Adaptive Geolocation of IoT devices for Active and Assisted Living

Recent developments in IoT devices and communication systems, have brought to light new solutions capable of offering advanced sensing of the surrounding environments. On the other hand, during the last decades, the average life expectancy has increased, which translates into a considerable rise in the number of elderly people. Consequently, in view of all these factors, there is currently a constant demand for solutions to support an Active and Assisted Living (AAL) of such people. The presented thesis intends to propose a solution to help to know the location of IoT devices that may be assisting people. The proposed solution should take into consideration the risk factors of the target group at each moment, as well as the technical constraints of the device, such as its available power energy and means of communications. Thus, ultimately, a profile-based decision should autonomously be made by the device or its integrated system, in order to ensure the usage of the best geolocation technology for each situation.Desenvolvimentos recentes em dispositivos IoT e em sistemas de comunicação, trouxeram consigo novas soluções capazes de oferecer uma deteção avançada dos ambientes circundantes. Por outro lado, no decorrer das últimas décadas, a esperança média de vida aumentou, o que se traduz também num considerável aumento do número de pessoas idosas. Por conseguinte, perante o conjunto destes factores, existe actualmente uma procura constante de soluções de suporte a uma Active and Assisted Living desse grupo de pessoas. A presente tese tenciona propor uma solução que ajude a conhecer a localização dos dispositivos IoT que possam estar a ajudar pessoas. A solução proposta deve ter em consideração os fatores de risco do grupo-alvo em cada momento e também as restrições técnicas do dispositivo, como a energia disponível e os meios de comunicação. Deste modo, em última instância, uma decisão baseada num perfil deve ser tomada autonomamente pelo dispositivo ou pelo seu sistema, para garantir a utilização da tecnologia de geolocalização mais adequada em cada situação

Performance and Consistency of Indicator Groups in Two Biodiversity Hotspots

In a world limited by data availability and limited funds for conservation, scientists and practitioners must use indicator groups to define spatial conservation priorities. Several studies have evaluated the effectiveness of indicator groups, but still little is known about the consistency in performance of these groups in different regions, which would allow their a priori selection.We systematically examined the effectiveness and the consistency of nine indicator groups in representing mammal species in two top-ranked Biodiversity Hotspots (BH): the Brazilian Cerrado and the Atlantic Forest. To test for group effectiveness we first found the best sets of sites able to maximize the representation of each indicator group in the BH and then calculated the average representation of different target species by the indicator groups in the BH. We considered consistent indicator groups whose representation of target species was not statistically different between BH. We called effective those groups that outperformed the target-species representation achieved by random sets of species. Effective indicator groups required the selection of less than 2% of the BH area for representing target species. Restricted-range species were the most effective indicators for the representation of all mammal diversity as well as target species. It was also the only group with high consistency.We show that several indicator groups could be applied as shortcuts for representing mammal species in the Cerrado and the Atlantic Forest to develop conservation plans, however, only restricted-range species consistently held as the most effective indicator group for such a task. This group is of particular importance in conservation planning as it captures high diversity of endemic and endangered species

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

Ensaio de proficiência: uma poderosa ferramenta para os labotatórios nacionais

5 p. : il.O ensaio de proficiência é uma comparação interlaboratorial, que visa medir a qualidade dos resultados emitidos pelos laboratórios participantes, além de constituir uma poderosa ferramenta para avaliação das metodologias, propicia também um meio para fomentar a discussão aprofundada das limitações sempre presentes em qualquer método analítico, buscando a melhoria contínua dos procedimentos de ensaio. Neste trabalho a Divisão de Metrologia Química do Instituto Nacional de Metrologia, Normalização e Qualidade Industrial apresenta a avaliação estatística aplicada no ensaio de proficiência de cobre em solução aquosa organizado e coordenado por esta Divisão

Clay Fraction Mineralogy and Structural Soil Attributes of Two Soil Classes under the Semi-Arid Climate of Brazil

Mineralogical studies are incipient and necessary in the Apodi Plateau, Brazil. This study aimed to evaluate the interrelationship between the mineralogy of the clay fraction and its structural and chemical attributes and to differentiate two important pedo-environments in the semi-arid region of northeastern Brazil (Ferralsol and Cambisols of the Apodi Plateau-RN) using the multivariate technique. We evaluated the interrelationships between mineralogy and the structural and chemical attributes of the soil and differentiated between agroenvironments. We collected soil samples from six profiles in diagnostic horizons of the Ferralsols and Cambisols. In the mineralogical analysis of the clay fraction, X-Ray Diffraction was used to identify mineral peaks of clay and iron oxides. The physical and chemical properties of the soils were determined. The multivariate statistical technique was applied to process the data. The clay minerals identified were hematite, goethite, kaolinite, and illite. The principal component analysis allowed for the separation of environments according to soil density, Fed and Mg2+ for developed soils, and potassium, weighted average diameter, microporosity, total organic carbon, sodium, the sum of bases, calcium, total porosity, aeration, potential acidity, and Feo discriminated developing soils. This study revealed that the clay fraction influenced the structural attributes of the soil according to the degree of soil development. Two profiles presented atypical situations: High contents of crystallized iron in Cambisols and illite peaks in Ferralsolos. These mineralogical results are not commonly found in the literature, highlighting the potential for further studies. The answers concerning the mineralogy of semiarid soils in Brazil and the world show similarity