New multifunctional isolated microinverter with integrated energy storage system for PV applications

This paper proposes a novel multifunctional isolated microinverter which is able to extract the maximum available power from a solar photovoltaic module and inject it into the power grid, while simultaneously charging a battery energy storage system (BESS). The proposed microinverter integrates a novel DC–DC power converter and a conventional DC–AC power converter. The DC–DC power converter is able to send electrical energy to the secondary side of a high-frequency transformer and to the BESS, using only two power switches. Throughout this paper, the converter topology, the operation modes, the control algorithms, and the development of a laboratory prototype of the proposed microinverter are described in detail. Moreover, simulation and experimental results are presented to demonstrate the feasibility of the proposed solution.This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&DUnits Project Scope: UIDB/00319/2020. This work has been supported by the FCT Project QUALITY4POWERPTDC/EEI-EEE/28813/2017. Luis A. M. Barros is supported by the doctoral scholarship PD/BD/143006/2018 granted by the Portuguese FCT foundation. Mohamed Tanta was supported by FCT PhD grant with a reference PD/BD/127815/2016 granted by the Portuguese FCT agency. Tiago J. C. Sousa is supported by the doctoralscholarship SFRH/BD/134353/2017 granted by the Portuguese FCT agency

Cross Species Analysis and Comparison of Tumors in Dogs and Cats, by Age, Sex, Topography and Main Morphologies. Data from Vet-OncoNet

The animal cancer burden is essential for the translational value of companion animals in comparative oncology. The present work aims to describe, analyze, and compare frequencies and associations of tumors in dogs and cats based on the Animal Cancer Registry created by Vet-OncoNet. With 9079 registries, regarding 2019 and 2020, 81% (n = 7355) belonged to dogs. In comparison, cats have a general one-year right advance in the mean age of cancer diagnosis compared to dogs. The multivariate topography group analysis shows a distinct pattern between the two species: dogs have higher odds of cancer in the genito-urinary system, spleen, soft tissue tumors and skin, while cats show higher odds for tumors in the eyes, digestive organs, nasal cavity, lymph nodes, bones and mammary glands. Regarding morphologies, dogs are overrepresented in mast cell tumors (MCT), melanomas, and hemangiosarcomas. While cats are overrepresented in fibrosarcomas, lymphomas (T and B-cell), in malignant mammary tumors, and squamous cell carcinoma (SCC). Females have greater odds only in the mammary gland, with males having greater odds in six of twelve topographies. This study is the first outcome of continuous animal cancer registration studies in Portugal

SARS-CoV-2 introductions and early dynamics of the epidemic in Portugal

Genomic surveillance of SARS-CoV-2 in Portugal was rapidly implemented by the National Institute of Health in the early stages of the COVID-19 epidemic, in collaboration with more than 50 laboratories distributed nationwide. Methods By applying recent phylodynamic models that allow integration of individual-based travel history, we reconstructed and characterized the spatio-temporal dynamics of SARSCoV-2 introductions and early dissemination in Portugal. Results We detected at least 277 independent SARS-CoV-2 introductions, mostly from European countries (namely the United Kingdom, Spain, France, Italy, and Switzerland), which were consistent with the countries with the highest connectivity with Portugal. Although most introductions were estimated to have occurred during early March 2020, it is likely that SARS-CoV-2 was silently circulating in Portugal throughout February, before the first cases were confirmed. Conclusions Here we conclude that the earlier implementation of measures could have minimized the number of introductions and subsequent virus expansion in Portugal. This study lays the foundation for genomic epidemiology of SARS-CoV-2 in Portugal, and highlights the need for systematic and geographically-representative genomic surveillance.We gratefully acknowledge to Sara Hill and Nuno Faria (University of Oxford) and Joshua Quick and Nick Loman (University of Birmingham) for kindly providing us with the initial sets of Artic Network primers for NGS; Rafael Mamede (MRamirez team, IMM, Lisbon) for developing and sharing a bioinformatics script for sequence curation (https://github.com/rfm-targa/BioinfUtils); Philippe Lemey (KU Leuven) for providing guidance on the implementation of the phylodynamic models; Joshua L. Cherry (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health) for providing guidance with the subsampling strategies; and all authors, originating and submitting laboratories who have contributed genome data on GISAID (https://www.gisaid.org/) on which part of this research is based. The opinions expressed in this article are those of the authors and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government. This study is co-funded by Fundação para a Ciência e Tecnologia and Agência de Investigação Clínica e Inovação Biomédica (234_596874175) on behalf of the Research 4 COVID-19 call. Some infrastructural resources used in this study come from the GenomePT project (POCI-01-0145-FEDER-022184), supported by COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation (POCI), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal Regional Operational Programme (CRESC Algarve2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by Fundação para a Ciência e a Tecnologia (FCT).info: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 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 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

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

Ciclos económicos: análise de 3 motores da Zona Euro: Alemanha, França e Itália

Dissertação de mestrado em Economia Monetária, Bancária e FinanceiraEste trabalho estuda a sincronia dos ciclos económicos da Alemanha, França e Itália. A sincronia dos ciclos económicos das principais economias constituintes da Zona Euro é um fator importante no desenvolvimento harmonioso e no crescimento estável e sustentado dessa área económica. Para além disso, a sincronia dos ciclos económicos é um elemento importante não só para essas economias como também para as restantes economias que pertencem à Zona Euro, pois através de diversos efeitos multiplicadores pode a robustez do seu desempenho económico ser maior ou menor de acordo com o desempenho das principais economias e serem mais ou menos afetadas pelas políticas comuns. Considerando o período 2000 – 2020, começamos por caracterizar, para cada país, os ciclos económicos e as suas fases, nomeadamente, em termos de durações e amplitudes, usando a metodologia de Harding e Pagan (2002) para a datação dos ciclos económicos. De seguida usamos o índice de concordância de séries sugerido pelos mesmos autores para determinar o grau de sincronização dos ciclos económicos das três economias em estudo. Os resultados sugerem que no período de vigência da Zona Euro, 2000-2020, a Alemanha e a França apresentam ciclos cada vez mais longos, devido a um aumento da duração das fases de expansão. Em termos de amplitudes, verifica-se também que estas são positivas e crescentes com o evoluir do tempo. Por sua vez, a Itália apresenta um comportamento diferente face à Alemanha e à França: os seus ciclos apresentam durações irregulares, não sendo estes crescentes ao longo do tempo como o padrão que se pode identificar para a Alemanha e a França e a amplitude dos seus ciclos é, em diversos ciclos identificados, negativa. Em relação à sincronia dos ciclos económicos verificamos que esta existe entre as três economias, e que o co-movimento das séries se intensificou após a crise financeira global de 2008. No entanto, os resultados obtidos com este trabalho sugerem que, apesar da sincronia das séries do PIB das três maiores economias da Zona Euro (Itália, Alemanha e França), há diferenças importantes no que diz respeito às características dos ciclos económicos de cada país – em particular, amplitudes divergentes. Assim, apesar de uma maior sincronia a convergência real entre países poderá estar em causa.This work studies the synchrony of the economic cycles of Germany, France and Italy. The synchrony of the economic cycles of the main constituent economies of the Euro Zone is an important factor in the harmonious development and stable and sustained growth of this economic area. Moreover, the synchrony of economic cycles is an important element not only for these economies but also for the other economies belonging to the Euro Zone, because through various multiplier effects the robustness of their economic performance can be greater or lesser according to the performance of the main economies and be more or less affected by common policies. Considering the period 2000 - 2020, we start by characterizing, for each country, the economic cycles and their phases, namely in terms of durations and amplitudes, using the methodology of Harding and Pagan (2002) for the dating of economic cycles. We then use the series concordance index suggested by the same authors to determine the degree of synchronization of the business cycles of the three economies under study. The results suggest that in the Euro Zone, 2000-2020, Germany and France present increasingly long cycles, due to an increase in the duration of the expansion phases. In terms of amplitudes, it can also be seen that these are positive and increasing with the evolution of time. Italy, on the other hand, presents a different behaviour compared to Germany and France: their cycles present irregular durations not being these increasing over time as the pattern that can be identified for Germany and France and the amplitude of their cycles is, in several identified cycles, negative. With regard to the synchrony of economic cycles, we find that this exists among the three economies, and that the series co-movement intensified after the global financial crisis of 2008. However, the results obtained with this work suggest that, despite the synchrony of the GDP series of the three largest economies in the Euro Zone (Italy, Germany and France), there are important differences in the characteristics of each country's economic cycles - in particular, divergent amplitudes. Thus, despite greater synchrony, real convergence between countries may be at stake