Discoloration process modeling by neural network

The photo-oxidation of acid orange 52 dye was performed in the presence of H₂O₂, utilizing UV light, aiming the discoloration process modeling and the process variable influence characterization. The discoloration process was modeled by the use of feedforward neural network. Each sample was characterized by five independent variables (dye concentration, pH, hydrogen peroxide volume, temperature and time of operation) and a dependent variable (absorbance). The neural model has also provided, through Garson Partition coefficients and the Pertubation method, the independent variable influence order determination. The results indicated that the time of operation was the predominant variable and reaction mean temperature was the lesser influent variable. The neural model obtained presented coefficients of correlation on the order 0.98, for sets of trainability, validation and testing, indicating the power of prediction of the model and its character of generalization.     

Narrow resonances and ripple fluctuations in light scattering by a spheroid

We develop a semiclassical theory to explain the rapid ripple fluctuations in the extinction efficiency of light scattering by a transparent prolate spheroid. The theory is based on uniform asymptotic expansion of spheroidal radial functions. We have calculated the extinction efficiency for normal and oblique incidence. Our results suggest that the excitation of resonant electromagnetic modes inside a spheroidal particle is an important factor in the ripple structure. To verify this assumption and based on a Breit-Wigner formula, we develop a method to fit the peaks that appear in the spheroid's extinction cross section when some scattering parameters vary. In other words, our calculations suggest that narrow resonances are related to ripple fluctuations, whereas broad resonances contribute to extinction cross-sectional background.     

Nanorobotics control design: a collective behavior approach for medicine

The authors present a new approach using genetic algorithms, neural networks, and nanorobotics concepts applied to the problem of control design for nanoassembly automation and its application in medicine. As a practical approach to validate the proposed design, we have elaborated and simulated a virtual environment focused on control automation for nanorobotics teams that exhibit collective behavior. This collective behavior is a suitable way to perform a large range of tasks and positional assembly manipulation in a complex three-dimensional workspace. We emphasize the application of such techniques as a feasible approach for the investigation of nanorobotics system design in nanomedicine. Theoretical and practical analyses of control modeling is one important aspect that will enable rapid development in the emerging field of nanotechnology.     

Catheter ablation in patients with refractory cardiac arrhythmias with radiofrequency techniques

The author suggests a working classification of dermopertorators from analysis of his own designs and devices described in the literature for forming netlike skin grafts in the treatment of patients with large tissue defects. It is shown that the well-known dermoperforators require essential modernization. The most promising model is a device with plane knives whose simple technology allows their production to be organized in Soviet industry.     

Effect of nanovesicle-encapsulated nisin on growth of Listeria monocytogenes in milk

Commercial nisin was encapsulated in nanovesicles (mean diameter 140 nm) prepared from partially purified soy lecithin. Nisin-loaded liposomes and unencapsulated (free) nisin were initially tested in BHI medium and skim milk inoculated with Listeria monocytogenes and incubated for 48 h at 30 °C. At such abuse temperature conditions, free nisin showed better inhibitory than the liposomal counterparts. Subsequently, the effect of encapsulated or free nisin was evaluated in combination with refrigeration (7 ± 1 °C) in both whole (3.25% fat) and skim (0% fat) milk for up to 14 day. A decrease of 3–4 log cycles in L. monocytogenes counts was observed for free and encapsulated nisin at 0.5 mg/ml concentration. Liposome encapsulation of antimicrobial peptides may be important to overcome stability issues and interaction with food components. The utilization of nanovesicle-encapsulated nisin in combination with low temperatures appeared to be effective to control L. monocytogenes in milk, emphasizing the importance of hurdle technology to assure food safety.     

The Mandibular Gland Secretions of the Leaf-Cutting Ants Atta sexdens sexdens and Atta opaciceps Exhibit Intercaste and Intercolony Variations

The mandibular gland secretions of worker castes from wild colonies of the leaf-cutting ants Atta sexdens sexdens and Atta opaciceps were analyzed quantitatively by gas chromatography–mass spectrometry. The secretions comprised a complex mixture of volatile, mainly oxygenated compounds, and their profiles exhibited considerable qualitative and quantitative variations among species and castes. The known alarm pheromone 4-methyl-3-heptanone was common to both species. The elevated relative proportions of this ketone found in the secretions of gardeners and generalists suggest that such castes are primarily responsible for the production and release of the alarm pheromone. Quantitative variations (but no qualitative differences) in the profiles of secretions of soldiers from different colonies of A. sexdens sexdens were detected, supporting the view that intraspecific colony recognition is mediated through mandibular gland secretions. Subsequent laboratory assays showed that, among the compounds identified by GC–MS, 4-methyl-3-heptanone elicited a strong alarm response in workers of A. sexdens sexdens and A. opaciceps.     

Fate of beta blockers and psycho-active drugs in conventional wastewater treatment

The removal of beta blockers and psycho-active drugs was investigated in a representative conventional German WWTP by long-term measurement campaigns along different biological treatment processes. The activated sludge treatment with an elevated SRT of 18 d was the only process which led to a significant removal of certain beta blockers and psycho-active drugs. The removal efficiency was below 60% for all compounds except for the natural opium alkaloids codeine and morphine being removed by more than 80%. Primary biological transformation and sorption onto sludge as the main removal mechanisms were examined in lab-scale batch experiments. Sorption onto activated sludge was found to be negligible (<3%). The biological transformation could be described by pseudo-first order kinetics and the transformation constants k_biol were used to predict the removal of beta blockers and psycho-active drugs in an activated sludge unit with a model. For most compounds the removal efficiencies measured on the full-scale WWTP were within the 95% confidence intervals predicted by the model. The results from full-scale measurements and modeling indicate that biological transformation in the nitrification tank together with parameters such as the sludge retention time and the temperature is crucial regarding the biological transformation of beta blockers and psycho-active drugs in conventional WWTPs.     

Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction

This paper presents an automated method for the segmentation of the vascular network in retinal images. The algorithm starts with the extraction of vessel centerlines, which are used as guidelines for the subsequent vessel filling phase. For this purpose, the outputs of four directional differential operators are processed in order to select connected sets of candidate points to be further classified as centerline pixels using vessel derived features. The final segmentation is obtained using an iterative region growing method that integrates the contents of several binary images resulting from vessel width dependent morphological filters. Our approach was tested on two publicly available databases and its results are compared with recently published methods. The results demonstrate that our algorithm outperforms other solutions and approximates the average accuracy of a human observer without a significant degradation of sensitivity and specificity.