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Background: Esterases (EC 3.1.1.X) are enzymes that catalyze the hydrolysis ester bonds. These enzymes have large potential for diverse applications in fine industries, particularly in pharmaceuticals, cosmetics, and bioethanol production. Methods and results: In this study, a gene encoding an esterase from Thermobifida fusca YX (TfEst) was successfully cloned, and its product was overexpressed in Escherichia coli and purified using affinity chromatography. The TfEst kinetic assay revealed catalytic efficiencies of 0.58 s−1 mM−1, 1.09 s−1 mM−1, and 0.062 s−1 mM−1 against p-Nitrophenyl acetate, p-Nitrophenyl butyrate, and 1-naphthyl acetate substrates, respectively. Furthermore, TfEst also exhibited activity in a pH range from 6.0 to 10.0, with maximum activity at pH 8.0. The enzyme demonstrated a half-life of 20 min at 70 °C. Notably, TfEst displayed acetyl xylan esterase activity as evidenced by the acetylated xylan assay. The structural prediction of TfEst using AlphaFold indicated that has an α/β-hydrolase fold, which is consistent with other esterases. Conclusions: The enzyme stability over a broad pH range and its activity at elevated temperatures make it an appealing candidate for industrial processes. Overall, TfEst emerges as a promising enzymatic tool with significant implications for the advancement of biotechnology and biofuels industries. [ABSTRACT FROM AUTHOR]

The anaerobic digestion process (AD) occurs via series of biochemical reactions, producing biogas as a renewable fuel and digestate, a rich by-product in trace elements (TEs), which has been directly disposed on soils as organic fertilizer. The application of mineral additives can result higher biogas production and CH4 yields in AD process; however, the chronical effects of these additives in digestates have not been reported in the literature. In this way, this research aims to analyze the chronic effects of digestates from swine manure (SD) and swine manure with iron ore tailings as additive (SDIOT) on survival and reproduction of Enchytraeus crypticus. The fresh samples were collected from sequential batch processes conducted at mesophilic conditions. The TEs and pH ranges in feedstock and digestates were determined in fresh matter (mg L−1), including analyses of heavy metals and nutrients, in which ranges concentrations were discussed according to biogas and CH4 productions, and compared with previous data of literature. These analyses were followed by chronic tests of digestates on reproduction of E. crypticus in Oxisols, in which tests performance met the validity criteria stablished according to ISO 16387 standard. The means of treatments were compared using the Holm–Sidak method, and the means of control groups were compared using t test (α = 0.05). The chronic effect on survival and reproduction of organisms might have occurred through synergistic effect of metals in digestates; however, more analyses must be needed to understand the toxicity effect of these products, specially under different climate conditions. Article Highlights: The application of swine manure resulted in a chronic effect to Enchytraeus crypticus. The synergistic effect of metals might have effects on organisms survival. Available fractions of metals and chemical properties of soils must also be evaluated. Climate change might influence on the speciation of metals within the soils. [ABSTRACT FROM AUTHOR]

Current applications of Graph Neural Networks in citywide short-term crash risk prediction have been limited by a gridded representation of space, which restricts the network's capability to effectively capture the spatial and temporal dependency of crash occurrences. In addition, a grided representation does not match most geographic units used for administrative purposes, limiting the use of crash risk predictions by practitioners. This paper applies a gated localised diffusion graph neural network (GLDNet) model to compare the use of two alternative geographic units, Mesh Block (MB) and grid, to forecast locations where crashes are likely to occur in a future time window. The GLDNet relies on a graph-based representation of geographic units and a weighted loss function to address the sparsity of crash occurrences. The tests are performed using crash data from the City of Melbourne, Australia, over a period of one year. The predictions are made at six-hour intervals, and the results show that the GLDNet consistently outperforms baseline methods, with differences in prediction accuracy from 10% to 21% in relation to historical average and benchmark deep learning models. In terms of geographic units, the MB-based GLDNet performed better than its grid counterpart, with differences in prediction accuracy of up to 12.3%. The better performance stems from the underlying information attached to the MB units (i.e., land use) and the network properties (i.e., degree of centrality), which enhance the GLDNet capability to identify crash risk in both central and peripherical areas. Regarding its applicability, the MB-based GLDNet directly integrates with other data sources, which provides contextual information about crash hotspots that helps decision-makers develop police patrolling and rescuing strategies. [ABSTRACT FROM AUTHOR]

This paper explores collaborative spatial data as an alternative data source for hydrodynamic model calibration, specifically concerning flood risk mapping. This study is motivated by the multiple uncertainties in the modeling process, especially in the relevant calibration and validation stages. Furthermore, information shared collaboratively can play a fundamental role when data are scarce, which is a usual modeling limitation. This paper tackled aspects like developing a collaborative platform (a mobile app) to collect flood marks; identifying strategies to motivate and engage potential collaborators; developing tools to analyze data consistency; and assessing the capability and restrictions in collaborative information use. Results validate the hypothesis that collaborative spatial data can be an alternative in hydrodynamic model calibration. Developing mechanisms to assess data consistency was crucial for achieving a good performance in the results, as simulations using collaborative data presented errors (RMSE) below 10 cm. Finally, regarding public motivation and engagement, elementary school students performed the best in data collection, highlighting the importance of direct actions, such as face-to-face workshops. Thus, the study hopes to reduce uncertainty in hydrological risk mapping, focusing specifically on observed data scarcity and its influence on model calibration and validation. [ABSTRACT FROM AUTHOR]

Spent mushroom substrate (SMS) is a promising alternative for supplementing oyster mushroom substrate, replacing conventional cereal bran. Therefore, the objective was to evaluate the production of Pleurotus ostreatus supplemented with Lentinula edodes' SMS, through the nutritional analysis of the substrate. Wheat straw was used as substrate and supplemented with rice bran (RB) or SMS in 0%, 7%,15% and 30%. Ca, K, Mg, Mn, Zn, Cu and Fe contents of the cultivation substrates (before and after harvest) were determined through atomic absorption spectrophotometry. Mycelial growth (cm²/day), mycelial time colonization (days), number of clusters, number of pileus, average clusters weight (g), pileus lenght (cm) and width (cm), productivity (1st, 2nd and 3rd flush) (%), biological efficiency (%) of mushrooms were evaluated. Results indicated mycelial growth was higher (0.87 cm²/day compared to the Control) when the substrate was supplemented regardless of the source. The proportions of 15% of SMS achieved the highest biological efficiency (107% − 15% SMS versus 66% - Control). The only nutrients that showed differences in absorption were Ca, K and Mn, in which substrates supplemented with SMS had greater absorption of Ca (5.37 g.kg− 1 versus 1.94 g.kg− 1 in Control) while substrates supplemented with RB absorbed more K (6.56 g.kg− 1 versus 3.74 g.kg− 1 in Control). The mineral composition of the substrate has a direct impact on the growth and yield of P. ostreatus, highlighting the potential of SMS as a alternative to traditional bran supplementation. [ABSTRACT FROM AUTHOR]

The big data concept has been gaining strength over the last few years. With the arise and dissemination of social media and high access easiness to information through applications, there is a necessity for all kinds of service providers to collect and analyze data, improving the quality of their services and products. In this regard, the relevance and coverage of this niche of study are notorious. It is not a coincidence that governments, supported by companies and startups, are investing in platforms to collect and analyze data, aiming at the better efficiency of the services provided to the citizens. Considering the aforementioned aspects, this work makes contextualization of the Big Data and ITS (Intelligent Transportation System) concepts by gathering recently published articles, from 2017 to 2021, considering a survey and case studies to demonstrate the importance of those themes in current days. Within the scope of big data applied to ITS, this study proposes a database for public transportation in the city of Campinas (Brazil), enabling its improvement according to the population demands. Finally, this study tries to present clearly and objectively the methodology employed with the maximum number of characteristics, applying statistical analyses (box-and-whisker diagrams and Pearson correlation), highlighting the limitations, and expanding the studied concepts to describe the application of an Advanced Traveler Information System (ATIS), a branch of Intelligent Transportation System (ITS), in a real situation. Therefore, besides the survey of the applied concepts, this work develops a specific case study, highlighting the identified deficiencies and proposing solutions. Future works are also contemplated to expand this study and improve the accuracy of the achieved results. [ABSTRACT FROM AUTHOR]

Developing countries demand a sewage treatment plant with low-cost processes that are viable in warm climates. The UASB (upflow anaerobic sludge blanket) associated with the trickling filter (TF) would meet this requirement. However, there is still a need for studies aimed at the use of new support media. Based on this, the use of expanded polystyrene (EPS) as a support media in TF was evaluated in this study. As a result, the TF filled with EPS presented a final effluent with quality similar to reactors filled with crushed stone or patented materials. The density of EPS (6.56 ± 0.30 kg m−3), the void ratio (61.7 ± 2.1%), and the mean surface area (201.9 ± 14.9 m2 m−3) once again demonstrate that EPS has characteristics similar to other alternative or patented materials. Therefore, we found that EPS can be another alternative material to be used in sewage treatment, and also that one could give an appropriate destination to a portion of this material, which is currently still discarded in landfills. [ABSTRACT FROM AUTHOR]

This systematic review and meta-analysis aimed at evaluating acute and chronic effects of physical exercise on IgA and IgG levels, as well as its relationship with the susceptibility to develop upper respiratory tract infections (URTI). This systematic review and meta-analysis was conducted and reported in accordance with PRISMA statement. A systematic search of PubMed, Web of Science, and EMBASE was performed in July 2020. This systematic review and meta-analysis included studies in which participants performed acute exercise or chronic physical training and were subjected to analyses of URTI incidence and concentrations of IgA and IgG. The selected studies for systematic review were divided into the following three groups: (I) trials that evaluated the effects of acute exercise in sedentary subjects, (II) trials that evaluated the effects of acute exercise in athletes/trained individuals, and (III) trials that evaluated the effects of chronic physical training on the incidence of URTI, as well as on the levels of IgA and IgG. Acute exercise increases the IgA levels in trained subjects but does not affect its levels in untrained subjects. Such increase in IgA levels induced by acute exercise is greater in trained individual that performed ultramarathon. On the other hand, chronic physical training reduces IgA levels in both trained and untrained subjects, does not change IgA levels in non-military subjects, besides from not affecting IgG levels. The present systematic review and meta-analysis indicates that acute exercise positively influences IgA levels in trained individuals, being this effect pronounced when a strenuous exercise such as ultramarathon is executed. Chronic physical training, in turn, does not affect IgG levels. [ABSTRACT FROM AUTHOR]

Key message: The species did not show a response pattern to flooding. Andira anthelmia and Vernonanthura discolor invested in plastic responses, while Guarea guidonia established a balance between integration and phenotypic plasticity. Dense ombrophilous forests are tropical phytophysiognomies that make up the vegetation mosaic of the Brazilian Atlantic Forest. These forests occur in humid regions and often contain flooded areas that impose obstacles to plant colonization. Some species such as Guarea guidonia (Meliaceae), Andira anthelmia (Fabaceae), and Vernonanthura discolor (Asteraceae) can tolerate these flooding conditions. However, little is known about the acclimatization of these species to flooding. For this reason, morphoanatomical and physiological analyses were performed on the leaves of five individuals of each species selected from a flooded and non-flooded site. The results showed that the species presented thicker leaves and higher specific leaf mass values under flooding conditions. However, it was observed that the thickening of G. guidonia and V. discolor is mainly influenced by the palisade parenchyma thickness, while in A. anthelmia thickening was more closely related to the spongy parenchyma thickness. Greater thickening of the cuticle and epidermis and greater density of stomata were also observed in the flooded site. The chlorophyll a and b and carotenoid contents were significantly lower in the flooded site. Chloroplasts exhibited higher amounts of starch grain, lipid drops, and plastoglobules in the flooded site. Regarding the quantum yield of photosystems II, only A. anthelmia showed a reduction in Fv/Fm values in the flooded site. Plasticity and phenotypic integration analyses made it possible to conclude that the acclimatization of A. anthelmia and V. discolor was mainly mediated by plastic adjustments. At the same time, G. guidonia presented greater phenotypic integration. [ABSTRACT FROM AUTHOR]

Numerous studies have recently shown the effects of global warming on worldwide and regional precipitation and temperature patterns. Despite knowing that the spatial and temporal impact of climate variability on agricultural production on different scales is substantial, few studies have addressed the effect of climate change on crop yield. This study aimed to provide information on regional trends by evaluating ETCCDMI extreme indices based on long-term (from 1970 to 2015), multi-station (57 weather stations), daily air temperature, and precipitation observations across the state of Nebraska located in the Central Great Plains, USA. We analyzed climate variability's spatial and temporal impact on agricultural production since agriculture is the most important economic sector for Nebraska. A predominant increase in mean maximum and minimum temperatures in Nebraska in the last four decades was observed with a nighttime warming trend. The extreme maximum temperatures and diurnal temperature range indices are environmental factors that negatively impact the rainfed crop production in Nebraska. As expected, the extreme precipitation events indices showed significant positive correlations with the rainfed crop yield. Further research is needed to evaluate the effect of extreme temperatures on plant growth at different phenological stages and its impact on productivity. [ABSTRACT FROM AUTHOR]

The Pantanal faced an unprecedented drought event in 2020. The hydrological year ended in July, 2020 had an annual average rainfall 26 % lower than the average from 1982 to 2020. Consequently, catastrophic wildfires burned out of control. Active fires during this year have also increased, and were 123 % higher than the 2002–2020 Pantanal's average. Approximately 95 % of these active fires occurred in natural land covers with 28 % of them occurring in areas classified as wetlands that likely dried out due to the drought. Therefore, the development of a special policy is needed to minimize the impact of this crisis on the biodiversity, conservation, and traditional people of the Pantanal. [ABSTRACT FROM AUTHOR]

The Amazon region of Brazil is a vitally important region for water and carbon cycling both for the region and the globe. This region is experiencing the impacts of global climate change as well as local land cover changes. Here, we investigated water and carbon estimates and related remotely sensed variables from both MODIS satellite and the Noah-MP land surface model for 3 years (2015–2017) in the state of Mato Grosso, Brazil. Land surface temperature agrees well between MODIS and the model, while the leaf area index (LAI) is higher in the model simulations. The monthly evapotranspiration (ET) from MODIS (MOD16A2) and gross primary productivity (GPP, MOD17A2) were lower than, but well correlated with, the model simulations. A noticeable exception was in the Broadleaf Forest class, which accounts for approximately 50% of the land cover in the state, where the modeled LAI was out of phase with the satellite observations, resulting in significantly poorer performance in the water and carbon fluxes for that land cover class. In addition, we investigated the sensitivity of the ET and GPP to precipitation forcing. The modeled ET relationships show correlations of approximately 0.6 for all classes (Broadleaf Forest being the exception, 0.24), while the MODIS shows reduced values averaging about 0.5 (Broadleaf Forest = 0.03). The slopes of the relationships illustrated the same sensitivity between MODIS and Noah-MP with the exception of Grasslands and Open Shrublands. The GPP relationships with precipitation show lower correlations across all land cover types for both MODIS and Noah-MP, with the slopes being significantly different for the Open Shrublands and Broadleaf Forest classes. In each of these classes, the Noah-MP simulations resulted in increased sensitivity to precipitation than was observed in the MODIS products. We highlight that this comparison is essential for increasing our understanding of how these different sources estimate water and carbon cycling and can be utilized for assessing the impacts of climate and land cover change in the region. [ABSTRACT FROM AUTHOR]

Inland Marsh (IM) is a type of wetland characterized by the presence of non-woody plants as grasses, reeds or sedges, with a water surface smaller than 25% of the area. Historically, these areas have been suffering impacts related to pollution by urban, industrial and agrochemical waste, as well as drainage for agriculture. The IM delineation allows to understand the vegetation and hydrodynamic dynamics and also to monitor the degradation caused by human-induced activities. This work aimed to compare four machine learning algorithms (classification and regression tree (CART), artificial neural network (ANN), random forest (RF), and k-nearest neighbors (k-NN)) using active and passive remote sensing data in order to address the following questions: (1) which of the four machine learning methods has the greatest potential for inland marshes delineation? (2) are SAR features more important for inland marshes delineation than optical features? and (3) what are the most accurate classification parameters for inland marshes delineation? To address these questions, we used data from Sentinel 1A and Alos Palsar I (SAR) and Sentinel 2A (optical) sensors, in a geographic object-based image analysis (GEOBIA) approach. In addition, we performed a vectorization of a 1975 Brazilian Army topographic chart (first official document presenting marsh boundaries) in order to quantify the marsh area losses between 1975 and 2018 by comparing it with a Sentinel 2A image. Our results showed that the method with the highest overall accuracy was k-NN, with 98.5%. The accuracies for the RF, ANN, and CART methods were 98.3%, 96.0% and 95.5%, respectively. The four classifiers presented accuracies exceeding 95%, showing that all methods have potential for inland marsh delineation. However, we note that the classification results have a great dependence on the input layers. Regarding the importance of the features, SAR images were more important in RF and ANN models, especially in the HV, HV + VH and VH channels of the Alos Palsar I L-band satellite, while spectral indices from optical images were more important in the marshes delineation with the CART method. In addition, we found that the CART and ANN methods presented the largest variations of the overall accuracy (OA) in relation to the different parameters tested. The multi-sensor approach was critical for the high OA values found in the IM delineation (> 95%). The four machine learning methods can be accurately applied for IM delineation, acting as an important low-cost tool for monitoring and managing these environments, in the face of advances in agriculture, soil degradation and pollution of water resources due to agrochemical dumping. [ABSTRACT FROM AUTHOR]

Epoxide hydrolases (EHs) are present in all living organisms and catalyze the hydrolysis of epoxides to the corresponding vicinal diols. EH are involved in the metabolism of endogenous and exogenous epoxides, and thus have application in pharmacology and biotechnology. In this work, we describe the substrates and inhibitors selectivity of an epoxide hydrolase recently cloned from the filamentous fungus Trichoderma reesei QM9414 (TrEH). We also studied the TrEH urea-based inhibitors effects in the fungal growth. TrEH showed high activity on radioative and fluorescent surrogate and natural substrates, especially epoxides from docosahexaenoic acid. Using a fluorescent surrogate substrate, potent inhibitors of TrEH were identified. Interestingly, one of the best compounds inhibit up to 60% of T. reesei growth, indicating an endogenous role for TrEH. These data make TrEH very attractive for future studies about fungal metabolism of fatty acids and possible development of novel drugs for human diseases. [ABSTRACT FROM AUTHOR]

This study aims to assess the concentrations of size-fractioned particle mass (PM1.0, PM2.5, PM4.0, PM10) and number (PNC0.3, PNC0.5, PNC1.0, PNC2.5), bacteria, and fungi in a Materials Recycling Facility (MRF) in Brazil. The measurements were performed inside the waste processing shed (P1) and in the outdoor environment (P2) during working days in winter and spring of 2017, and summer of 2019. A total of 2,400 min of PM, 1,440 min of PNC, and 216 samples of bioaerosols were collected in the morning and afternoon. P1 has the strongest air contamination with mean values of 475.5 ± 563.7 µg m−3 for PM10, 58.6 ± 36.0 cm−3 for PNC0.3, 1,088.8 ± 825.2 colony-forming units per cubic meter (CFU m−3) for bacteria, and 2,738.3 ± 1,381.3 CFU m−3 for fungi. The indoor/outdoor ratios indicated the large influence of indoor sources due to the activities performed inside P1 that promote the generation and resuspension of pollutants. Gram-positive bacteria dominated with 58.6% of indoor samples. Overall, our results show a critical indoor air quality situation in a Brazilian MRF, which may cause several health risks for waste pickers. Finally, we call attention to the lack of occupational exposure limits for bioaerosols in industrial workplaces and mainly in MRFs. [ABSTRACT FROM AUTHOR]

Arid and semi-arid environments correspond to one-third of the Earth's terrestrial surface. In these environments, precipitation is an essential and limiting element for vegetation growth and ecosystem biomass productivity. The semi-arid region of Brazil comprises around 11.5% of the national territory, where the Caatinga biome originally composed ~ 76% of this area, with water deficit as a prominent feature, annual rainfall lower than 800 mm, temperatures ranging between 25 and 30 °C, and potential evapotranspiration higher than 2000 mm/year. Research on the dynamics of mass and heat fluxes through techniques such as eddy covariance (EC) has contributed to estimate the magnitude and seasonal patterns of turbulent exchanges between ecosystems and the atmosphere. This study was conducted in an area of dense Caatinga (DC) and another of sparse Caatinga (SC) from 2013 to 2014. It was observed that albedo (α) and net radiation (Rn) were higher in the SC compared with DC since the magnitude of incoming shortwave radiation was higher in this area. It was found that most of the Rn is converted to sensible heat flux (H), mainly during the dry period in the SC, about 50% for H and 20% for λE. The energy balance closure showed that the turbulent fluxes (H + λE) were underestimated in comparison to the available energy at the surface (Rn − G). We also observed that this discrepancy was higher in the DC area, corresponding to ~ 30%. [ABSTRACT FROM AUTHOR]