Incorporating domain knowledge into the fuzzy connectedness framework: application to brain lesion volume estimation in multiple sclerosis

A method for incorporating prior knowledge into the fuzzy connectedness image segmentation framework is presented. This prior knowledge is in the form of probabilistic feature distribution and feature size maps, in a standard anatomical space, and "intensity hints" selected by the user that allow for a skewed distribution of the feature intensity characteristics. The fuzzy affinity between pixels is modified to encapsulate this domain knowledge. The method was tested by using it to segment brain lesions in patients with multiple sclerosis, and the results compared to an established method for lesion outlining based on edge detection and contour following. With the fuzzy connections (FC) method, the user is required to identify each lesion with a mouse click, to provide a set of seed pixels. The algorithm then grows the features from the seeds to define the lesions as a set of objects with fuzzy connectedness above a preset threshold. The FC method gave improved interobserver reproducibility of lesion volumes, and the set of pixels determined to be lesion was more consistent compared to the contouring method. The operator interaction time required to evaluate one subject was reduced from an average of 111 min with contouring to 16 min with the FC method.     

The use of Raman spectroscopy as a versatile characterization tool for calcium sulphoaluminate cements: a compositional and hydration study

Calcium sulphoaluminate (CSA) cement is considered the third series cement besides ordinary Portland cement (OPC) and calcium aluminate (CA) cement. It is produced from gypsum, bauxite and limestone at 1,300 °C and consists of yeelimite, belite and anhydrite as main mineral phases. In the last years, many attempts have been made in applying Raman spectroscopy for the characterization of cement, clinker minerals and supplementary cementing materials (SCMs), revealing that this technique is a valuable tool for the identification of different phases in cements. In this work micro-Raman spectroscopy has been used, together with X-ray diffraction, for the characterization of CSA cement and its main minerals. In order to identify which mineral phase is responsible for the different bands, Raman spectra have been acquired from synthesized yeelimite and belite phases (whose purity degree was checked by X-ray diffraction) and from calcium sulphate di-hydrate and anhydrous (gypsum and anhydrite, respectively). On these bases, Raman spectra collected on CSA clinker and cement have been successfully assigned. Moreover, Raman spectroscopy, together with X-ray diffraction, proved useful to follow the hydration process of CSA cement up to 28 days. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

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Carbon materials for chemical capacitive energy storage

Carbon materials have attracted intense interests as electrode materials for electrochemical capacitors, because of their high surface area, electrical conductivity, chemical stability and low cost. Activated carbons produced by different activation processes from various precursors are the most widely used electrodes. Recently, with the rapid growth of nanotechnology, nanostructured electrode materials, such as carbon nanotubes and template-synthesized porous carbons have been developed. Their unique electrical properties and well controlled pore sizes and structures facilitate fast ion and electron transportation. In order to further improve the power and energy densities of the capacitors, carbon-based composites combining electrical double layer capacitors (EDLC)-capacitance and pseudo-capacitance have been explored. They show not only enhanced capacitance, but as well good cyclability. In this review, recent progresses on carbon-based electrode materials are summarized, including activated carbons, carbon nanotubes, and template-synthesized porous carbons, in particular mesoporous carbons. Their advantages and disadvantages as electrochemical capacitors are discussed. At the end of this review, the future trends of electrochemical capacitors with high energy and power are proposed.     

“Brick‐and‐Mortar” Self‐Assembly Approach to Graphitic Mesoporous Carbon Nanocomposites

Mesoporous carbon materials do not have sufficient ordering at the atomic scale to exhibit good electronic conductivity. To date, mesoporous carbons having uniform mesopores and high surface areas have been prepared from partially‐graphitizable precursors in the presence of templates. High temperature thermal treatments above 2000 °C, which are usually required to increase conductivity, result in a partial or total collapse of the mesoporous structures and reduced surface areas induced by growth of graphitic domains, limiting their applications in electric double layer capacitors and lithium‐ion batteries. In this work, we successfully implemented a “brick‐and‐mortar” approach to obtain ordered graphitic mesoporous carbon nanocomposites with tunable mesopore sizes below 850 °C without using graphitization catalysts or high temperature thermal treatments. Phenolic resin‐based mesoporous carbons act as mortar to highly conductive carbon blacks and carbon onions (bricks). The capacitance and resistivity of final materials can be tailored by changing the mortar to brick ratios.     

A simple method to disentangle nanoparticle optical properties by darkfield microspectroscopy

We present a darkfield optical microspectroscopy technique devoted to the disentangled measurement of the absorption and scattering cross sections of nanoparticle (NP) samples with variable concentration. The robustness of the method, including the needed instrumental calibrations, is examined in detail by analyzing and quantifying the major sources of statistic and systematic errors. As an exemplary case, results are presented on a gold NP colloid. The technique takes advantage of a simple inverted microscope, coupled with a spectrograph and equipped with a darkfield condenser and a variable numerical aperture objective to obtain spectra either in darkfield or brightfield optical configurations. By adopting the Lambert–Beer (LB) equation modeling, we were able to disentangle and measure with a single setup the absorption, scattering, and extinction coefficients of the same sample by combining three spectra, obtained by opportunely varying the objective numerical aperture. Typical plasmonic resonances were recognized at approximately 520 and 750 nm. Optical coefficients were measured as a function of particle number density (0.04–3.94 µm^?3, corresponding to 40 µM–4 mM nominal Au concentration) and good linearity was verified up to ～1.5 µm^?3 (～1 mM Au). Moreover, extinction and scattering cross sections were quantified and the validity of the LB approximation was reviewed. Besides its applications to plasmonic NPs, this method may be appropriate for any colloid, provided there exists a characteristic spectral feature in the ultraviolet‐visible‐near infrared range. This technique may be exploited to localize NPs in biological samples. Microsc. Res. Tech. 77:886–895, 2014. © 2014 Wiley Periodicals, Inc.     

Impact of waste cooking oil in biodiesel blends on particle size distributions from a city-car engine

Using biodiesel as a blending component in diesel engine has demonstrated to reduce hydrocarbon and particulate matter emissions. Literature showed that biodiesel type, engine architecture and test conditions deeply affect performance and emission characteristics. Among suitable biodiesel fuels, waste cooking oil (WCO) is considered very attractive due to the reduced environmental impact without sacrificing engine performance.This paper aims at investigating how mixing ratio of biodiesel from WCO and mineral diesel affects the particle size distributions of a current state of art small displacement diesel engine.Experimental tests have been performed on an up-to date light common rail diesel engine. Its complete operative field has been investigated. The results obtained show that the use of biodiesel blends from WCO reduces the total number of particles emitted from the engine with respect to the diesel fuel; the reduction is more evident as the percentage of biodiesel in the blend increases. The number of particles in WCO biodiesel soot with diameter smaller than 10 nm is reduced as compared to diesel fuel; the same trend is observed for diameters larger than 200 nm; comparable particle numbers were obtained in the ultrafine range (Dp < 100 nm).     

CD146+ Pericytes Subset Isolated from Human Micro-Fragmented Fat Tissue Display a Strong Interaction with Endothelial Cells: A Potential Cell Target for Therapeutic Angiogenesis

Pericytes (PCs) are mesenchymal stromal cells (MSCs) that function as support cells and play a role in tissue regeneration and, in particular, vascular homeostasis. PCs promote endothelial cells (ECs) survival which is critical for vessel stabilization, maturation, and remodeling. In this study, PCs were isolated from human micro-fragmented adipose tissue (MFAT) obtained from fat lipoaspirate and were characterized as NG2⁺/PDGFRβ⁺/CD105⁺ cells. Here, we tested the fat-derived PCs for the dispensability of the CD146 marker with the aim of better understanding the role of these PC subpopulations on angiogenesis. Cells from both CD146-positive (CD146⁺) and negative (CD146⁻) populations were observed to interact with human umbilical vein ECs (HUVECs). In addition, fat-derived PCs were able to induce angiogenesis of ECs in spheroids assay; and conditioned medium (CM) from both PCs and fat tissue itself led to the proliferation of ECs, thereby marking their role in angiogenesis stimulation. However, we found that CD146⁺ cells were more responsive to PDGF-BB-stimulated migration, adhesion, and angiogenic interaction with ECs, possibly owing to their higher expression of NCAM/CD56 than the corresponding CD146⁻ subpopulation. We conclude that in fat tissue, CD146-expressing cells may represent a more mature pericyte subpopulation that may have higher efficacy in controlling and stimulating vascular regeneration and stabilization than their CD146-negative counterpart.     

The General Product Machine: a New Model for Symbolic FSM Traversal

Proving the equivalence of two Finite State Machines (FSMs) has many applications to synthesis, verification, testing, and diagnosis. Building their product machine is a theoretical framework for equivalence proof. There are some cases where product machine traversal, a necessary and sufficient check, is mandatory. This is much more complex than traversing just one of the component machines. This paper proposes an equivalence-preserving function that transforms the product machine in theGeneral Product Machine (GPM). Using the GPM in symbolic state space traversal reduces the size of the BDDs and makes image computation easier. As a result, GPM traversal is much less expensive than product machine traversal, its cost being close to dealing with a single machine.