Feasibility and Environmental Sustainability of a 103.5 kWp floating Photovoltaic Electrical System with a Case Study in a Hydroelectric Power Plant, Santa Clara Hpp, Located in the South of Brazil Region

Typical environmental problems associated with the implementation of solar photovoltaic systems for the generation of peak electrical energy, on a larger scale, such as on the order of 1 MWp, is in the occupied area, usually more than 3 km2. This can be minimized by the use of water parks or water dam’s reservoir, small and large hydroelectric power plants dams. Both the terrestrial and aquatic systems can impact the site, the first one, for the need to promote earthworks, removal of extensive green areas in the surroundings, installation of new transmission line, among others; and the second, despite the fact that a flat surface is already used and that there is no need for new civil procedures for its installation and can normally take advantage of the existing power transmission line, may cause changes in the biota of the reservoir, depending on the shading areas on the surface of the lake. Due to these facts, this research was proposed to investigate, parameterize and tropicalize an electric power generation system based on floating silicon photovoltaic cell panels installed in the Santa Clara HPP reservoir, in terms of peak power, durability, aspects and environmental impacts, with the study of possible evolutionary improvements of the project such as "tracking" or solar tracking, as well as dynamism of the structure, allowing the shadow area to be shifted over time, minimizing its effects in the local biota

SmartIX: A database indexing agent based on reinforcement learning

Configuring databases for efficient querying is a complex task, often carried out by a database administrator. Solving the problem of building indexes that truly optimize database access requires a substantial amount of database and domain knowledge, the lack of which often results in wasted space and memory for irrelevant indexes, possibly jeopardizing database performance for querying and certainly degrading performance for updating. In this paper, we develop the SMARTIX architecture to solve the problem of automatically indexing a database by using reinforcement learning to optimize queries by indexing data throughout the lifetime of a database. We train and evaluate SMARTIX performance using TPC-H, a standard, and scalable database benchmark. Our empirical evaluation shows that SMARTIX converges to indexing configurations with superior performance compared to standard baselines we define and other reinforcement learning methods used in related work

Sea-level rise causes feeding habitat loss for migratory shorebirds in remote coastal wetlands of Brazilian Amazon

Funding information: We thank Iranildo Coutinho and Ricardo Pires, representatives of ICMBio at Estação Ecológica de Maracá-Jipioca and Parque Nacional do Cabo Orange, for logistical support to our fieldwork, as well as Elimarcos Sacramento and Jorgeney Figueredo, who worked as our field assistants. This research was supported by the Protected Areas in Amazonia Program—ARPA and the Marine and Coastal Protected Areas Project through financial support to ICMBio, the Petrobras Socioambiental Program (funded project ‘Projeto Aves Migratórias II—Margem Equatorial’) and the Portuguese Foundation for Science and Technology (financial support to MARE (10.54499/UIDB/04292/2020 and 10.54499/UIDP/04292/2020) and ARNET (10.54499/LA/P/0069/2020)). Publisher Copyright: © 2025 The Author(s). Published by IOP Publishing Ltd.Sea-level rise (SLR) can cause significant changes in coastal wetlands, such as the retreat of coastlines and sedimentary shifts in tidal flats. In areas lacking coastal defenses, rising sea levels are expected to drive the inland migration of coastal wetlands, generally maintaining the extent of tidal flat habitats but also triggering important ecosystem changes. Migratory shorebirds are apex predators in coastal wetlands, thus being highly sensitive to such changes. Despite the worldwide decline of this group of birds, the impacts of SLR on their habitats have not been readily evaluated. In this study, we investigated how migratory shorebirds are responding to the gradual occupation of tidal flats by areas originating from marine transgression of terrestrial habitats, which is a consequence of inland migration of coastal wetlands. We conducted aerial surveys to assess the distribution of shorebirds along 630 km of tidal flats in coastal wetlands of the Brazilian Amazon. We then mapped the distribution of tidal flats in the late 1980s and for the survey period using satellite imagery to identify the tidal areas created by marine transgression over the past four decades. Finally, we sampled these areas and nearby tidal flats to assess shorebird prey abundance and sediment characteristics. We found that shorebirds avoid transgressed areas as feeding grounds, with their numbers sharply declining with the increasing occupancy of this habitat. The dominant shorebird species, the semipalmated sandpiper (Calidris pusilla), presented densities one order of magnitude lower in transgressed areas than in other tidal flats, indicating a clear response to the reduced availability of its main prey, the crustacean Discapseudes surinamensis. We conclude that, although inland migration of coastal wetlands may preserve the extent of tidal flats over time, their increased occupation by transgressed areas can lead to significant losses in feeding habitat for migratory shorebirds.publishersversionpublishe

ACO-RR: Ant Colony Optimization Ridge Regression in Reuse of Smart City System

© 2019, Springer Nature Switzerland AG. With the rapid development of artificial intelligence, governments of different countries have been focusing on building smart cities. To build a smart city is a system construction process which not only requires a lot of human and material resources, but also takes a long period of time. Due to the lack of enough human and material resources, it is a key challenge for lots of small and medium-sized cities to develop the intelligent construction, compared with the large cities with abundant resources. Reusing the existing smart city system to assist the intelligent construction of the small and medium-sizes cities is a reasonable way to solve this challenge. Following this idea, we propose a model of Ant Colony Optimization Ridge Regression (ACO-RR), which is a smart city evaluation method based on the ridge regression. The model helps small and medium-sized cities to select and reuse the existing smart city systems according to their personalized characteristics from different successful stories. Furthermore, the proposed model tackles the limitation of ridge parameters’ selection affecting the stability and generalization ability, because the parameters of the traditional ridge regression is manually random selected. To evaluate our model performance, we conduct experiments on real-world smart city data set. The experimental results demonstrate that our model outperforms the baseline methods, such as support vector machine and neural network

Caracterização do genoma e teste de proteção vacinal para amostras do vírus da bronquite infecciosa das aves associadas a surtos ?atípicos?? da doença.

Projeto/Plano de Ação: 02.05.01.018

Agricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil.

Abstract. Knowledge of the agricultural calendar of crops is essential to better estimate and forecast the cultivation of large-scale crops. The aim of this study was to estimate sowing date (SD), date of maximum vegetative development (DMVD), and harvest date (HD) of soybean and corn in the state of Paraná, Brazil. Dates from 120 farms and the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2011 to 2014 were used into a seasonal trend analysis to obtain soybean and corn seasonal patterns. The results indicate that the majority soybean is sown during October and the DMVD occurs between the second ten-day period of December and the first ten-day period of January. Owing to the spatial variability of the SD, the difference in the maturation cycles of the cultivars, and regional climatic variation, the HD of soybean varied greatly during the studied crop years, ranging from mid-February to late March. The SD of corn is before that of soybean, and mainly occurs in late September to mid-October. The DMVD mainly occurs during December, and the HD is distributed throughout January to March in Paraná. When comparing the estimated dates with observed dates the mean error (ME) varied from 0.2 days earlier to 3.3 days after the observed date for soybean with root mean square error (RMSE) from 1.93 to 14.73 days. For corn, the ME varied from 10.3 days to 18.5 days after the observed date with RMSE from 18.02 to 27.82 days.Suplemento 1

Toxocariasis in children attending a Public Health Service Pneumology Unit in Paraná State, Brazil

The enzyme-linked immunosorbent assay (ELISA) is the most widely used tool to detect anti-Toxocara IgG antibodies for both serodiagnostic and seroepidemiological surveys on human toxocariasis. In the last eight years a high prevalence of toxocariasis (32.2-56.0%) has been reported in children attending public health units from municipalities in the state of Paraná, Brazil. Therefore, the aim of this work was to compare the frequency found among the general child population with that of children attending a public pneumology service in Maringá, Paraná, Brazil and describe the laboratorial, clinical and epidemiological findings. The research was conducted at the Consórcio Público Intermunicipal de Saúde do Setentrião Paranaense (CISAMUSEP) from July 2009 to July 2010 among children aged between one and 15 years. From a total of 167 children studied, only 4.2% (7/167) tested positive for anti-Toxocara spp. IgG antibodies and presented mild eosinophilia (2/7), increased serum IgE levels (6/7) and a positive allergy test for mites (5/7). The presence of pets (dogs or cats) at home did not correlate with the seroprevalence. In conclusion, cases of toxocariasis involving the respiratory tract are rare in children attending a public health pneumology unit in the northwestern region of Paraná State, despite the high prevalence of this type of toxocariasis among the infantile population attending Basic Health Units in the same geographical area