Fractal Dimension Coefficient Research Articles

Antifungal Activity of ZnO Nanoparticles Synthesized from Eichhornia crassipes Extract for Construction Applications.

Fungal growth on construction materials in tropical climates can degrade aesthetics and manifestations on modern and historical sick buildings, affecting the health of their inhabitants. This study synthesized ZnO nanoparticles with enhanced antifungal properties using a precipitation method. Different concentrations (25%, 50%, and 100%) of Eichhornia crassipes aqueous extract were used with Zn(NO3)2·6H2O as the precursor to evaluate their spectroscopic, morphological, textural, and antifungal properties. X-ray diffraction confirmed the hexagonal wurtzite phase of ZnO with crystallite sizes up to 20 nm. Fourier-transform infrared spectroscopy identified absorption bands at 426, 503, and 567 cm-1 for ZnO-100, ZnO-50, and ZnO-25, respectively. Nitrogen physisorption indicated a type II isotherm with macropores and a fractal dimension coefficient near 2 across all concentrations. Polydispersity index analysis showed that ZnO-50 had a higher PDI, indicating a broader size distribution, while ZnO-25 and ZnO-100 exhibited lower PDI values, reflecting uniform and monodisperse particle sizes. FESEM observations revealed semi-spherical ZnO morphologies prone to agglomeration, particularly in ZnO-25. Antifungal tests highlighted ZnO-25 as the most effective, especially against Phoma sp. with an MFC/MIC ratio of 78 µg/mL. Poisoned plate assays demonstrated over 50% inhibition at 312 µg/mL for all tested fungi, outperforming commercial antifungals. The results indicate that ZnO NPs synthesized using E. crassipes extract effectively inhibit fungal growth on construction materials. This procedure offers a practical approach to improving the durability of building aesthetics and may contribute to reducing the health risks associated with exposure to fungal compounds.

On the growth and dissemination laws in a mathematical model of metastatic growth

Metastasis represents one of the main clinical challenge in cancer treatment since it is associated with the majority of deaths. Recent technological advances allow quantification of the dynamics of the process by means of noninvasive techniques such as longitudinal tracking of bioluminescent cells. The metastatic process was simplified here into two essential components – dissemination and colonization – which were mathematically formalized in terms of simple quantitative laws. The resulting mathematical model was confronted to in vivo experimental data of spontaneous metastasis after primary tumor resection. We discuss how much information can be inferred from confrontation of theories to the data with emphasis on identifiability issues. It is shown that two mutually exclusive assumptions for the secondary growth law (namely same or different from the primary tumor growth law) could fit equally well the data. Similarly, the fractal dimension coefficient in the dissemination law could not be uniquely determined from data on total metastatic burden only. Together, these results delimitate the range of information that can be recovered from fitting data of metastatic growth to already simplified mathematical models.

A Method for Post-hazard Assessment Through Topography Analysis using Regional Segmentation for Multi-temporal Satellite Imagery: A Case Study of 2011 Tohuku Earthquake Region

Non-rigid image registration in ext racting deformation map for two satellite images of the same region before and after earthquake occurrence based on measure of intensity dissimilarity C(Ir, T(If)) can play a significant ro le in post hazard analysis. In this paper, we have proposed a novel image transformation and regional segmentation of the same visualized region by assigning displacement label to change in intensity using Advanced Synthetic Aperture Radar (ASAR) satellite images. We used graph cut based non rig id reg istraion with a data term and a s moothness term for assigning markovianity between neighboring pixels. Displacement labels has been directly assigned fro m this data term for small intensity difference. Secondly, our data term imposes stricter penalty for intensity mis matches and hence yields higher registration accuracy. Based on the satellite image analysis through image segmentation, it is found that the area of .997 km 2 for the Honshu region was a maximu m damage zone localized in the coastal belt of NE Japan fore-arc region. A further objective has been to correlate fractal analysis of seismic clustering behavior with image segmentation suggesting that increase in the fractal dimension coefficient is associated with the deviation of the pixel values that gives a met ric of the devastation of the de-clustered region.