current work focuses on preprocessing the extracted statistical features rather than the prepossessing of the source image. It begins with the augmentation of series images for a microscopic field by inducing illumination variations during the microscopic image acquisition stage. A set of such image series is analyzed using a Nonlinear Regression Model to generalize the relationship between microscopic images acquired with variable ambient brightness and a specific feature. The projection point of the centroid feature onto the brightness parameter is identified in the model and it is denoted as the optimum brightness factor (OBF). Using the model, the feature correction factor (CF) is calculated from the rate of change of feature values over the interval OBF, and the brightness of the test image is processed. The present work has investigated OBF for selected image textural features, namely Contrast, Homogeneity, Entropy, Energy, and Correlation individually from its co-occurrence matrices. For performance analysis, the best state-of-the-art method uses selected texture as a subset feature to evaluate the effectiveness of P. falciparum malaria classification. Then, the impact of proposed feature processing is evaluated on 274 blood smear images with and without Feature Correction (FC). As a result, the “p” value is less than .05, which leads to the result that it is highly significant and the classification accuracy and F-score of P. falciparum malaria are increased.     

Changing the Properties of Coal Pitch by Means of Additives

The influence of various additives—including nanoparticles—on coal pitch is investigated, with a view to improving its properties. Surfactants facilitate the formation of coal-pitch products but have little effect on their properties. Materials that react with the pitch components may increase the yield and microstructure of pitch coke. Nanoparticles increase the yield of pitch coke and its aggregate strength. Additives are classified in terms of their effects on the pitch.     

Diffusional Boriding of Subeutectoidal Tool Steels: Technology and Outcome

Structural, subeutectoidal structural, and tool steels are studied. Their boriding is considered. Equipment for electrolytic boriding and a modernized high-temperature casting crucible are presented. The conditions of electrolytic boriding are established. Shortcomings of electrolytic boriding are noted.     

Estimation of Limit Energy Characteristics of Volumetric Pneumatic Motors Taking into Account the Process Dynamics in Working Chambers

A methodology for estimation of the limit energy characteristics of volumetric pneumatic motors based on the Parameter Space Investigation method and a generalized mathematical model in dimensionless (normalized) form taking into account the dynamics of working processes is proposed. A calculated example is presented. The methodology is applicable for determination of the limit energy characteristics of newly created design solutions, of prospects to improve the known designs of pneumatic motors, of evaluation of energy capacity of several pneumatic motors supplied from a single source of compressed air, and of the initial data preparation for parametric synthesis of rotational pneumatic drives for two or more robots taking into account their interaction.