Instituto de Engenharia de Sistemas e Computadores Microsistemas e Nanotecnologias

Rhodamine dyes are widely used as fluorescent probes owing to their high absorption coefficient and broad fluorescence in the visible region of electromagnetic spectrum, high fluorescence quantum yield and photostability. A great interest in the development of new synthetic procedures for preparation of Rhodamine derivatives has arisen in recent years because for most applications the probe must be covalently linked to another (bio)molecule or surface. In this critical review the strategies for modification of Rhodamine dyes and a discussion on the variety of applications of these new derivatives as fluorescent probes are given (108 references).

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTThe Sol–Gel Route to Advanced Silica-Based Materials and Recent ApplicationsRosaria Ciriminna†, Alexandra Fidalgo‡, Valerica Pandarus§, François Béland§, Laura M. Ilharco*‡, and Mario Pagliaro*†View Author Information† Istituto per lo Studio dei Materiali Nanostrutturati, CNR, via U. La Malfa 153, 90146 Palermo, Italy‡ Centro de Química-Física Molecular and IN-Institute of Nanoscience and Nanotechnology, Instituto Superior Técnico, Complexo I, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal§ SiliCycle Inc., 2500, Parc-Technologique Boulevard, Quebec City, Quebec G1P 4S6, Canada*E-mail: (M.P.) [email protected] and (L.M.I.) [email protected]Cite this: Chem. Rev. 2013, 113, 8, 6592–6620Publication Date (Web):June 19, 2013Publication History Received2 October 2012Published online19 June 2013Published inissue 14 August 2013https://pubs.acs.org/doi/10.1021/cr300399chttps://doi.org/10.1021/cr300399creview-articleACS PublicationsCopyright © 2013 American Chemical SocietyRequest reuse permissionsArticle Views21861Altmetric-Citations478LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Catalysts,Coating materials,Nanocomposites,Nanoparticles,Silica Get e-Alerts

Deep desulfurization of diesel fuel has attracted the attention of a growing number of scientists and engineers due to the stringent regulations imposed on the presence of sulfur in fuel (10 ppm). To bring down the concentration of sulfur compounds to less than 10 ppm is very challenging and demands newer technologies. Novel processes are being proposed for this purpose. It is observed that ionic liquids as class of green solvents can play a major role in the deep desulfurization of diesel fuel. For this reason, this review focuses on the current status in application of ionic liquids for achieving ultra-low-sulfur diesel (ULSD). To get a comprehensive perspective about the topic, other techniques of desulfurization are also discussed in brief in the introduction. Here we propose that the appropriate removal method should be selected according to different systems. To achieve deep desulfurization using ionic liquids, a better understanding regarding the regeneration of ionic liquids is vitally important.

Magnetoresistive sensors using spin valves and magnetic tunnel junctions are reviewed, considering applications as readers in hard disk drives, as well as applications where the ultimate field detection limits are required (from nT down to pT). The sensor noise level in quasi-DC or high-frequency applications is described, leading to sensor design considerations concerning biomedical and read head applications. Magnetic tunnel junction based sensors using MgO barriers appear as the best candidates for ultra-low field (pT) detection, either in the high-frequency regime, or for quasi-DC applications.

Affordances encode relationships between actions, objects, and effects. They play an important role on basic cognitive capabilities such as prediction and planning. We address the problem of learning affordances through the interaction of a robot with the environment, a key step to understand the world properties and develop social skills. We present a general model for learning object affordances using Bayesian networks integrated within a general developmental architecture for social robots. Since learning is based on a probabilistic model, the approach is able to deal with uncertainty, redundancy, and irrelevant information. We demonstrate successful learning in the real world by having an humanoid robot interacting with objects. We illustrate the benefits of the acquired knowledge in imitation games.

Proposes a method for the visual-based navigation of a mobile robot in indoor environments, using a single omnidirectional (catadioptric) camera. The geometry of the catadioptric sensor and the method used to obtain a bird's eye (orthographic) view of the ground plane are presented. This representation significantly simplifies the solution to navigation problems, by eliminating any perspective effects. The nature of each navigation task is taken into account when designing the required navigation skills and environmental representations. We propose two main navigation modalities: topological navigation and visual path following. Topological navigation is used for traveling long distances and does not require knowledge of the exact position of the robot but rather, a qualitative position on the topological map. The navigation process combines appearance based methods and visual servoing upon some environmental features. Visual path following is required for local, very precise navigation, e.g., door traversal, docking. The robot is controlled to follow a prespecified path accurately, by tracking visual landmarks in bird's eye views of the ground plane. By clearly separating the nature of these navigation tasks, a simple and yet powerful navigation system is obtained.

In this paper, we propose novel methods to evaluate the performance of object detection algorithms in video sequences. This procedure allows us to highlight characteristics (e.g., region splitting or merging) which are specific of the method being used. The proposed framework compares the output of the algorithm with the ground truth and measures the differences according to objective metrics. In this way it is possible to perform a fair comparison among different methods, evaluating their strengths and weaknesses and allowing the user to perform a reliable choice of the best method for a specific application. We apply this methodology to segmentation algorithms recently proposed and describe their performance. These methods were evaluated in order to assess how well they can detect moving regions in an outdoor scene in fixed-camera situations

Due to its manufacturing and size tailoring ease, porous anodic alumina (PAA) templates are an elegant physical-chemical nanopatterning approach and an emergent alternative to more sophisticated and expensive methods currently used in nanofabrication. In this review, we will describe the ground work on the fabrication methods of PAA membranes and PAA-based nanostructures. We will present the specificities of the electrochemical growth processes of multifunctional nanomaterials with diversified shapes (e.g., nanowires and nanotubes), and the fabrication techniques used to grow ordered nanohole arrays. We will then focus on the fabrication, properties and applications of magnetic nanostructures grown on PAA and illustrate their dependence on internal (diameter, interpore distance, length, composition) and external (temperature and applied magnetic field intensity and direction) parameters. Finally, the most outstanding experimental findings on PAA-grown nanostructures and their trends for technological applications (sensors, energy harvesting, metamaterials, and biotechnology) will be addressed.

Magnetoresistive (MR) sensors have been identified as promising candidates for the development of high-performance magnetometers due to their high sensitivity, low cost, low power consumption, and small size. The rapid advance of MR sensor technology has opened up a variety of MR sensor applications. These applications are in different areas that require MR sensors with different properties. Future MR sensor development in each of these areas requires an overview and a strategic guide. An MR sensor roadmap (non-recording applications) was therefore developed and made public by the Technical Committee of the IEEE Magnetics Society with the aim to provide an research and development (R&D) guide for MR sensors intended to be used by industry, government, and academia. The roadmap was developed over a three-year period and coordinated by an international effort of 22 taskforce members from ten countries and 17 organizations, including universities, research institutes, and sensor companies. In this paper, the current status of MR sensors for non-recording applications was identified by analyzing the patent and publication statistics. As a result, timescales for MR sensor development were established and critical milestones for sensor parameters were extracted in order to gain insight into potential MR sensor applications (non-recording). Five application areas were identified, and five MR sensor roadmaps were established. These include biomedical applications, flexible electronics, position sensing and human–computer interactions, non-destructive evaluation and monitoring, and navigation and transportation. Each roadmap was analyzed using a logistic growth model, and new opportunities were predicted based on the extrapolated curve, forecast milestones, and professional judgment of the taskforce members. This paper provides a framework for MR sensor technology (non-recording applications) to be used for public and private R&D planning, in order to provide guidance into likely MR sensor applications, products, and services expected in the next 15 years and beyond.

We surveyed the "dark" proteome-that is, regions of proteins never observed by experimental structure determination and inaccessible to homology modeling. For 546,000 Swiss-Prot proteins, we found that 44-54% of the proteome in eukaryotes and viruses was dark, compared with only ∼14% in archaea and bacteria. Surprisingly, most of the dark proteome could not be accounted for by conventional explanations, such as intrinsic disorder or transmembrane regions. Nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. Dark proteins fulfill a wide variety of functions, but a subset showed distinct and largely unexpected features, such as association with secretion, specific tissues, the endoplasmic reticulum, disulfide bonding, and proteolytic cleavage. Dark proteins also had short sequence length, low evolutionary reuse, and few known interactions with other proteins. These results suggest new research directions in structural and computational biology.

We present a new supervised learning model designed for the automatic segmentation of the left ventricle (LV) of the heart in ultrasound images. We address the following problems inherent to supervised learning models: 1) the need of a large set of training images; 2) robustness to imaging conditions not present in the training data; and 3) complex search process. The innovations of our approach reside in a formulation that decouples the rigid and nonrigid detections, deep learning methods that model the appearance of the LV, and efficient derivative-based search algorithms. The functionality of our approach is evaluated using a data set of diseased cases containing 400 annotated images (from 12 sequences) and another data set of normal cases comprising 80 annotated images (from two sequences), where both sets present long axis views of the LV. Using several error measures to compute the degree of similarity between the manual and automatic segmentations, we show that our method not only has high sensitivity and specificity but also presents variations with respect to a gold standard (computed from the manual annotations of two experts) within interuser variability on a subset of the diseased cases. We also compare the segmentations produced by our approach and by two state-of-the-art LV segmentation models on the data set of normal cases, and the results show that our approach produces segmentations that are comparable to these two approaches using only 20 training images and increasing the training set to 400 images causes our approach to be generally more accurate. Finally, we show that efficient search methods reduce up to tenfold the complexity of the method while still producing competitive segmentations. In the future, we plan to include a dynamical model to improve the performance of the algorithm, to use semisupervised learning methods to reduce even more the dependence on rich and large training sets, and to design a shape model less dependent on the training set.

We propose a new methodology for reliably solving the correspondence problem between sparse sets of points of two or more images. This is a key step inmost problems of computer vision and, so far, no general method exists to solve it. Our methodology is able to handle most of the commonly used assumptions in a unique formulation, independent of the domain of application and type of features. It performs correspondence and outlier rejection in a single step and achieves global optimality with feasible computation. Feature selection and correspondence are first formulated as an integer optimization problem. This is a blunt formulation, which considers the whole combinatorial space of possible point selections and correspondences. To find its global optimal solution, we build a concave objective function and relax the search domain into its convex-hull. The special structure of this extended problem assures its equivalence to the original one, but it can be optimally solved by efficient algorithms that avoid combinatorial search. This methodology can use any criterion provided it can be translated into cost functions with continuous second derivatives.

We study the magnetization damping in ion-beam deposited Co72Fe18B10 thin films as a function of film thickness and crystalline state. As-deposited amorphous layers showed low damping (αapp=0.006) that is thickness independent. 40nm Co80Fe20 with no boron content exhibited a value twice higher (αapp=0.013). Crystallization in Co72Fe18B10, triggered by annealing at 280°C, results in increased magnetization as well as a strong increase in damping, by a factor of 5 for 40nm films. For lower thicknesses the damping increase upon annealing is less pronounced. The exchange stiffness constant for amorphous films is deduced from perpendicular standing spin waves to be 28.4×10−12J∕m. The annealing dependence of damping should have consequences for the spin-transfer switching in CoFeB∕MgO∕CoFeB magnetic tunnel junctions.

A chemical procedure was developed to functionalize poly(methyl methacrylate) (PMMA) substrates. PMMA is reacted with hexamethylene diamine to yield an aminated surface for immobilizing DNA in microarrays. The density of primary NH2 groups was 0.29 nmol/cm2. The availability of these primary amines was confirmed by the immobilization of DNA probes and hybridization with a complementary DNA strand. The hybridization signal and the hybridization efficiency of the chemically aminated PMMA slides were comparable to the hybridization signal and the hybridization efficiency obtained from differently chemically modified PMMA slides, silanized glass, commercial silylated glass and commercial plastic Euray trade mark slides. Immobilized and hybridized densities of 10 and 0.75 pmol/cm2, respectively, were observed for microarrays on chemically aminated PMMA. The immobilized probes were heat stable since the hybridization performance of microarrays subjected to 20 PCR heat cycles was only reduced by 4%. In conclusion, this new strategy to modify PMMA provides a robust procedure to immobilize DNA, which is a very useful substrate for fabricating single use diagnostics devices with integrated functions, like sample preparation, treatment and detection using microfabrication and microelectronic techniques.

We describe a method for visual based robot navigation with a single omni-directional (catadioptic) camera. We show how omni-directional images can be used to generate the representations needed for two main navigation modalities: Topological Navigation and Visual Path Following. Topological Navigation relies on the robot's qualitative global position, estimated from a set of omni-directional images obtained during a training stage (compressed using PCA). To deal with illumination changes, an eigenspace approximation to the Hausdorff measure is exploited. We present a method to transform omni-directional images to Bird's Eye Views that correspond to scaled orthographic views of the ground plane. These images are used to locally control the orientation of the robot, through visual servoing. Visual Path Following is used to accurately control the robot along a prescribed trajectory, by using bird's eye views to track landmarks on the ground plane. Due to the simplified geometry of these images, the robot's pose can be estimated easily and used for accurate trajectory following. Omni-directional images facilitate landmark based navigation, since landmarks remain visible in all images, as opposed to a small field-of-view standard camera. Also, omni-directional images provide the means of having adequate representations to support both accurate or qualitative navigation. Results are described in the paper.

Magnetic bead sensors based on the planar Hall effect in thin films of exchange-biased permalloy have been fabricated and characterized. Typical sensitivities are 3 μV/Oe mA. The sensor response to an applied magnetic field has been measured without and with coatings of commercially available 2 μm and 250 nm magnetic beads used for bioapplications (Micromer-M and Nanomag-D, Micromod, Germany). Detection of both types of beads and single bead detection of 2 μm beads is demonstrated, i.e., the technique is feasible for magnetic biosensors. Single 2 μm beads yield 300 nV signals at 10 mA and 15 Oe applied field.

Image enhancement is the task of applying certain transformations to an input image such as to obtain a visually more pleasant, more detailed, or less noisy output image. The transformation usually requires interpretation and feedback from a human evaluator of the output result image. Therefore, image enhancement is considered a difficult task when attempting to automate the analysis process and eliminate the human intervention. This paper introduces a new automatic image enhancement technique driven by an evolutionary optimization process. We propose a novel objective criterion for enhancement, and attempt finding the best image according to the respective criterion. Due to the high complexity of the enhancement criterion proposed, we employ an evolutionary algorithm (EA) as a global search strategy for the best enhancement. We compared our method with other automatic enhancement techniques, like contrast stretching and histogram equalization. Results obtained, both in terms of subjective and objective evaluation, show the superiority of our method.

The concept of affordances appeared in psychology during the late 60s as an alternative perspective on the visual perception of the environment. It was revolutionary in the intuition that the way living beings perceive the world is deeply influenced by the actions they are able to perform. Then, across the last 40 years, it has influenced many applied fields, e.g., design, human-computer interaction, computer vision, and robotics. In this paper, we offer a multidisciplinary perspective on the notion of affordances. We first discuss the main definitions and formalizations of the affordance theory, then we report the most significant evidence in psychology and neuroscience that support it, and finally we review the most relevant applications of this concept in robotics.

The synchronization of two pendulum clocks hanging from a wall was first observed by Huygens during the XVII century. This type of synchronization is observed in other areas, and is fundamentally different from the problem of two clocks hanging from a moveable base. We present a model explaining the phase opposition synchronization of two pendulum clocks in those conditions. The predicted behaviour is observed experimentally, validating the model.

This paper addresses the development of a vision-based target tracking system for a small unmanned air vehicle. The algorithm performs autonomous tracking of a moving target, while simultaneously estimating GPS coordinates of the target. A low cost off the shelf system is utilized, with a modified radio controlled aircraft airframe, gas engine and servos. Tracking is enabled using a low-cost, miniature pan-tilt gimbal. The control algorithm provides rapid and sustained target acquisition and tracking capability. A target position estimator was designed and shown to provide reasonable targeting accuracy. The impact of target loss events on the control and estimation algorithms is analyzed in detail