ALBERT

Description: In this paper, the integration of directional antennas in a room-level received signal strength (RSS) fingerprinting-based indoor localization system (ILS) is studied. The sensor reader (SR), which is in charge of capturing the RSS to infer the tag position, can be attached to an omnidirectional or directional antenna. Unlike commonly-employed omnidirectional antennas, directional antennas can receive a stronger signal from the direction in which they are pointed, resulting in a different RSS distributions in space and, hence, more distinguishable fingerprints. A simulation tool and a system management software have been also developed to control the system and assist the initial antenna deployment, reducing time-consuming costs. A prototype was mounted in a real scenario, with a number of SRs with omnidirectional and directional antennas properly positioned. Different antenna configurations have been studied, evidencing a promising capability of directional antennas to enhance the performance of RSS fingerprinting-based ILS, reducing the number of required SRs and also increasing the localization success.

Description: Net radiation is an essential forcing of climate in the lower layers of Earth’s atmosphere. In this paper, radiation balance is measured in clay soil and green grass, and is compared with three urban materials. These materials: asphalt, concrete and white painted elastomeric polystyrene roofing sheet are widely used in Mexicali, Baja California, México. This study was carried out during August of 2011, the hottest time of the year. The 24-hour average values of net radiation found were: 137.2 W·m−2 for asphalt, 119.1 for concrete, 104.6 for clay soil, 152 for green grass and 29.2 for the polystyrene insulation. The latter two types of materials are likely to be the most effective in reducing urban heat island effects. This variation in the radiation balance has widespread implications for human living conditions, as land cover change tends to be towards surfaces that have higher levels of net radiation.

Description: Indoor navigation is a challenging task for visually impaired people. Although there are guidance systems available for such purposes, they have some drawbacks that hamper their direct application in real-life situations. These systems are either too complex, inaccurate, or require very special conditions (i.e., rare in everyday life) to operate. In this regard, Ultra-Wideband (UWB) technology has been shown to be effective for indoor positioning, providing a high level of accuracy and low installation complexity. This paper presents SUGAR, an indoor navigation system for visually impaired people which uses UWB for positioning, a spatial database of the environment for pathfinding through the application of the A* algorithm, and a guidance module. The interaction with the user takes place using acoustic signals and voice commands played through headphones. The suitability of the system for indoor navigation has been verified by means of a functional and usable prototype through a field test with a blind person. In addition, other tests have been conducted in order to show the accuracy of different relevant parts of the system.

Description: Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies in order to assess crop yield. Frequently, plant canopy analyzers (LAI-2000) and digital cameras for hemispherical photography (DHP) are used for indirect effective plant area index (PAIeff) estimates. Nevertheless, these instruments are expensive and have the disadvantages of low portability and maintenance. Recently, a smartphone app called PocketLAI was presented and tested for acquiring PAIeff measurements. It was used during an entire rice season for indirect PAIeff estimations and for deriving reference high-resolution PAIeff maps. Ground PAIeff values acquired with PocketLAI, LAI-2000, and DHP were well correlated (R2 = 0.95, RMSE = 0.21 m2/m2 for Licor-2000, and R2 = 0.94, RMSE = 0.6 m2/m2 for DHP). Complementary data such as phenology and leaf chlorophyll content were acquired to complement seasonal rice plant information provided by PAIeff. High-resolution PAIeff maps, which can be used for the validation of remote sensing products, have been derived using a global transfer function (TF) made of several measuring dates and their associated satellite radiances.

Description: In order to perform sensing tasks, most current Intelligent Transportation Systems (ITS) rely on expensive sensors, which offer only limited functionality. A more recent trend consists of using Wireless Sensor Networks (WSN) for such purpose, which reduces the required investment and enables the development of new collaborative and intelligent applications that further contribute to improve both driving safety and traffic efficiency. This paper surveys the application of WSNs to such ITS scenarios, tackling the main issues that may arise when developing these systems. The paper is divided into sections which address different matters including vehicle detection and classification as well as the selection of appropriate communication protocols, network architecture, topology and some important design parameters. In addition, in line with the multiplicity of different technologies that take part in ITS, it does not consider WSNs just as stand-alone systems, but also as key components of heterogeneous systems cooperating along with other technologies employed in vehicular scenarios.

Description: This paper evaluates the performance of spatial methods to estimate leaf area index (LAI) fields from ground-based measurements at high-spatial resolution over a cropland landscape. Three geostatistical model variants of the kriging technique, the ordinary kriging (OK), the collocated cokriging (CKC) and kriging with an external drift (KED) are used. The study focused on the influence of the spatial sampling protocol, auxiliary information, and spatial resolution in the estimates. The main advantage of these models lies in the possibility of considering the spatial dependence of the data and, in the case of the KED and CKC, the auxiliary information for each location used for prediction purposes. A high-resolution NDVI image computed from SPOT TOA reflectance data is used as an auxiliary variable in LAI predictions. The CKC and KED predictions have proven the relevance of the auxiliary information to reproduce the spatial pattern at local scales, proving the KED model to be the best estimator when a non-stationary trend is observed. Advantages and limitations of the methods in LAI field predictions for two systematic and two stratified spatial samplings are discussed for high (20 m), medium (300 m) and coarse (1 km) spatial scales. The KED has exhibited the best observed local accuracy for all the spatial samplings. Meanwhile, the OK model provides comparable results when a well stratified sampling scheme is considered by land cover.

Description: Within the ROAMER project, which aims to provide a Roadmap for Mental Health Research in Europe, a two-stage Delphi survey among 86 European experts was conducted in order to identify research priorities in clinical mental health research. Expert consensus existed with regard to the importance of three challenges in the field of clinical mental health research: (1) the development of new, safe and effective interventions for mental disorders; (2) understanding the mechanisms of disease in order to be able to develop such new interventions; and (3) defining outcomes (an improved set of outcomes, including alternative outcomes) to use for clinical mental health research evaluation. Proposed actions involved increasing the utilization of tailored approaches (personalized medicine), developing blended eHealth/mHealth decision aids/guidance tools that help the clinician to choose between various treatment modalities, developing specific treatments in order to better target comorbidity and (further) development of biological, psychological and psychopharmacological interventions. The experts indicated that addressing these priorities will result in increased efficacy and impact across Europe; with a high probability of success, given that Europe has important strengths, such as skilled academics and a long research history. Finally, the experts stressed the importance of creating funding and coordinated networking as essential action needed in order to target the variety of challenges in clinical mental health research.

Description: Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR) is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted) local regression filter (LOESS) and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG), smoothing spline (SSP), Interpolation for Data Reconstruction (IDR) and adaptive Savitzky-Golay (ASG). This paper evaluates the main advantages and drawbacks of the considered techniques. The results have shown that ASG and the adapted LOESS perform better in recovering fAPAR time series over multiple controlled noisy scenarios. Both methods can robustly reconstruct the fAPAR trajectories, reducing the noise up to 80% in the worst simulation scenario, which might be attributed to the quality control (QC) MODIS information incorporated into these filtering algorithms, their flexibility and adaptation to the upper envelope. The adapted LOESS is particularly resistant to outliers. This method clearly outperforms the other considered methods to deal with the high presence of gaps and noise in satellite data records. The low RMSE and biases obtained with the LOESS method (|rMBE| 〈 8%; rRMSE 〈 20%) reveals an optimal reconstruction even in most extreme situations with long seasonal gaps. An example of application of the LOESS method to fill in invalid values in real MODIS images presenting persistent cloud and snow coverage is also shown. The LOESS approach is recommended in most remote sensing applications, such as gap-filling, cloud-replacement, and observing temporal dynamics in situ where rapid seasonal changes are produced.

Description: The Smart Grid (SG) is conceived as the evolution of the current electrical grid representing a big leap in terms of efficiency, reliability and flexibility compared to today’s electrical network. To achieve this goal, the Wireless Sensor Networks (WSNs) are considered by the scientific/engineering community to be one of the most suitable technologies to apply SG technology to due to their low-cost, collaborative and long-standing nature. However, the SG has posed significant challenges to utility operators—mainly very harsh radio propagation conditions and the lack of appropriate systems to empower WSN devices—making most of the commercial widespread solutions inadequate. In this context, and as a main contribution, we have designed a comprehensive ad-hoc WSN-based solution for the Smart Grid (SENSED-SG) that focuses on specific implementations of the MAC, the network and the application layers to attain maximum performance and to successfully deal with any arising hurdles. Our approach has been exhaustively evaluated by computer simulations and mathematical analysis, as well as validation within real test-beds deployed in controlled environments. In particular, these test-beds cover two of the main scenarios found in a SG; on one hand, an indoor electrical substation environment, implemented in a High Voltage AC/DC laboratory, and, on the other hand, an outdoor case, deployed in the Transmission and Distribution segment of a power grid. The results obtained show that SENSED-SG performs better and is more suitable for the Smart Grid than the popular ZigBee WSN approach.

Description: IJERPH, Vol. 15, Pages 838: Furthering the Evidence of the Effectiveness of Employment Strategies for People with Mental Disorders in Europe: A Systematic Review International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15050838 Authors: Amalia Muñoz-Murillo Eva Esteban Carolina C. Ávila Klemens Fheodoroff Josep Maria Haro Matilde Leonardi Beatriz Olaya (1) Purpose: This systematic review aims to assess the effectiveness of strategies used in the professional (re)integration of persons with mental disorders (MD) in European countries; (2) Methods: We conducted a search for scientific publications available in relevant electronic databases (Medline, PsycINFO, CDR-HTA, CDR-DARE, and Cochrane Library). The present study collected evidence on the effectiveness, from 2011 to 2016, of employment strategies for persons with MDs; (3) Results: A total of 18 studies were included, representing 5216 participants (aged 18–65, mean age of 38.5 years old) from 7 countries. Job access programs demonstrated effectiveness in four out of six studies. Return to work (RTW) interventions showed significant positive results in two studies, while four studies did not refer to effectiveness. There were inconsistent results in another four studies; (4) Conclusions: Our findings highlight the complexities of the implementation of employment strategies (job access and return to work). Job access strategies seem to improve employment outcomes. The effectiveness of return to work strategies remains unclear. The involvement and commitment of physicians, employment specialists, and employers, and employees capacity for self-care seem decisive for employment re-integration success. Further analyses are needed to assess the cost-effectiveness of these interventions and corroborate our results, with longer follow-ups.