Abstract
Focused ion beam (FIB) patterning of 3D topography on optical fiber tips for application in stand-alone, rugged and simplified setups for optical tweezers cell sorters, optical near-field lithography and optical beam profile engineering are reported. We demonstrate various configurations based on single-step FIB patterning, multiple-step FIB processing and hybrid approaches based on optical fiber pre- and post-FIB treatment with either etching, fusion splicing, photo-polymerization or electroplating steps for optical fiber texture, topography and composition engineering. Different conductive coatings for minimal charge accumulation and beam drift are studied with the relative merits compared. Furthermore optimal beam parameters for accurate pattern replication and positioning are also presented. Measured experimental field profiles are compared with numerical simulations of fabricated optical fiber tips for fabrication accuracy evaluation. Applications employing these engineered fiber tips in the field of optical tweezers, optical vortex generation, photolithography, photo-polymerization and beam forming are presented.

Abstract
The increase in the complexity inherent to public administrative activities, including public procurement, has led ANO to develop a public e-procurement platform in order for Portuguese public entities to perform their contracts and acquisitions. Given the introduction of European PEPPOL standards and the requirement for all Portuguese e-procurement platforms to be WCAG 2.0 level A compliant, ANO company established a consortium with the UTAD University in order to improve their platform and develop the required features. By using a specially designed stage-based work methodology, the R&D project was carried out with success and all initial goals were achieved. © Springer-Verlag Berlin Heidelberg 2015.

Abstract
Crop monitoring and harvesting by ground robots on mountain vineyards is an intrinsically complex challenge, due to two main reasons: harsh conditions of the terrain and reduced time availability and unstable localization accuracy of the GPS system. In this paper is presented a cost effective robot that can be used on these mountain vineyards for crop monitoring tasks. Also it is explored a natural vineyard feature as the input of a standard 2D simultaneous localization and mapping approach (SLAM) for feature-based map extraction. In order to be possible to evaluate these natural features for mapping and localization purposes, a virtual scenario under ROS/Gazebo has been built and described. A low cost artificial landmark and an hybrid SLAM is proposed to increase the localization accuracy, robustness and redundancy on these mountain vineyards. The obtained results, on the simulation framework, validates the use of a localization system based on natural mountain vineyard features.

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Abstract
In this paper a Distribution State Estimator (DSE) tool suitable for real-time monitoring in poorly characterized low voltage networks is presented. An Autoencoder (AE) properly trained with Extreme Learning Machine (ELM) technique is the "brain" of the DSE. The estimation of system state variables, i.e., voltage magnitudes and phase angles is performed with an Evolutionary Particle Swarm Optimization (EPSO) algorithm that makes use of the already trained AE. By taking advantage of historical data and a very limited number of quasi real-time measurements, the presented approach turns possible monitoring networks where information of topology and parameters is not available. Results show improvements in terms of estimation accuracy and time performance when compared to other similar DSE tools that make use of the traditional back-propagation based algorithms for training execution.