Abstract

Abstract
Due to their universal accessibility, interactivity and scaling ease, Web applications relying on client-side code execution are currently the most common form of delivering applications and it is likely that they will continue to enter into less common realms such as IoT-based applications. We reason that modern Web applications should be able to exhibit advanced security protection mechanisms and review the research literature that points to useful partial solutions. Then, we propose a framework to support such characteristics and the features needed to implement them, providing a roadmap for a comprehensive solution to support Web application integrity. Copyright

Abstract
Knowledge of the optical properties of tissues is necessary, since they change from tissue to tissue and can differ between normal and pathological conditions. These properties are used in light transport models with various areas of application. In general, tissues have significantly high scattering coefficient when compared to the absorption coefficient and such difference usually increases with decreasing wavelength. The study of the wavelength dependence of the optical properties has been already made for several animal and human tissues, but extensive research is still needed in this field. Considering that most of the Biophotonics techniques used in research and clinical practice use visible to NIR light, we have estimated the optical properties of colorectal muscle (muscularis propria) between 400 and 1000 nm. The samples used were collected from patients undergoing resection surgery for colorectal carcinoma. The estimated scattering coefficient for colorectal muscle decreases exponentially with wavelength from 122 cm(-1) at 400 nm to 95 cm(-1) at 650 nm and to 91 cm(-1) at 1000 nm. The absorption coefficient shows a wavelength dependence according to the behavior seen for other tissues, since it decreases from 8 cm(-1) at 400 nm to 2.6 cm(-1) at 650 nm and to 1.3 cm(-1) at 1000 nm. The estimated optical properties differ from the ones that we have previously obtained for normal and pathological colorectal mucosa. The data obtained in this study covers an extended spectral range and it can be used for planning optical clearing treatments for some wavelengths of interest.

Abstract
To characterize the optical clearing treatments in human colorectal tissues and possibly to differentiate between treatments of normal and pathological tissues, we have used a simple indirect method derived from Mie scattering theory to estimate the kinetics of the reduced scattering coefficient. A complementary method to estimate the kinetics of the scattering coefficient is also used so that the kinetics of the anisotropy factor and of the refractive index are also calculated. Both methods rely only on the thickness and collimated transmittance measurements made during treatment. The results indicate the expected time dependencies for the optical properties of both tissues: an increase in the refractive index and anisotropy factor and a decrease in the scattering coefficients. The similarity in the kinetics obtained for normal and pathological tissues indicates that optical clearing treatments can be applied also in pathological tissues to produce similar effects. The estimated time dependencies using experimental spectral data in the range from 400 to 1000 nm allowed us to compare the kinetics of the optical properties between different wavelengths. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

Abstract
With the objective of developing a diagnostic tool, we have used the immersion optical clearing method and studied normal and pathological tissues (cancer, diabetes) under treatment by optical clearing agents (OCAs). In order to quantify pathology status OCA diffusion properties in different tissues were measured. We have demonstrated that free water content in cancerous tissues is higher than in normal.

Abstract
Numerous diagnostic decisions are made every day by healthcare professionals. Bayesian networks can provide a useful aid to the process, but learning their structure from data generally requires the absence of missing data, a common problem in medical data. We have studied missing data imputation using a step-wise nearest neighbors' algorithm, which we recommended given its limited impact on the assessed validity of structure learning Bayesian network classifiers for Obstructive Sleep Apnea diagnosis. © 2018 European Federation for Medical Informatics (EFMI) and IOS Press.