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• Single/interacting drop drying patterns have been studied with gelatin and sodium sulfate. • Crystal growth depends on drop drying mechanism for single/interacting cases. • Particle size separation could be modified by the presence of another drop. • Regular crystal growth could be characterized by fractals and first/second order statistics. • Hypothesis testing shows the most significant FESEM features for these patterns. A simple colloidal drop generally forms ring like patterns after drying. The deposition morphology of the dried drop changes significantly when such a drop dries in the vicinity of another similar drop. Here we present an observational study and statistical analysis of the patterns formed inside an isolated as well as interacting drops of gelatin containing sodium sulfate (Na 2 SO 4). In all the cases, multiple concentric regions of solute particles combined with the polymer gel appear as the drops dry up. Needle crystals of sulfur and coacervates of salt and gelatin are visible in some regions. The outer region becomes non-uniform, so does the size distribution of the needle crystals and coacervates. The non-uniformity increases with proximity of the drops. Here we propose a novel mechanism of growing patterns inside the single drop during drying and correlate that with the results obtained for interacting drops. This study and the proposed mechanism provide insights into the future studies of drying drops under different physical conditions. Further we explore the statistical characteristics of the single and interacting drops using the field emission scanning electron microscopy (FESEM) images. Next, we report fractal and image texture analyses along with object shape statistics of the drop FESEM images, under various experimental conditions. Several statistical hypothesis tests have been carried out to identify the most significant features. [ABSTRACT FROM AUTHOR]

To investigate whether the FD of non-small cell lung cancer (NSCLC) on CT predicts tumor stage and uptake on 18F-fluorodeoxyglucose positron emission tomography. The FD within a tumor region was determined using a box counting algorithm and compared to the lymph node involvement (NI) and metastatic involvement (MI) and overall stage as determined from PET. A Mann-Whitney U test was applied to the extracted FD features for the NI and the MI. The two tests showed good significance with p <.05 (p NI = 0.0139, p MI = 0.0194). Also after performing fractal analysis to all cases, it was found that for those who had a CT of stage I or II had a higher likelihood of the NI and/or MI stage being upstaged by PET, Odds Ratio 5.38 (95% CI 0.99–29.3). For those who are CT stage III or IV had an increased likelihood of the NI and/or MI stage being down staged by PET, Odds Ratio: 7.33 (95% CI 0.48–111.2). Initial results of this study indicate higher FD in CT images of NSCLC is associated with advanced stage and greater FDG uptake on PET. Measurements of tumor fractal analysis on conventional non-contrast CT examinations could potentially be used as a prognostic marker and/or to select patients for PET. Unlabelled Image • Fractal analysis can quantify complexity within image texture. • Conventional non-contrast enhanced CT scans are employed. • Fractal dimension (FD) estimated within a tumor region using box counting algorithm • FD values correlate with PET lymph node, metastasis and overall tumor stage. • Fractal analysis could potentially be used as a prognostic marker and/or to select patients for PET. [ABSTRACT FROM AUTHOR]

Atomic force microscopy (AFM) was used to evaluate the mechanical properties of apple tissue ( Malus domestica var. Golden Delicious) and isolated cells. Young's modulus (E) obtained for the tissue was 0.86 ± 0.81 MPa, while for isolated cells an average value of 0.63 ± 0.42 MPa was found. The fractal dimension of the distribution of E (FD E ) was estimated to be 1.81 for tissue and 2.47 for isolated cells, which indicates more anisotropic structures in single cell topography in comparison with the tissue. Finally, an image texture analysis was performed and different values were obtained; for roughness Ra = 49.70 ± 23 and 18.00 ± 3, entropy Ent = 5.26 ± 0.66 and 5.70 ± 0.23 and for the fractal dimension of the texture image FD T = 2.55 ± 0.02 and 2.62 ± 0.03, for tissue and isolated cells respectively. Industrial relevance AFM is rarely used to evaluate the structural and mechanical properties of food materials. AFM studies could provide insight on food properties. For example, the nanoindentation of cells by AFM could be used to follow-up changes to the mechanical properties that occur during the processing and storage of fruits with industrial relevance such as apple. Study of the nanostructure and nanomechanical properties of vegetable cells could lead to a more in-depth understanding of the relationship structure–functionality in foodstuffs. This could be applied to address several issues, such as extending the storage life of climacteric fruits, verifying the structural modifications of the tissues when they are chemically treated and having a better control of mechanical and structural properties. Currently, fractal and image analysis is gaining attention in the food science industry. Their application allows one to obtain quantitative information from nanoindentation data and AFM images which can be related to structural modifications which occur during ripening and processing of climacteric fruits. This methodology could be extended to other food materials. [ABSTRACT FROM AUTHOR]

Remote sensing of urban heat islands (UHIs) has traditionally used the Normalized Difference Vegetation Index (NDVI) as the indicator of vegetation abundance to estimate the land surface temperature (LST)–vegetation relationship. This study investigates the applicability of vegetation fraction derived from a spectral mixture model as an alternative indicator of vegetation abundance. This is based on examination of a Landsat Enhanced Thematic Mapper Plus (ETM+) image of Indianapolis City, IN, USA, acquired on June 22, 2002. The transformed ETM+ image was unmixed into three fraction images (green vegetation, dry soil, and shade) with a constrained least-square solution. These fraction images were then used for land cover classification based on a hybrid classification procedure that combined maximum likelihood and decision tree algorithms. Results demonstrate that LST possessed a slightly stronger negative correlation with the unmixed vegetation fraction than with NDVI for all land cover types across the spatial resolution (30 to 960 m). Correlations reached their strongest at the 120-m resolution, which is believed to be the operational scale of LST, NDVI, and vegetation fraction images. Fractal analysis of image texture shows that the complexity of these images increased initially with pixel aggregation and peaked around 120 m, but decreased with further aggregation. The spatial variability of texture in LST was positively correlated with those in NDVI and in vegetation fraction. The interplay between thermal and vegetation dynamics in the context of different land cover types leads to the variations in spectral radiance and texture in LST. These variations are also present in the other imagery, and are responsible for the spatial patterns of urban heat islands. It is suggested that the areal measure of vegetation abundance by unmixed vegetation fraction has a more direct correspondence with the radiative, thermal, and moisture properties of the Earth''s surface that determine LST. [Copyright &y& Elsevier]