Effective exposure to solar UV in building workers: influence of local and individual factors.

Excessive exposure to solar UV light is the main cause of skin cancers in humans. UV exposure depends on environmental as well as individual factors related to activity. Although outdoor occupational activities contribute significantly to the individual dose received, data on effective exposure are scarce and limited to a few occupations. A study was undertaken in order to assess effective short-term exposure among building workers and characterize the influence of individual and local factors on exposure. The effective exposure of construction workers in a mountainous area in the southern part of Switzerland was investigated through short-term dosimetry (97 dosimeters). Three altitudes, of about 500, 1500 and 2500 m were considered. Individual measurements over 20 working periods were performed using Spore film dosimeters on five body locations. The postural activity of workers was concomitantly recorded and static UV measurements were also performed. Effective exposure among building workers was high and exceeded occupational recommendations, for all individuals for at least one body location. The mean daily UV dose in plain was 11.9 SED (0.0-31.3 SED), in middle mountain 21.4 SED (6.6-46.8 SED) and in high mountain 28.6 SED (0.0-91.1 SED). Measured doses between workers and anatomical locations exhibited a high variability, stressing the role of local exposure conditions and individual factors. Short-term effective exposure ranged between 0 and 200% of ambient irradiation, indicating the occurrence of intense, subacute exposures. A predictive irradiation model was developed to investigate the role of individual factors. Posture and orientation were found to account for at least 38% of the total variance of relative individual exposure, and were also found to account more than altitude on the total variance of effective daily exposures. Targeted sensitization actions through professional information channels and specific prevention messages are recommended. Altitude outdoor workers should also benefit from preventive medical examination.

Estudi del disseny i la implementació d¿un: Sistema de control de la salut dels bancs europeus en temps real.

El Banc Central Europeu(BCE) ens ha encarregat preparar-li una base de dades on poder emmagatzemar uns registres diaris relacionats amb uns indicadors. En el moment d¿enregistrar els indicadors si es viola alguna regla de negoci, prèviament definides per el BCE, es llencen una sèrie d¿alertes que també s¿emmagatzemaran a la base de dades per al seu posterior tractament. Amb la informació emmagatzemada en aquesta base de dades(BD), el BCE utilitzant una aplicació per explotar aquestes dades, podrà controlar la salut dels bancs europeus en temps real i facilitar la presa de decisions. També se¿ns demana la implementació d¿un mòdul estadístic on hi hagin una sèrie de dades ja precalculades per facilitar la seva consulta.

Building Capacity in Developing Countries : OER for Food Safety

The Food Safety Knowledge Network (FSKN) was developed through the collaboration of Michigan State University and a professional network of international food industry retailers and manufacturers. The key objective of the FSKN project is to provide technical resources, in a cost effective way, in order to promote food safety in developing countries and for small and less developed companies. FSKN uses a competency based model including a framework, OERs, and assessments. These tools are being used to support face-to-face training, fully online training, and to gauge the learning outcomes of a series of pilot groups which were held in India, Egypt, and China.

AgShare : Building Community and Content with Multiple Partners

Michigan State University and OER Africa are creating a win-win collaboration of existing organizations for African publishing, localizing, and sharing of teaching and learning materials that fill critical resource gaps in African MSc agriculture curriculum. By the end of the 18-month planning and pilot initiative, African agriculture universities, faculty, students, researchers, NGO leaders, extension staff, and farmers will participate in building AgShare by demonstrating its benefits and outcomes and by building momentum and support for growth.

Building a Manifesto for OER sustainability : UK experiences

Evidence of sustainability, or the potential to achieve this, is increasingly a pre-requisite for OER activity, whether imposed by funders, by institutions requiring a 'business case' for OER, or practitioners themselves - academics, educational technologists and librarians, concerned about how to justify engagement with a unfamiliar, and unproven practices, in today's climate of limited resource. However, it is not clear what is meant by 'sustainability' in relation to OER, what will be needed to achieve or demonstrate this, nor who the expectation of sustainability relates to. This paper draws on experiences of UK OER projects to identify aspirations that those involved in delivering OER activity have for OER sustainability ¿ what a 'manifesto' for OER sustainability beyond project funding, based on OER use, might look like.

Virtual library, a real library?

Les possibilitats ofertes per la virtualitat tenen una gran importància en l'esfera educativa i en tots els aspectes referents a ella. Evidentment, les biblioteques i els centres de documentació no són estranys a aquest nou ambient virtual facilitat pel canvi social, econòmic i, sobretot, tecnològic que ha permès que els bibliotecaris-documentalistes accedeixin a gran quantitat d'informació i de documentació, permetent que actuïn com a agents intermediaris entre aquesta nova situació i l'ús que se'n poden fer pels diversos tipus d'usuaris.

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Towards a real-time vision-based navigation system for a small-class UUV

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

A new approach to real time traffic sign recognition based on colour information

The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs

Local WMR navigation with monocular data

This article presents recent WMR (wheeled mobile robot) navigation experiences using local perception knowledge provided by monocular and odometer systems. A local narrow perception horizon is used to plan safety trajectories towards the objective. Therefore, monocular data are proposed as a way to obtain real time local information by building two dimensional occupancy grids through a time integration of the frames. The path planning is accomplished by using attraction potential fields, while the trajectory tracking is performed by using model predictive control techniques. The results are faced to indoor situations by using the lab available platform consisting in a differential driven mobile robot

The Estrada Real project and endemic diseases: the case of schistosomiasis, geoprocessing and tourism

Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R² = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.

Real-time PCR-based quantification of Toxoplasma gondii in tissue samples of serologically positive outdoor chickens

This study aimed to quantify Toxoplasma gondii in tissue samples of serologically positive chickens using real-time polymerase chain reaction (PCR). Of 65 chickens evaluated, 28 were positive for T. gondii antibodies. Brain and heart samples were collected from 26 seropositive chickens and DNA was extracted using Trizol® and amplified using real-time PCR with SYBR® Green. Parasite DNA was detected in 24 of the 26 samples analyzed; the number of positive tissue samples and the parasite quantity did not differ between tissue types. The results confirmed the analytical sensitivity of parasite detection in chicken tissue samples and demonstrated the possibility of using other molecular systems for genotypic analysis.

Using 3D surface datasets to understand landslide evolution: From analogue models to real case study

Early detection of landslide surface deformation with 3D remote sensing techniques, as TLS, has become a great challenge during last decade. To improve our understanding of landslide deformation, a series of analogue simulation have been carried out on non-rigid bodies coupled with 3D digitizer. All these experiments have been carried out under controlled conditions, as water level and slope angle inclination. We were able to follow 3D surface deformation suffered by complex landslide bodies from precursory deformation still larger failures. These experiments were the basis for the development of a new algorithm for the quantification of surface deformation using automatic tracking method on discrete points of the slope surface. To validate the algorithm, comparisons were made between manually obtained results and algorithm surface displacement results. Outputs will help in understanding 3D deformation during pre-failure stages and failure mechanisms, which are fundamental aspects for future implementation of 3D remote sensing techniques in early warning systems.