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BackgroundBioimaging techniques offer a robust tool for studying molecular pathways and morphological phenotypes of cell populations subjected to various conditions. As modern high resolution 3D microscopy provides access to an ever-increasing amount of high quality images, there arises a need for their analysis in an automated, unbiased and simple way.Segmentation of structures within cell nucleus, which is the focus of this paper, presents a new layer of complexity in the form of dense packing and significant signal overlap.At the same time the available segmentation tools provide a steep learning curve for new users with limited technical background. This is especially apparent in bulk processing of image sets, which requires the use of some form of programming notation.ResultsIn this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of cell nucleus. PartSeg integrates refined versions of several state-of-the-art algorithms, including a new multi-scale approach for segmentation and quantitative analysis of 3D microscopy images.The features and user-friendly interface of PartSeg were carefully planned with biologists in mind, based on analysis of multiple use cases and difficulties encountered with other tools, to offer ergonomic interface with a minimal entry barrier. Bulk processing in an ad-hoc manner is possible without the need for programmer support. As the size of datasets of interest grows, such bulk processing solutions become essential for proper statistical analysis of results.Advanced users can use PartSeg components as a library within Python data processing and visualisation pipelines, for example within Jupyter notebooks. The tool is extensible so that new functionality and algorithms can be added by the use of plugins.For biologists the utility of PartSeg is presented in several scenarios, showing the quantitative analysis of nuclear structures.ConclusionsIn this paper, we have presented PartSeg which is a tool for precise and verifiable segmentation and reconstruction of 3D microscopy images. PartSeg is optimised for cell nucleus analysis and offers multiscale segmentation algorithms best-suited for this task. PartSeg can also be used for bulk processing of multiple images and its components can be reused in other systems or computational experiments.Contactg.bokota@cent.uw.edu.pl, a.magalska@nencki.edu.pl, d.plewczynski@cent.uw.edu.pl

A general method is presented for in situ assessment of mechanical strength degradation of materials or components using an embedded interferometric fiber-optic strain sensor. This method is based on the analysis of acoustic signature responses resulting from mechanical excitation of the subject under investigation. Acoustic signature responses are observed by monitoring light intensity changes resulting from the combination of light signals traveling through the embedded optical fiber (experiencing dimensional changes through vibrational excitation) and an external optical fiber. This paper discusses the fundamental aspects of the methodology and its potential investigational pathways and applications. A case study, addressing unobservable corrosion related degradation of aircraft fuselage lap joints is presented as an example for retrieving information and to demonstrate the correlations between material properties and fiber-optic interferometric measurements. The application of inverse method analysis for the interpretation of response signals is also discussed.

The authors present a general method based on inverse analysis of light signals from a fiber-optic sensor for in situ detection of metal, film, or coating degradation. This method, which does not, in principle, depend on the geometry of the fiber-optic sensor, is based on analysis of reflected light intensity loss as opposed to reflected or transmitted intensity modulation. Following an inverse-analysis approach, the level and rate of intensity loss are correlated with levels and rates of surface degradation. This approach allows optimization of fiber-optic sensors for specific applications and different environments. Case study analyses using experimental data are used to demonstrate the fundamentals of various aspects of this method.

The effects of six commercial water-soluble inhibitor formulations on the corrosion rates of aluminum and steel in seawater were determined. Corrosion rates were measured by the weight loss of specimens following long-term immersion in artificial seawater containing inhibitors at the developer’s recommended dosages. The effects of environmental changes on inhibitor behavior were also investigated by varying the seawater concentration in certain tests. Surface plasmon resonance (SPR) spectroscopy was investigated as a method to observe the inherent adherence and persistence of the inhibitors at a metal surface. Results show that the level of effectiveness of the test inhibitors varies significantly and is dependent on the nature of the metal being protected. While some inhibitors reduce the corrosion of steel by up to 80%, others actually increase the corrosion rate. Four of the six inhibitors were observed to increase aluminum pitting; the other two offered protection. Two of the inhibitors reduced the corrosion rates for the aluminum and steel. Surface plasmon resonance spectroscopy was able to detect and discriminate between inhibitors. These measurements show good correlation between the adherence of an inhibitor to a metal surface and its ability to reduce corrosion rates. Results of this study provide a firm measure of the levels of corrosion control that can be achieved by commercially available inhibitor formulations. They also provide a quantitative basis for comparison and selection of corrosion inhibitors for use in a variety of applications (i.e., metal holding tanks and cans, recirculation loops, and modified wash downs of outdoor equipment typically experiencing deterioration due to exposure to salt-containing environments).

Powders and thin coatings of ceria and titania were synthesized from aqueous and solvent-based precursors. Thin coatings were deposited on polished 304 stainless steel coupons by dipping them in the appropriate sol-gel oxide precursors. The coatings were subsequently densified and crystallized at several hundreds of degrees. It was possible to obtain dense titania coatings by applying thin coatings of cerium dioxide prior to titania on stainless steel substrates. Underlayer ceria coatings proved to be pivotal in obtaining dense titania coatings and preserving the integrity of the stainless steel while going through the high temperature treatments. The effect of processing parameters such as the atmosphere of heat-treatment, and temperature on the microstructure and crystal structure of the films and powders of ceria and titania was investigated. X-ray diffraction was used to identify the crystal structure of films and powders upon heat-treatment. Electrochemical measurements in NaCl, and analytical techniques such as SEM and EDX were used to evaluate the corrosion performance and pitting morphology of coated samples. A composite coating of ceria and titania was able to prevent crevice corrosion and increase the pitting resistance of the 304 stainless steel relative to the uncoated substrate.

SCOPUS: ar.j, info:eu-repo/semantics/published