Abstract
Precision agriculture is gaining an increasing interest in the current farming paradigm. This new production concept relies on the use of information technology (IT) to provide a control and supervising structure that can lead to better management policies. In this framework, imaging techniques that provide visual information over the farming area play an important role in production status monitoring. As such, accurate representation of the gathered production images is amajor concern, especially if those images are used in detection and classification tasks. Real scenes, observed in natural environment, present high dynamic ranges that cannot be represented by the common LDR (Low Dynamic Range) devices. However, this issue can be handled by High Dynamic Range (HDR) images since they have the ability to store luminance information similarly to the human visual system. In order to prove their advantage in image processing, a comparative analysis between LDR and HDR images, for fruits detection and counting, was carried out. The obtained results show that the use of HDR images improves the detection performance to more than 30% when compared to LDR.

Abstract
The brain emotional learning (BEL) control paradigm has been gathering increased interest by the control systems design community. However, the lack of a consistent mathematical formulation and computer based tools are factors that have prevented its more widespread use. In this article both features are tackled by providing a coherent mathematical framework for both the continuous and discrete-time formulations and by presenting a SIMULINK (R) computational tool that can be easily used for fast prototyping BEL based control systems.

Abstract
Despite the studies already developed about Trombe walls, more research work is needed to contribute to the knowledge about their behaviour and optimize it according to the specific characteristics of each climatic region. The ventilation openings and the shading device operation decisively influence the temperatures fluctuation along the system and that impact should be discussed. In this context, a test cell with a classical Trombe wall was submitted to real climatic conditions in a Portuguese city. The effect of ventilation openings and shading devices in the temperatures fluctuation was analysed. The temperatures in the air layer and along the massive wall presented a similar oscillation pattern and exceeded 60 degrees C without ventilation and shading devices. For this configuration, temperature values at the top of the air layer were always higher than those obtained at the base and a differential of 19 degrees C was achieved. The temperature fluctuation across the massive wall was not proportional to its thickness due to its heat storage capacity. When the ventilation system was closed and the shading device was not activated, the temperature inside the test cell exceeded the outside temperature value in 9 degrees C, showing the system ability to store and release heat.

Abstract
An analytical and experimental analysis on the Trombe wall thermal performance was carried out for different conditions of ventilation openings and occlusion device operation. Experimental results allowed to determine temperature fluctuation, heat flux, heat delay and air velocity at the ventilation openings. A calculation methodology was applied to estimate the heat gains and losses through the system using experimental data. Ventilation openings and occlusion device effect was immediately visible in the temperature fluctuation and, consequentelly, in the heat gains and losses. Experimental.results showed that, when there was no occlusion device, massive wall external surface temperature values exceeded 60 degrees C and, when it was placed, reduced to 30 degrees C or less. Heat took almost 3 times more to achieve the interior of the test cell when the ventilation openings were closed. Air velocity increased following a diagonally pattern from the bottom to the top of the ventilation opening and its values varied between 0.10 m/s and 0.40 m/s, leading to air flow values between 0.002 m(3)/s and 0.008 m(3)/s. The calculation methodology application allowed to determine the total gains through the system for a continuous period. The impact of the system operation on the different thermal performance parameters was observed.

Abstract
Animal experiments have gained importance in human diseases studies, namely neurological diseases and its biomechanical and physiological aspects. As a model of human disease, the rat offers many advantages over other organisms. For the biomechanical aspects of locomotion these studies are based on the analysis of animals' kinetic parameters, accessed through a locomotion measurement system. However, these systems are not yet thoroughly developed, are still scarce and are also very expensive when developed for studies using small rodents. In this paper, a system capable of measuring contact forces of small rodents is presented. The platform hardware is based on a 5 x 3 matrix of ultra-sensitive force sensors that produce a set of signals acquired in a LabVIEW (TM) environment, used for data acquisition and processing. The post processing steps include the removal of null data, curve normalization related to the rat's weight and expressed as percentage of passage, resulting in a gait pattern. The proposed cost-effective system has achieved excellent results regarding the locomotion profile of healthy animals.

Abstract
Traditional imageryprovided, for example, by RGB and/or NIR sensorshas proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors' ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestrywherein the combination of UAV and hyperspectral sensors plays a center roleis presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processingby isolating the common user from the processes' mathematical complexityseveral available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper's conclusions.