Abstract
The purpose of this study was to analyze the change in antagonist co-activation ratio of upper-limb muscle pairs, during the reaching movement, of both ipsilesional and contralesional limbs of post-stroke subjects. Nine healthy and nine post-stroke subjects were instructed to reach and grasp a target, placed in the sagittal and scapular planes of movement. Surface EMG was recorded from postural control and movement related muscles. Reaching movement was divided in two sub-phases, according to proximal postural control versus movement control demands, during which antagonist co-activation ratios were calculated for the muscle pairs LD/PM, PD/AD, TRIlat/BB and TRIlat/BR. Post-stroke's ipsilesional limb presented lower co-activation in muscles with an important role in postural control (LD/PM), comparing to the healthy subjects during the first sub-phase, when the movement was performed in the sagittal plane (p < 0.05). Conversely, the post-stroke's contralesional limb showed in general an increased co-activation ratio in muscles related to movement control, comparing to the healthy subjects. Our findings demonstrate that, in post-stroke subjects, the reaching movement performed with the ipsilesional upper limb seems to show co-activation impairments in muscle pairs associated to postural control, whereas the contralesional upper limb seems to have signs of impairment of muscle pairs related to movement.

Abstract
Use case specifications have successfully been used for requirements description. They allow joining, in the same modeling space, the expectations of the stakeholders as well as the needs of the software engineer and analyst involved in the process. While use cases are not meant to describe a system's implementation, by formalizing their description we are able to extract implementation relevant information from them. More specifically, we are interested in identifying requirements patterns (common requirements with typical implementation solutions) in support for a requirements based software development approach. In the paper we propose the transformation of Use Case descriptions expressed in a Controlled Natural Language into an ontology expressed in the Web Ontology Language (OWL). OWL's query engines can then be used to identify requirements patterns expressed as queries over the ontology. We describe a tool that we have developed to support the approach and provide an example of usage. © 2014 R. Couto, A.N. Ribeiro & J.C. Campos.

Abstract
Despite the socio-economic importance of mining in Douro Coalfield, the coal exploitation and utilization originated impacts on the environment. From these stands out the S. Pedro da Cova waste pile which is self-burning since 2005. The potential environmental impacts associated with this coal waste pile include: air pollution caused by the gaseous emissions and dispersion of solid particles; pollution of soils, surface and groundwater caused by mobilization of solid particles, leaching of hazardous elements, dissolution of neoformed and deposition of solid particles; landslides and mass movements also caused the weathering agents, and deterioration of vegetation that may also be due to the acid drainage. The main objective of this work is the combustion temperature monitoring in S. Pedro da Cova waste pile using the infrared thermography technique. The acquired results during the temperature monitoring campaigns allow the study of the dynamics and evolutionary scenarios of the self-burning process in the coal waste pile, contributing to a precise definition of the risks to the environment and human health. © 2014, LNEG – Laboratório Nacional de Geologia e Energia IP.

Abstract
An optical fiber sensor based on arrays of silica microspheres is proposed. The microspheres are produced separately using a fusion splicer and then also connected in series by fusion splicing. Three different sensors are presented, differing by the number of microspheres. Due to the geometry of the structures, different behaviors are obtained in strain measurements. Sensors with an odd number of microspheres are more sensitive to strain than the ones with an even number of microspheres. Additionally, the sensing heads are subjected to temperature where a sensitivity of 20.3 pm/degrees C is obtained in a range of 200 degrees C. (C) 2014 Optical Society of America

Abstract
In the current marketplace, enterprises face enormous competitive pressures. Global competition for customers that demand customized products with shorter due dates and the advancement in information technologies, marked the introduction of the Extended Enterprise. In these EMEs (Extended Manufacturing Environments), lean, virtual, networked and distributed enterprises, form MO (Meta-Organizations), which collaborate to respond to the dynamic marketplace. MO members share resources, customers and information. In this paper we present a hybrid framework based on a DKBS (Distributed Knowledge Base System), which includes information about scheduling methods for collaborative enterprises sharing their problems. A core component of this system includes an inference engine as well as two indexes, to help in the classification of the usefulness of the information about the problems and solving methods. A more structured approach for expanding the MO concept is presented, with the HO (Hyper-Organization). The manner in which MO-DSS can communicate, cooperate and share information, in the context of the HO is also detailed.

Abstract
Private car commuting is heavily dependent on the subsidisation that exists in the form of available free parking. However, the public funding policy of such free parking has been changing over the last years, with a substantial increase of meter-charged parking areas in many cities. To help to increase the sustainability of car transportation, a novel concept of a self-automated parking lot has been recently proposed, which leverages on a collaborative mobility of parked cars to achieve the goal of parking twice as many cars in the same area, as compared to a conventional parking lot. This concept, known as self-automated parking lots, can be improved if a reasonable prediction of the exit time of each car that enters the parking lot is used to try to optimize its initial placement, in order to reduce the mobility necessary to extract blocked cars. In this paper we show that the exit time prediction can be done with a relatively small error, and that this prediction can be used to reduce the collaborative mobility in a self-automated parking lot.