Physical and thermal strain of firefighters according to the firefighting tactics used to suppress wildfires

The aim of this study was to analyse the physiological strain of firefighters, using heart rate (HR) and core temperature, during real wildfire suppression according to the type of attack performed (direct, indirect or mixed). Three intensity zones were established according to the HR corresponding to the ventilatory threshold (VT) and respiratory compensation threshold (RCT): zone 1, RCT. The exercise workload (training impulse (TRIMP)), the physiological strain index (PSI) and the cumulative heat strain index(CHSI) were calculated using the time spent in each zone, and the HR and core temperature, respectively. Significantly higher mean HR, time spent in Z2 and Z3 and TRIMP h(-1) were found in direct and mixed versus indirect attacks. The highest PSI and CHSI were observed in the direct attack. In conclusion, exercise strain and combined thermal strain, but not core temperature during wildfire suppression, are related to the type of attack performed. STATEMENT OF RELEVANCE: Our findings demonstrated that wildfire firefighting is associated with high physiological demands, which vary significantly depending on the tactics chosen for performing the task. These results should be kept in mind when planning programmes to improve wildland firefighters' physical fitness, which will allow improvement in their performance.     

Learning a subclass of k-quasi-Horn formulas with membership queries

Boolean formulas have been widely studied in the field of learning theory. We focus on the model of learning with queries, and study a restriction of the class of k-quasi-Horn formulas, that is, conjunctive normal form formulas where the number of unnegated literals per clause is at most k. This class is known to be as hard to learn as the general class CNF of conjunctive normal form formulas. By imposing some constraints, we define a fragment of this logic that can be learned using only membership queries. Also we prove that none of these constraints makes by itself the class learnable.     

Exploring synergies between content-based filtering and Spreading Activation techniques in knowledge-based recommender systems

Recommender systems fight information overload by selecting automatically items that match the personal preferences of each user. The so-called content-based recommenders suggest items similar to those the user liked in the past, using syntactic matching mechanisms. The rigid nature of such mechanisms leads to recommending only items that bear strong resemblance to those the user already knows. Traditional collaborative approaches face up to overspecialization by considering the preferences of other users, which causes other severe limitations. In this paper, we avoid the intrinsic pitfalls of collaborative solutions and diversify the recommendations by reasoning about the semantics of the user’s preferences. Specifically, we present a novel content-based recommendation strategy that resorts to semantic reasoning mechanisms adopted in the Semantic Web, such as Spreading Activation techniques and semantic associations. We have adopted these mechanisms to fulfill the personalization requirements of recommender systems, enabling to discover extra knowledge about the user’s preferences and leading to more accurate and diverse suggestions. Our approach is generic enough to be used in a wide variety of domains and recommender systems. The proposal has been preliminary evaluated by statistics-driven tests involving real users in the recommendation of Digital TV contents. The results reveal the users’ satisfaction regarding the accuracy and diversity of the reasoning-driven content-based recommendations.     

Persistent Scatterers Interferometry detects and measures ground subsidence in Lisbon

Results from the application of Persistent Scatterers Interferometry in Lisbon Metropolitan Area revealed two previously unknown subsiding urban areas: one (Laranjeiras) is located in the center of Lisbon; another (Vialonga) is to be found toward the North, in an industrial region crossed by Lisbon's main highway and railway lines. The two subsiding sectors are bordered by sharp velocity gradients, and the subsidence pattern appears partially delimited by mapped geologic faults. Surface geology and urbanization alone are unable to explain the phenomena. In the Vialonga area, the historical record of water pore pressure shows a clear decline of the levels (up to 65 m in 27 years), providing evidence of over-exploitation of groundwater resources. Limited information from wells drilled inside and outside the subsidence area points to a spatial correlation between the subsidence and the water pressure levels, and suggests that faults could be acting as hydraulic barriers in the aquifer system. The surface subsidence detected is probably caused by compaction of a clay-rich Oligocene-aged aquitard, led by over-exploitation of adjacent aquifers. The same Oligocene aquitard layer is present in the Laranjeiras area, immediately bellow a multi-layered sand-clay-limestone Miocene aquifer, but further work is needed to diagnose the possibility of over-exploitation of groundwater here. In this work we were able to independently confirm the PSI results, by comparing autonomous PSI results processed for the same geographical areas, and by comparing PSI with leveling and continuous GPS derived subsidence velocities, whose close match provided further ground validation of the space-borne PSI technique.     

Quantifying blood flow and wall shear stresses in the outflow tract of chick embryonic hearts

Wall shear stresses (WSS) exerted by blood flow on cardiac tissues modulate growth and development of the heart. To study the role of hemodynamic conditions on cardiac morphogenesis, here, we present a methodology that combines imaging and finite element modeling to quantify the in vivo blood flow dynamics and WSS in the cardiac outflow tract (OFT) of early chicken embryos (day 3 out of 21-day incubation period). We found a distinct blood flow field and heterogeneous distribution of WSS in the chicken embryonic heart OFT, which have physiological implications for OFT morphogenesis.     

Forecasting and visualization of wildfires in a 3D geographical information system

This paper describes a wildfire forecasting application based on a 3D virtual environment and a fire simulation engine. A novel open-source framework is presented for the development of 3D graphics applications over large geographic areas, offering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community. The application includes a remote module that allows simultaneous connections of several users for monitoring a real wildfire event. The system is able to make a realistic composition of what is really happening in the area of the wildfire with dynamic 3D objects and location of human and material resources in real time, providing a new perspective to analyze the wildfire information. The user is enabled to simulate and visualize the propagation of a fire on the terrain integrating at the same time spatial information on topography and vegetation types with weather and wind data. The application communicates with a remote web service that is in charge of the simulation task. The user may specify several parameters through a friendly interface before the application sends the information to the remote server responsible of carrying out the wildfire forecasting using the FARSITE simulation model. During the process, the server connects to different external resources to obtain up-to-date meteorological data. The client application implements a realistic 3D visualization of the fire evolution on the landscape. A Level Of Detail (LOD) strategy contributes to improve the performance of the visualization system.     

A note on the security of PAP

In this letter, we analyze the security of an RFID authentication protocol proposed by Liu and Bailey [1], called privacy and authentication protocol (PAP). We present two traceability attacks and an impersonation attack.     

Semantic-based authorization architecture for Grid

There are a few issues that still need to be covered regarding security in the Grid area. One of them is authorization where there exist good solutions to define, manage and enforce authorization policies in Grid scenarios. However, these solutions usually do not provide Grid administrators with semantic-aware components closer to the particular Grid domain and easing different administration tasks such as conflict detection or resolution. This paper defines a proposal based on Semantic Web to define, manage and enforce security policies in a Grid scenario. These policies are defined by means of semantic-aware rules which help the administrator to create higher-level definitions with more expressiveness. These rules also permit performing added-value tasks such as conflict detection and resolution, which can be of interest in medium and large scale scenarios where different administrators define the authorization rules that should be followed before accessing a resource in the Grid. The proposed solution has been also tested providing some reasonable response times in the authorization decision process.     

A model of cerebral cortex formation during fetal development using reaction-diffusion-convection equations with Turing space parameters

The cerebral cortex is a gray lamina formed by bodies of neurons covering the cerebral hemispheres, varying in thickness from 1.25 mm in the occipital lobe to 4 mm in the anterior lobe. The brain's surface is about 30 times greater that of the skull because of its many folds; such folds form the gyri, sulci and fissures and mark out areas having specific functions, divided into five lobes. Convolution formation may vary between individuals and is an important feature of brain formation; such patterns can be mathematically represented as Turing patterns. This article describes how a phenomenological model was developed by describing the formation pattern for the gyri occurring in the cerebral cortex by reaction diffusion equations with Turing space parameters. Numerical examples for simplified geometries of a brain were solved to study pattern formation. The finite element method was used for the numerical solution, in conjunction with the Newton–Raphson method. The numerical examples showed that the model can represent cerebral cortex fold formation and reproduce pathologies related to gyri formation, such as polymicrogyria and lissencephaly.     

A GPU framework for parallel segmentation of volumetric images using discrete deformable models

Despite the ability of current GPU processors to treat heavy parallel computation tasks, its use for solving medical image segmentation problems is still not fully exploited and remains challenging. A lot of difficulties may arise related to, for example, the different image modalities, noise and artifacts of source images, or the shape and appearance variability of the structures to segment. Motivated by practical problems of image segmentation in the medical field, we present in this paper a GPU framework based on explicit discrete deformable models, implemented over the NVidia CUDA architecture, aimed for the segmentation of volumetric images. The framework supports the segmentation in parallel of different volumetric structures as well as interaction during the segmentation process and real-time visualization of the intermediate results. Promising results in terms of accuracy and speed on a real segmentation experiment have demonstrated the usability of the system.