971 resultados para Earth-based plasters


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The new generation of artificial satellites is providing a huge amount of Earth observation images whose exploitation can report invaluable benefits, both economical and environmental. However, only a small fraction of this data volume has been analyzed, mainly due to the large human resources needed for that task. In this sense, the development of unsupervised methodologies for the analysis of these images is a priority. In this work, a new unsupervised segmentation algorithm for satellite images is proposed. This algorithm is based on the rough-set theory, and it is inspired by a previous segmentation algorithm defined in the RGB color domain. The main contributions of the new algorithm are: (i) extending the original algorithm to four spectral bands; (ii) the concept of the superpixel is used in order to define the neighborhood similarity of a pixel adapted to the local characteristics of each image; (iii) and two new region merged strategies are proposed and evaluated in order to establish the final number of regions in the segmented image. The experimental results show that the proposed approach improves the results provided by the original method when both are applied to satellite images with different spectral and spatial resolutions.

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Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite’s Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.

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Strong convective events can produce extreme precipitation, hail, lightning or gusts, potentially inducing severe socio-economic impacts. These events have a relatively small spatial extension and, in most cases, a short lifetime. In this study, a model is developed for estimating convective extreme events based on large scale conditions. It is shown that strong convective events can be characterized by a Weibull distribution of radar-based rainfall with a low shape and high scale parameter value. A radius of 90km around a station reporting a convective situation turned out to be suitable. A methodology is developed to estimate the Weibull parameters and thus the occurrence probability of convective events from large scale atmospheric instability and enhanced near-surface humidity, which are usually found on a larger scale than the convective event itself. Here, the probability for the occurrence of extreme convective events is estimated from the KO-index indicating the stability, and relative humidity at 1000hPa. Both variables are computed from ERA-Interim reanalysis. In a first version of the methodology, these two variables are applied to estimate the spatial rainfall distribution and to estimate the occurrence of a convective event. The developed method shows significant skill in estimating the occurrence of convective events as observed at synoptic stations, lightning measurements, and severe weather reports. In order to take frontal influences into account, a scheme for the detection of atmospheric fronts is implemented. While generally higher instability is found in the vicinity of fronts, the skill of this approach is largely unchanged. Additional improvements were achieved by a bias-correction and the use of ERA-Interim precipitation. The resulting estimation method is applied to the ERA-Interim period (1979-2014) to establish a ranking of estimated convective extreme events. Two strong estimated events that reveal a frontal influence are analysed in detail. As a second application, the method is applied to GCM-based decadal predictions in the period 1979-2014, which were initialized every year. It is shown that decadal predictive skill for convective event frequencies over Germany is found for the first 3-4 years after the initialization.

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In Angola, the construction made of raw earth is a cultural heritage widely used by low income households, representing over 80% of the population [1, 3]. In Huila province is evident construction in raw earth in a large scale, either in urban or in periurban and rural areas. The construction methods follow the ancestral standards, distributed throughout the region of Huila, being built by the several ethnic groups. Among the construction techniques in earth, stand out: the adobe, wattle-and-daub and more recently on CEB (Compressed Earth Block). The type of soil used to make the adobes is mainly silty-clayed sand [1]. The most applied materials are: rods, reeds, wood, grass, straw, soil and stone, almost with the same characteristics [2]. The manufacture of adobe, consists essentially in mixing clay and grass (plant fibers), then put the mixture inside a wooden mold, having a size of 42 cm long and 18 cm high and taking three to four days to dry and be applied in housing construction. The application of these materials makes the construction less expensive because they are collected, transformed and applied by the owner himself of housing without any project, based only on the result of the practice and experience acquired from their ancestors. They are simple constructions, presenting a typology of grouped and isolated single-family housing, ranging between 2 and 3 bedrooms [2]. The construction techniques used in such small housings have positive environmental aspects, both as regards the materials employed, such as the manner in which the constructions are raised, showing special concerns for the quality improvement of them, as regards the resistance, durability and comfort [4].

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Evaluating the nature of the earliest, often controversial, traces of life in the geological record (dating to the Palaeoarchaean, up to ~3.5 billion years before the present) is of fundamental relevance for placing constraints on the potential that life emerged on Mars at approximately the same time (the Noachian period). In their earliest histories, the two planets shared many palaeoenvironmental similarities, before the surface of Mars rapidly became inhospitable to life as we know it. Multi-scalar, multi-modal analyses of fossiliferous rocks from the Barberton greenstone belt of South Africa and the East Pilbara terrane of Western Australia are a window onto primitive prokaryotic ecoystems. Complementary petrographic, morphological, (bio)geochemical and nanostructural analyses of chert horizons and the carbonaceous material within using a wide range of techniques – including optical microscopy, SEM-EDS, Raman spectroscopy, PIXE, µCT, laser ablation ICP-MS, high-resolution TEM-based analytical techniques and secondary ion mass spectrometry – can characterise, at scales from macroscopic to nanoscopic, the fossilised biomes of the earliest Earth. These approaches enable the definition of the palaeoenvironments, and potentially metabolic networks, preserved in ancient rocks. Modifying these protocols is necessary for Martian exploration using rovers, since the range and power of space instrumentation is significantly reduced relative to terrestrial laboratories. Understanding the crucial observations possible using highly complementary rover-based payloads is therefore critical in scientific protocols aiming to detect traces of life on Mars.

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Chitin is the second most abundant biopolymer on Earth and the most diffused across the known species, being present in more than 70 % of them. It is present in a huge variety of different structures and morphologies being a massive pool of information for new material science approach. This thesis aims to study chitin at different level of organization using diverse approaches. Three main topics are discussed in this manuscript. The first is the use of a bottom-up approach to study chitin nanofibrils self-assembly in water triggering the assembly by pH increment. Successively, the assembly was studied in presence of another pH responsive biomacromolecule, the collagen, to get new composite materials and study how the assembly and the chitin/collagen ratio influence fibroblast’s viability. The second topic focuses on biogenic organized chitin-based matrices, in both Ariolimax californicus and Loligo vulgaris. This study aims to understand the features that give raise to the properties of those matrices. Finally, in the last section a top-up approach was used to exploit natural hierarchically organized chitinous matrices to obtain organized functional materials introducing a catechol on the free amino group of deacetylated chitin (DA 77 %). In conclusion, this study of chitin at different level of organization emphasized different novelties depending on the organization level studied. Moreover, this thesis gives many possibilities for future bioinspired routes to get highly organized materials, or for highly organized functional materials based on natural chitin-based matrices.

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Since the dawn of its presence on earth, the human being has been able to exploit the enzymes for its subsistence. More recent is the meeting between the enzymatic processes and the urgent need for technologies that aim to preserve our planet. In this field nowadays enzymatic catalysis is tested either to depollution/remediation as well as waste disposal. The work presented in this thesis, regarding both these two topics, is tailored on two European projects (EU 2020), MADFORWATER and TERMINUS respectively. Firstly, production of micro- and nanocatalysts via immobilization of laccases (a lignin-degrader enzyme) is performed. In the second part of the thesis laccase is applied to a tertiary treatment of wastewater with the aim to degrade 9 pharmaceutical active compounds in batch reactors. Despite several optimizations, poor degradation is reached and we did not proceed with the study of different bioreactor setups. Therefore, the focus is moved to a project concerning the production of smart multi-layer plastic packaging containing enzymes to improve the possibilities of recycling. In this field shielded nanocatalysts produced via coating techniques able to interact with redox mediators are investigated. The target substrate in this second project is produced in laboratory (i.e. polyurethane like compounds), starting from monomers whose degradation had already been tested, as a proof of concept. The first enzyme studied is still the laccase.

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In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.

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The study of the user scheduling problem in a Low Earth Orbit (LEO) Multi-User MIMO system is the objective of this thesis. With the application of cutting-edge digital beamforming algorithms, a LEO satellite with an antenna array and a large number of antenna elements can provide service to many user terminals (UTs) in full frequency reuse (FFR) schemes. Since the number of UTs on-ground are many more than the transmit antennas on the satellite, user scheduling is necessary. Scheduling can be accomplished by grouping users into different clusters: users within the same cluster are multiplexed and served together via Space Division Multiple Access (SDMA), i.e., digital beamforming or Multi-User MIMO techniques; the different clusters of users are then served on different time slots via Time Division Multiple Access (TDMA). The design of an optimal user grouping strategy is known to be an NP-complete problem which can be solved only through exhaustive search. In this thesis, we provide a graph-based user scheduling and feed space beamforming architecture for the downlink with the aim of reducing user inter-beam interference. The main idea is based on clustering users whose pairwise great-circle distance is as large as possible. First, we create a graph where the users represent the vertices, whereas an edge in the graph between 2 users exists if their great-circle distance is above a certain threshold. In the second step, we develop a low complex greedy user clustering technique and we iteratively search for the maximum clique in the graph, i.e., the largest fully connected subgraph in the graph. Finally, by using the 3 aforementioned power normalization techniques, a Minimum Mean Square Error (MMSE) beamforming matrix is deployed on a cluster basis. The suggested scheduling system is compared with a position-based scheduler, which generates a beam lattice on the ground and randomly selects one user per beam to form a cluster.

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Global population growth reflects how humans increasingly exploited Earth's resources. Urbanization develops along with anthropization. It is estimated that nearly 60% of the world's population lives in urban areas, which symbolize the denaturalized dimension of current modernity. Cities are artificial ecosystems that suffer most from environmental issues and climate change. The Urban Heat Island (UHI) effect is a common microclimatic phenomenon affecting cities, which causes considerable differences between urban and rural areas temperatures. Among the driving factors, the lack of vegetation in urban settlements can damage both humans and the environment (health diseases, heat waves caused deaths, biodiversity loss, and so on). As the world continues to urbanize, sustainable development increasingly depends on successful management of urban areas. To enhance cities’ resilience, Nature-based Solutions (NbSs), are defined as an umbrella concept that encompasses a wide range of ecosystem-based approaches and actions to climate change adaptation (CCA) and disaster risk reduction (DRR). This paper analyzes a 15-days study on air temperature trends carried out in Isla, a small locality in the Maltese archipelago, and proposes Nature-based Solutions-characterized scenarios to mitigate the Urban Heat Island effect the Mediterranean city is affected by. The results demonstrates how in some areas where vegetation is present, lower temperatures are recorded than in areas where vegetation is absent or scarce. It also appeared that in one location, the specific type of vegetation does not contribute to high temperature mitigation, whereas in another one, different environmental parameters can influence the measurements. Among the case-specific Nature-based Solutions proposed there are vertical greening (green wall, façades, ground based greening, etc.), tree lines, green canopy, and green roofs.

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Among the various ways of adopting the biographical approach, we used the curriculum vitaes (CVs) of Brazilian researchers who work as social scientists in health as our research material. These CVs are part of the Lattes Platform of CNPq - the National Council for Scientific and Technological Development, which includes Research and Institutional Directories. We analyzed 238 CVs for this study. The CVs contain, among other things, the following information: professional qualifications, activities and projects, academic production, participation in panels for the evaluation of theses and dissertations, research centers and laboratories and a summarized autobiography. In this work there is a brief review of the importance of autobiography for the social sciences, emphasizing the CV as a form of autobiographical practice. We highlight some results, such as it being a group consisting predominantly of women, graduates in social sciences, anthropology, sociology or political science, with postgraduate degrees. The highest concentration of social scientists is located in Brazil's southern and southeastern regions. In some institutions the main activities of social scientists are as teachers and researchers with great thematic diversity in research.

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Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.

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A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.