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The SARS-CoV-2 virus was first registered in Brazil by the end of February 2020. Since then, the country counts over 150000 deaths due to COVID-19 and faces a profound social and economic crisis; there is also an ongoing health catastrophe, with the majority of hospital beds in many Brazilian cities currently occupied with COVID-19 patients. Thus, a Nonlinear Model Predictive Control (NMPC) scheme used to plan appropriate social distancing measures (and relaxations) in order to mitigate the effects of this pandemic is formulated in this paper. The strategy is designed upon an adapted data-driven Susceptible–Infected–Recovered–Deceased (SIRD) model, which includes time-varying auto-regressive immunological parameters. A novel identification procedure is proposed, composed of analytical regressions, Least-Squares optimization and auto-regressive model fits. The adapted SIRD model is validated with real data and able to adequately represent the contagion curves over large forecast horizons. The NMPC strategy is designed to generate piecewise constant quarantine guidelines, which can be reassessed (relaxed/strengthened) each week. Simulation results show that the proposed NMPC technique is able to mitigate the number of infections and progressively loosen social distancing measures. With respect to a "no-control" condition, the number of deaths could be reduced in up to 30% if the proposed NMPC coordinated health policy measures are enacted. [ABSTRACT FROM AUTHOR]

American Bullfrogs, Aquarana catesbeiana, are invasive anuran species distributed worldwide. One of the adverse impacts that this species causes in native communities is as a reservoir host for pathogens and parasites. Here, we report the coinfection of two pathogenic organisms in A. catesbeiana : Ranavirus and the nematode Eustrongylides. Bullfrogs were collected in the wild in a pond close to the urban area of São Paulo, Brazil. The prevalence of both pathogens was high: 77% were infected with ranavirus with a mean viral load of 1010.3 viral copies, and 100% of the bullfrogs were infected by Eustrongylides sp. with a mean intensity of infection of 13.4 specimens per host. Four host specimens (31%) presented pathological signs that seemed to be related to the Eustrongylides sp. infection, such as internal organs adhered to each other due to high intensity and large size of the nematodes, ulcers, and raw flesh wounds caused by the nematode. The pathogenic and concomitant infections have potential zoonotic implications and raise concerns about human infection risks for Eustrongylides infection. Moreover, such infections may represent an additional level of threat to native communities through the potential shifts in patterns of parasite and pathogen transmission. Future research involving the native anuran community is essential to ascertain whether invasive bullfrogs are attenuating or exacerbating diseases such as ranavirosis and eustrongylidiosis. [Display omitted] • Invasive American Bullfrogs in Brazil are infected with ranavirus and Eustrongylides sp. • Prevalence and intensity of infection are high. • Coinfections led to severe pathologic manifestations. [ABSTRACT FROM AUTHOR]

Scholars have often applied the concept of boundary work and its conceptual progeny to explain how science, policy, and practice collaborate to introduce change into agrifood systems. However, previous studies focused primarily on specific boundary elements (i.e., boundary spanners, boundary organizations, and boundary objects) or particular innovation processes (in terms of scope or timescale) within broad transformative change. This study aims to deepen the understanding of long-term transformative processes in agri-food systems by looking at how boundary infrastructures influenced the evolution of the Brazilian pig production system from a setting in which it mainly produced pork lard for a domestic market to a setting of being integrated in global supply chains and following international standards. Mainly, we add to the extant literature by highlighting that boundary infrastructures influenced the longterm transformative process experienced by BPPS by establishing a space where science-policy-practice interactions legitimized particular visions and values and instilled responsibility and accountability to spur various joint actions in support of innovation. We also contribute to the extant literature by showing that boundary infrastructures evolution in BPPS was incremental, long-term, multi-site, and with intertwined leverage. Boundary infrastructures provide structuration to system transformation and are also (re)structured while transitions unfold. Since boundary infrastructures have a certain directionality and may become hegemonic and exclusionary, this requires sensitiveness to the need to reorient a hegemonic boundary infrastructure or create a parallel one. Our study deepens the understanding of how coordination unfolds in long-term transformative processes, a topic deemed of interest given current debates on promoting agri-food systems transformation. We argue that better awareness of boundary infrastructures in which science-policy-practice interactions occur can help guide the direction of innovation to support sustainability transitions in agri-food systems. • An expanded boundary work view is applied to analyze changes in an agri-food system. • Boundary elements in an infrastructure are highly intertwined and complementary. • Interactions between boundary infrastructure elements play a role in long-term changes. • Boundary infrastructure evolves through a 'mutual structuration process'. • Boundary infrastructure sheds light on political dynamics and inclusion and exclusion. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic (SARS-CoV-2 virus) is the global crisis of our time. The absence of mass testing and the relevant presence of asymptomatic individuals causes the available data of the COVID-19 pandemic in Brazil to be largely under-reported regarding the number of infected individuals and deaths. We develop an adapted Susceptible-Infected-Recovered (SIR) model, which explicitly incorporates the under-reporting and the response of the population to public health policies (confinement measures, widespread use of masks, etc). Large amounts of uncertainty could provide misleading predictions of the COVID-19 spread. In this paper, we discuss the role of uncertainty in these model-based predictions, which is illustrated regarding three key aspects: (i) Assuming that the number of infected individuals is under-reported, we demonstrate anticipation regarding the infection peak. Furthermore, while a model with a single class of infected individuals yields forecasts with increased peaks, a model that considers both symptomatic and asymptomatic infected individuals suggests a decrease of the peak of symptomatic cases. (ii) Considering that the actual amount of deaths is larger than what is being registered, we demonstrate an increase of the mortality rates. (iii) When we consider generally under-reported data, we demonstrate how the transmission and recovery rate model parameters change qualitatively and quantitatively. We also investigate the "the uncertainty tripod": under-reporting level in terms of cases, deaths, and the true mortality rate of the disease. We demonstrate that if two of these factors are known, the remainder can be inferred, as long as proportions are kept constant. The proposed approach allows one to determine the margins of uncertainty by assessments on the observed and true mortality rates. [ABSTRACT FROM AUTHOR]

Abstract: This article aims to investigate the introduction, sustenance and consolidation of bioethanol in Brazil. It presents an analysis of its introductory stage, from the first decades of the 20th century until the early 1970s, when, in a second stage, additional measures allowed for its consolidation and maturity, under the widely known Proalcool. The paper presents a historical reinterpretation of the policies, mechanisms and instruments adopted in both stages, aiming to highlight the economical and political links. It is concluded that the interests of the agrarian elites, operating at the political level, and the fuel supply crisis during Second World War were basic during the first stage, to sustain a productive and logistic capacity and maintain ethanol alive as an automotive fuel. It is also concluded that the launching of Proalcool represented a transition combining the interests of the sugarcane agribusiness, burdened by the drop in sugar prices, and the need to equilibrate the balance of payments due to the oil shocks of the 1970s. Ethanol supply shocks harmed its credibility and its commercial consolidation was only possible through the introduction of flex-fuel vehicles with expectations strongly relying on climate change mitigation actions. [Copyright &y& Elsevier]

• Almada River contains Na+ and Cl− above the limits established by the WHO. • Electrodialysis reversal was evaluated during 192 h in continuous mode. • Ion removal was evaluated for a range of current density values. • High recovery rate of treated water (80 %) with low concentrated generation. Water scarcity has been a cause of concern throughout the world. Brazil, home of the largest freshwater reserve in the world, is no different, as it suffers recurring problems of scarcity and the uneven distribution of water reserves. This research evaluated the Electrodialysis Reversal (EDR) process applied to the treatment of brackish water from the Almada River Basin, southern Bahia, known as the Cocoa Region, in northeast Brazil. In periods of water scarcity, marine intrusion causes high levels of salinity in rivers and freshwater wells. Water collected directly from the Almada River, with high concentrations of sodium and chloride, 661.3 mg/L 1,091.9 mg/L respectively, and electrical conductivity about 2.98 mS/cm, was treated in pilot-scale EDR equipment. The treatment reduced conductivity by 70–80 %, especially removal of sodium and chloride, found in higher concentrations than those found in higher concentrations than those established in regulations for drinking water. After EDR treatment under two different values of applied electric current, the water reached levels suitable for consumption. The system operated at 80 % water recovery rate. The power consumption calculated for each treatment was 1.06 kWh or 2.6 kW/m3 and 0.66 kWh or 1.7 kW/m3. EDR proved to be an efficient alternative to guarantee the supply of drinking water during periods of severe drought. [ABSTRACT FROM AUTHOR]

The notion of simply transfering agricultural innovation from suppliers to receivers as a strategy to improve agri-food systems globally has been strongly criticized and has raised debates in the field of agricultural technology development and innovation. Previous studies have shown that there is translational work to be done within agricultural innovation systems when technologies travel from one context to another, and they have also increasingly focused on how public research and technology institutions (PRTIs) participate in such efforts. However, previous literature has not sharpened such translation roles played by PRTIs into local innovation systems to interpret and adapt foreign agricultural technologies. This study aims to analyze translation roles played by Embrapa (a pivotal PRTI in Brazil) into the innovation system linked to Brazilian pig production. It analyses how Embrapa took part in the decontextualization and recontextualization of the pyramid model and hybrid pigs in the Brazilian setting. This study applies a qualitative research approach based on a case study method. Its primary data sources are 21 in-depth interviews with key actors involved with Brazilian pig production. Furthermore, interviewee's content was triangulated with secondary data and interpreted using our conceptual understanding as an analytical lens. Our findings add to theory on agricultural technology development and innovation systems in threefold way: 1) we show that PRTIs get involved in what we dub 'translation ecosystems' when helping to interpret and adapt imported innovations; 2) we uncover that PRTIs may present a 'translation flexibility' and perform more than a single translation role simultaneously within translation ecosystems; and 3) we propose more fine-grained translation roles (orchestrator and supporter) by observing how Embrapa contributed to translation ecosystems functioning. This study enhances previous knowledge on how PRTIs can better deal with global flows of knowledge and traveling of innovation. It also evidences that PRTIs should be highly regarded in terms of how to approach imported innovations in terms of scaling readiness as they can perform pivotal functions to assist actors who may become marginalized by innovations from abroad, by providing options that suit local contexts. [Display omitted] • Innovations go through translational processes when going to scale. • This study unravels how research institutes deal with global flows of knowledge. • Analysis of translational roles played by Embrapa in unpacking and repacking innovation. • Translation processes unfold through translation ecosystems. • Research institutes perform translation roles as supporter and orchestrator. [ABSTRACT FROM AUTHOR]

• Five precipitation datasets were evaluated on 714 basins across Brazil. • CHIRPS, MERRA-2 and IMERG excelled in hydrological simulations. • Hydrologic modelling presented KGE > 0.5 for 78 % of the catchments. • The worst hydrological performances were in the most arid hydrographic regions. • Parameter sensitivity varies with catchment climate and aridity. Satellite-based and reanalysis precipitation products are widely adopted as complementary information to in situ measurements for estimating river discharge using hydrological modelling. However, there is still a notable research gap in the literature associated with assessing the accuracy of satellite-based or reanalysis products in different tropical and sub-tropical catchments at large-sampling hydrological modelling with sensitivity analysis. We investigated the accuracy of precipitation, hydrological model performance and parameter sensitivity related to seven precipitation data sets based on satellite and reanalysis products, i.e., CHIRPS, TRMM, GLDAS, IMERG, MERRA-2, PERSIANN-CDR, and ERA5 over 714 contrasting tropical and subtropical catchments located in Brazil. We used the Génie Rural Journalier 4 (GR4J) hydrological model to simulate the hydrological processes of the different catchments with two approaches for the calibration: using measured ground-based precipitation data (approach I) or using each individual satellite/reanalysis precipitation products (approach II) to calibrate the models. The results showed that the precipitation products tend to overestimate precipitation, with the exception of ERA5 and MERRA-2. CHIRPS is the only product that produces unbiased precipitation estimates for most catchments. The model calibration using each precipitation product individually improved the hydrological model performance. CHIRPS, IMERG, and MERRA-2 showed good accuracy in terms of both, precipitation estimation and hydrological simulation performance in the calibration period. In the validation period, the best products in terms of KGE were CHIRPS, IMERG and TRMM (KGE > 0.64). The errors in precipitation products are better compensated via hydrological modelling in wet regions. The model parameter sensitivity varies according to precipitation input, climate, and catchment aridity. Overall, all seven products exhibited their worst hydrological performance in arid regions. This study helps to improve our understanding of the catchment response in tropical and subtropical regions while also providing key insights into the reliability of satellite/reanalysis rainfall products for streamflow simulation. This study is valuable in hydrometeorological applications, climate change assessment, water resources and disaster management, especially in regions with a relatively sparse density of precipitation stations. [ABSTRACT FROM AUTHOR]

Objective: To determine the accuracy of the Timed Up and Go Test (TUGT) for screening the risk of falls among community-dwelling elderly individuals. Method: This is a prospective cohort study with a randomly by lots without reposition sample stratified by proportional partition in relation to gender involving 63 community-dwelling elderly individuals. Elderly individuals who reported having Parkinson´s disease, a history of transitory ischemic attack, stroke and with a Mini Mental State Exam lower than the expected for the education level, were on a wheelchair and that reported a single fall in the previous six months were excluded. The TUGT, a mobility test, was the measure of interested and the occurrence of falls was the outcome. The performance of basic activities of daily living (ADL) and instrumental activities of daily living (IADL) was determined through the Older American Resources and Services, and the socio-demographic and clinical data were determined through the use of additional questionnaires. Receiver Operating Characteristic Curves were used to analyze the sensitivity and specificity of the TUGT. Results: Elderly individuals who fell had greater difficulties in ADL and IADL (p<0.01) and a slower performance on the TUGT (p=0.02). No differences were found in socio-demographic and clinical characteristics between fallers and non-fallers. Considering the different sensitivity and specificity, the best predictive value for discriminating elderly individuals who fell was 12.47 seconds [(RR=3.2) 95%CI: 1.3-7.7]. Conclusions: The TUGT proved to be an accurate measure for screening the risk of falls among elderly individuals. Although different from that reported in the international literature, the 12.47 second cutoff point seems to be a better predictive value for Brazilian elderly individuals. [ABSTRACT FROM AUTHOR]

This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social distancing policies in the country. The achieved results are based on data from the period between March and May of 2020, regarding the cumulative number of infections and deaths due to the SARS-CoV-2 virus. This dataset is assumably largely sub-notified due to the absence of mass testing in Brazil. Thus, the MPC is based on a SIR model which is identified using an uncertainty-weighted Least-Squares criterion. Furthermore, this model includes an additional dynamic variable that mimics the response of the population to the social distancing policies determined by the government, which affect the COVID-19 transmission rate. The proposed control method is set within a mixed-logical formalism, since the decision variable is forcefully binary (existence or the absence of social distance policy). A dwell-time constraint is included to avoid too frequent shifts between these two inputs. The achieved simulation results illustrate how such optimal control method would operate in practice, pointing out that no social distancing should be relaxed before mid August 2020. If relaxations are necessary, they should not be performed before this date and should be in small periods, no longer than 25 days. This paradigm would proceed roughly until January/2021. The results also indicate a possible second peak of infections, which has a forecast to the beginning of October. This peak can be reduced if the periods of days with relaxed social isolation measures are shortened. [ABSTRACT FROM AUTHOR]

• A Polynomial State-Space model for fish population dynamics in areas affected by the golden mussel. • Model identification validation for ten different species. • Discussion of real-life applicable control strategies with a Nonlinear Model Predictive Control framework. • Numerical simulations. The invasion of exotic species in aquatic environments is one of the several disturbance factors responsible for altering the dynamics of fish communities. The golden mussel Limnoperna fortunei was first recorded in the upper Uruguay river, Brazil, in 2012 and, since then, it has been needed to discuss and evaluate how this invasive species interferes with the dynamics of the ten most abundant fishes of this region. Literature lacks works that investigate how to model and control the effect of such kind of invasion. This paper proposes a polynomial-nonlinear state-space representation to model the dynamics of the these fish communities, whose parameters are identified with the use of Least Squares procedures, considering in loci collected data from 2007 to 2016. This work also evaluates quantitatively, by relying on simulation results, how the (sudden) presence of the golden mussel medelled with the aquatic life of the upper Uruguay river. The obtained model allows some ambitious automatic control objectives. Using a Nonlinear Model Predictive Control (NMPC) approach, an automatic controller is designed to determine how much and how often the golden mussel should be removed from the water in order for the most affected species to once again exhibit sustainable life conditions, in terms of its K Condition Factor and abundance. The NMPC strategy is synthesized considering performance constraints and piecewise-constant control trajectories. By relying on simulation results, this work elucidates how an automatic controller could be implemented as management policies established by environmental agencies to gradually restore the fish ecological balance of the upper Uruguay river, previously unsettled by an exotic invasor. [ABSTRACT FROM AUTHOR]

The Amazon is the largest river by discharge volume and one of the most biodiverse biomes in the world. Lately, there has been a rapid increase of the urban population in the region, which has been translated into a growing emission of organic contaminants such as polycyclic aromatic hydrocarbons (PAHs) into surface water bodies. This study provides the most comprehensive evaluation of the PAH contamination levels in surface waters of the Amazon basin. We investigated the occurrence and potential sources of 16 priority PAHs and characterised their risks for freshwater ecosystems. For this, we took 40 water samples from different sites along the Brazilian part of the Amazon River, including three major tributaries, and smaller rivers crossing the main urban areas. The results of this study show that PAHs are widespread contaminants in rivers of the Brazilian Amazon. The sum of the total concentration of the 16 priority PAHs reached values of 134 ng L−1 in the Amazon River, and 163 ng L−1 near densely populated areas. On the other hand, the total PAH concentration was generally lower in the monitored tributaries. In most samples, the contamination pattern was dominated by high molecular weight PAHs, suggesting a major contribution of pyrogenic sources, although petrogenic contamination was also present in some locations near urban areas. We assessed ecological risks posed by PAH mixtures using a hazard index. The results indicated that PAH contamination is not likely to pose direct toxic effects for Amazonian freshwater organisms, however continued monitoring is recommended near densely populated areas. [Display omitted] • The presence of 16 priority PAHs was investigated in Amazonian surface waters. • PAHs were found in all samples, with total concentrations up to 163 ng L−1. • Higher concentrations were found next to large urban areas. • In most samples, PAH contamination was of pyrogenic origin. • PAHs may not directly harm Amazonian freshwater ecosystems. [ABSTRACT FROM AUTHOR]

• Interviewees were highly favorable to use demand management systems. • Interviewees were more favorable to allowing load shifting than load curtailment. • QoE profiles were leveraged for several appliances focusing demand management systems. The present work delivers the results of a survey conducted in the southern region of Brazil, using a digital questionnaire that inquired about the interaction with residential demand management systems (DMSs). Demand-side management is a very important strategy that can be used to improve the stability of the energy grid acting in different time scales and control levels, as well as, flatten the demand curve. In particular, the survey addressed the interviewees' thoughts on demand management and gathered data to enable the design of Quality of Experience (QoE) based demand management policies. The investigation of QoE-aware approaches is significant as it enables the DMS to take decisions not only based on economic metrics, but also taking the discomfort caused to the users into account. The survey considered three different DM policies assuming that the loads can be sheddable, dimmerizable, or time-flexible.The number of responses guaranteed a confidence level of 95% and an error margin of 4.63%, and the content of such responses showed favorable disposition of the interviewees on allowing interventions of DMSs on their energy consumption habits as long as it reduces their expenses with energy. The data concerning discomfort caused by demand management actions on several home appliances was treated using clustering techniques and different typical user profiles were leveraged, represented by the centroid of each cluster. Those profiles can be used to deploy QoE-aware DMSs tailored for the local reality, which seem like a promising business model as smart houses become a reality. The results of this survey and their promising applicability in DMSs are presented and discussed. 1 1 The authors thank CNPq for projects 401126/2014-5, 303702/2011-7 and 305785/2015-0. [ABSTRACT FROM AUTHOR]