Design and early development of a UAV terminal and a ground station for laser communications

A free-space laser communication system has been designed and partially developed as an alternative to standard RF links from UAV to ground stations. This project belongs to the SINTONIA program (acronym in Spanish for low environmental-impact unmanned systems), led by BR&TE (Boeing Research and Technology Europe) with the purpose of boosting Spanish UAV technology. A MEMS-based modulating retroreflector has been proposed as a communication terminal onboard the UAV, allowing both the laser transmitter and the acquisition, tracking and pointing subsystems to be eliminated. This results in an important reduction of power, size and weight, moving the burden to the ground station. In the ground station, the ATP subsystem is based on a GPS-aided two-axis gimbal for tracking and coarse pointing, and a fast steering mirror for fine pointing. A beacon-based system has been designed, taking advantage of the retroreflector optical principle, in order to determine the position of the UAV in real-time. The system manages the laser power in an optimal way, based on a distance-dependent beam-divergence control and by creating two different optical paths within the same physical path using different states of polarization.Comment: 9 pages, 12 figures. Appears in Proceedings of the SPIE Security+Defence (Prague, Czech Republic, 2011

Efficient plot-based floristic assessment of tropical forests

The tropical flora remains chronically understudied and the lack of floristic understanding hampers ecological research and its application for large-scale conservation planning. Given scarce resources and the scale of the challenge there is a need to maximize the efficiency of both sampling strategies and sampling units, yet there is little information on the relative efficiency of different approaches to floristic assessment in tropical forests. This paper is the first attempt to address this gap. We repeatedly sampled forests in two regions of Amazonia using the two most widely used plot-based protocols of floristic sampling, and compared their performance in terms of the quantity of floristic knowledge and ecological insight gained scaled to the field effort required. Specifically, the methods are assessed first in terms of the number of person-days required to complete each sample (‘effort’), secondly by the total gain in the quantity of floristic information that each unit of effort provides (‘crude inventory efficiency’), and thirdly in terms of the floristic information gained as a proportion of the target species pool (‘proportional inventory efficiency’). Finally, we compare the methods in terms of their efficiency in identifying different ecological patterns within the data (‘ecological efficiency’) while controlling for effort. There are large and consistent differences in the performance of the two methods. The disparity is maintained even after accounting for regional and site-level variation in forest species richness, tree density and the number of field assistants. We interpret our results in the context of selecting the appropriate method for particular research purposes

Green Production of Anionic Surfactant Obtained from Pea Protein

A pea protein isolate was hydrolyzed by a double enzyme treatment method in order to obtain short peptide sequences used as raw materials to produce lipopeptides-based surfactants. Pea protein hydrolysates were prepared using the combination of Alcalase and Flavourzyme. The influence of the process variables was studied to optimize the proteolytic degradation to high degrees of hydrolysis. The average peptide chain lengths were obtained at 3–5 amino acid units after a hydrolysis of 30 min with the mixture of enzymes. Then, N-acylation in water, in presence of acid chloride (C12 and C16), carried out with a conversion rate of amine functions of 90%, allowed to obtain anionic surfactant mixtures (lipopeptides and sodium fatty acids). These two steps were performed in water, in continuous and did not generate any waste. This process was therefore in line with green chemistry principles. The surface activities (CMC, foaming and emulsifying properties) of these mixtures were also studied. These formulations obtained from natural renewable resources and the reactions done under environmental respect, could replace petrochemical based surfactants for some applications

Hormone secreted by the pineal gland - melatonin feedsideward involvement in cancer growth

Here the presence of a chronomodulating actions of melatonin via feedsideawards mechanism in vitro as well as, in vivo, in two experimental models was presented. Intriguing process of how this takes place may due to an interacting pineal pituitary-adrenal networks (1). In vivo studies confirmed the role of melatonin in the study on Meth-A-sarcoma in mice and in LOU tumor growth. Melatonin disrupted circadian time structure of in vivo tumor growth on a feedsideawards manner in the case of the immunocytoma growth in female inoculated rats. Low doses disrupted the circadian DNA synthesis of mF-cells. Drug delivery systems must be taken in consideration the role of melatonin feedsideawards involvement during chronomodulated therapy of cancer patients

Selecting patterns and features for between- and within-crop-row weed mapping using UAV-imagery

This paper approaches the problem of weed mapping for precision agriculture, using imagery provided by Unmanned Aerial Vehicles (UAVs) from sunflower and maize crops. Precision agriculture referred to weed control is mainly based on the design of early post-emergence site-specific control treatments according to weed coverage, where one of the most important challenges is the spectral similarity of crop and weed pixels in early growth stages. Our work tackles this problem in the context of object-based image analysis (OBIA) by means of supervised machine learning methods combined with pattern and feature selection techniques, devising a strategy for alleviating the user intervention in the system while not compromising the accuracy. This work firstly proposes a method for choosing a set of training patterns via clustering techniques so as to consider a representative set of the whole field data spectrum for the classification method. Furthermore, a feature selection method is used to obtain the best discriminating features from a set of several statistics and measures of different nature. Results from this research show that the proposed method for pattern selection is suitable and leads to the construction of robust sets of data. The exploitation of different statistical, spatial and texture metrics represents a new avenue with huge potential for between and within crop-row weed mapping via UAV-imagery and shows good synergy when complemented with OBIA. Finally, there are some measures (specially those linked to vegetation indexes) that are of great influence for weed mapping in both sunflower and maize crops