3D Hair sketching for real-time dynamic & key frame animations

Physically based simulation of human hair is a well studied and well known problem. But the “pure” physically based representation of hair (and other animation elements) is not the only concern of the animators, who want to “control” the creation and animation phases of the content. This paper describes a sketch-based tool, with which a user can both create hair models with different styling parameters and produce animations of these created hair models using physically and key frame-based techniques. The model creation and animation production tasks are all performed with direct manipulation techniques in real-time.     

Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells

The aim of this study is to investigate the effects of non-uniform solar irradiation distribution on energy output of different interconnected configurations in photovoltaic (PV) arrays. In order to find which configuration is less susceptible to mismatch effects, a PV module model is developed. This model can take into consideration the effects of bypass diodes and the variation of the equivalent circuit parameters with respect to operating conditions. The proposed model can provide sufficient degree of precision as well as solar cell-based analysis in analyzing large scale PV arrays without increasing the computational effort. In order to produce more reliable and robust simulations, improved and extended algorithms are presented. Some results are discussed in detail and some recommendations are extracted by testing several shading scenarios.     

CFAR processing with switching exponential smoothers for nonhomogeneous environments

Conventional constant false alarm rate (CFAR) methods use a fixed number of cells to estimate the background variance. For homogeneous environments, it is desirable to increase the number of cells, at the cost of increased computation and memory requirements, in order to improve the estimation performance. For nonhomogeneous environments, it is desirable to use less number of cells in order to reduce the number of false alarms around the clutter edges. In this work, we present a solution with two exponential smoothers (first order IIR filters) having different time-constants to leverage the conflicting requirements of homogeneous and nonhomogeneous environments. The system is designed to use the filter having the large time-constant in homogeneous environments and to promptly switch to the filter having the small time constant once a clutter edge is encountered. The main advantages of proposed Switching IIR CFAR method are computational simplicity, small memory requirement (in comparison to windowing based methods) and its good performance in homogeneous environments (due to the large time-constant smoother) and rapid adaptation to clutter edges (due to the small time-constant smoother).     

Exploring brain connectivity with two-dimensional neural maps

We introduce two-dimensional neural maps for exploring connectivity in the brain. For this, we create standard streamtube models from diffusion-weighted brain imaging data sets along with neural paths hierarchically projected into the plane. These planar neural maps combine desirable properties of low-dimensional representations, such as visual clarity and ease of tract-of-interest selection, with the anatomical familiarity of 3D brain models and planar sectional views. We distribute this type of visualization both in a traditional stand-alone interactive application and as a novel, lightweight web-accessible system. The web interface integrates precomputed neural-path representations into a geographical digital-maps framework with associated labels, metrics, statistics, and linkouts. Anecdotal and quantitative comparisons of the present method with a recently proposed 2D point representation suggest that our representation is more intuitive and easier to use and learn. Similarly, users are faster and more accurate in selecting bundles using the 2D path representation than the 2D point representation. Finally, expert feedback on the web interface suggests that it can be useful for collaboration as well as quick exploration of data.     

Visualizing Extracellular Vesicles and Their Function in 3D Tumor Microenvironment Models

Extracellular vesicles (EVs) are cell-derived nanostructures that mediate intercellular communication by delivering complex signals in normal tissues and cancer. The cellular coordination required for tumor development and maintenance is mediated, in part, through EV transport of molecular cargo to resident and distant cells. Most studies on EV-mediated signaling have been performed in two-dimensional (2D) monolayer cell cultures, largely because of their simplicity and high-throughput screening capacity. Three-dimensional (3D) cell cultures can be used to study cell-to-cell and cell-to-matrix interactions, enabling the study of EV-mediated cellular communication. 3D cultures may best model the role of EVs in formation of the tumor microenvironment (TME) and cancer cell-stromal interactions that sustain tumor growth. In this review, we discuss EV biology in 3D culture correlates of the TME. This includes EV communication between cell types of the TME, differences in EV biogenesis and signaling associated with differing scaffold choices and in scaffold-free 3D cultures and cultivation of the premetastatic niche. An understanding of EV biogenesis and signaling within a 3D TME will improve culture correlates of oncogenesis, enable molecular control of the TME and aid development of drug delivery tools based on EV-mediated signaling.     

Aromatic products of 340 °C supercritical-toluene extraction of two Turkish lignites: an n.m.r. study

Fractions of Elbistan and Seyitomer (Turkish) lignites, extracted with supercritical toluene at 340 °C and 8 MPa, have been separated by solvent extraction and silica-gel chromatography. Analyses by n.m.r. and i.r. spectroscopies and other methods have been combined in structural-analysis schemes to yield information about the average molecule in aromatic extracts. Carbon aromaticities, f_a, derived from 22.63 MHz ¹H-decoupled pulse Fourier-transform (PFT) ¹³C-n.m.r. are more widely spread for Elbistan (0.34–0.56) than for Seyitomer (0.40–0.43), and are lower than for supercritical-gas (SCG) products from bituminous coals. ¹³C-n.m.r. also reveals the presence of aromatic ether-O in polar fractions. Narrow aromatic signals in 100 MHz ¹H-n.m.r. spectra suggest the presence of single-aromatic-ring average structures. In the hexane-soluble aromatics, 27% (Elbistan) and 29% (Seyitomer) of the available sites are substituted by alkyI groups, some of which are at least eight carbon atoms long; the hexane-soluble polar and asphaltene/asphaltol fractions contain fewer such groups.     

An investigation of some Schiff bases as corrosion inhibitors for austenitic chromium–nickel steel in H2SO4

The corrosion inhibition of austenitic chromium–nickel steel by two Schiff bases, N-(1-toluidine)salicylaldimine and N-(2-hydroxyphenyl)salicylaldimine, was investigated in sulphuric acid medium. The effect of concentration and temperature on inhibition properties was determined. It was found that when the concentrations of inhibitor were increased the inhibition efficiencies () and surface coverage () increased. Some thermodynamic parameters such as free energy of adsorption, G _ads, and enthalpy, H, were determined for the Schiff bases. Experimental results agree with the Temkin isotherm for N-(1-toluidine)salicylaldimine, but the Langmuir isotherm is more appropriate for N-(2-hydroxyphenyl)salicylaldimine.