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Atypical fish diversity gradients suggest a recent formation of the Amazon system such as we know it today.

The aim of the current study was to examine effects of daily temperature variations on the performance of anaerobic digestion. Forced square-wave temperature variations (between 11 and 25, 15 and 28, and 19 and 32 degrees C) were imposed on a bench-scale digester using a mixture of llama-cow-sheep manure in a semi-continuous process. The volumetric biogas production rate, methane yield, and the volatile solid reductions were compared with the results obtained from anaerobic digestion (AD) at constant temperatures. The forced cyclic variations of temperature caused large cyclic variations in the rate of gas production and the methane content. As much as 94-97% of the daily biogas was obtained in the 12h half-cycle at high temperature. The values for volumetric biogas production rate and methane yield increased at higher temperatures. The average volumetric biogas production rate for cyclic operation between 11 and 25 degrees C was 0.22Ld(-1)L(-1) with a yield of 0.07m3CH4kg(-1) VS added (VSadd), whereas for operation between 15 and 29 degrees C the volumetric biogas production rate increased by 25% (to 0.27Ld(-1)L(-1) with a yield of 0.08m3CH4kg(-1) VSadd). In the highest temperature region a further increase of 7% in biogas production was found and the methane yield was 0.089m(3)CH(4)kg(-1) VSadd. The employed digester showed an immediate response when the temperature was elevated, which indicates a well-maintained metabolic capacity of the methanogenic bacteria during the period of low temperature. Overall, periodic temperature variations appear to give less decrease in process performance than a priori anticipated.

AbstractAimLarge tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan‐tropical model to predict plot‐level forest structure properties and biomass from only the largest trees.LocationPan‐tropical.Time periodEarly 21st century.Major taxa studiedWoody plants.MethodsUsing a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees.ResultsMeasuring the largest trees in tropical forests enables unbiased predictions of plot‐ and site‐level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium‐sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate‐diameter classes relative to other continents.Main conclusionsOur approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change.

<div class="section abstract"><div class="htmlview paragraph">This study experimentally investigates the temperature distribution and behavior of a 48V Lithium-Ion (Li-ion) battery pack during two charge-discharge cycles using 25 thermocouples. Results indicate that better convective heat transfer occurs at the external surfaces of the pack, while middle cells reach maximum temperatures. Differences are also observed in the behavior of the three modules. The discharge cycle shows a temperature rise of 5.8°?? with a pack temperature gradient increasing from 1.3°?? to 2.7°??. The study highlights the importance of assessing the thermal behavior of each module and the complexity of the Li-ion battery pack system. Findings on the battery cells, modules, and pack in the same study can provide valuable insights for designing efficient cooling systems for Li-ion battery packs.</div></div>

A Micro Hydro-Power Plant is a suitable and effective mean to provide electric power to rural remote communities without harming the environment. However, the lack of resources and technical training in these communities frequently leads to designs based of rules of thumb, compromising both the generation capacity and efficiency. This work makes an attempt to address this problem by developing a new tool to design the layout of the plants. The proposed mechanism relies on a discrete topographic survey of the terrain and utilizes a Genetic Algorithm to optimize the installation layout, making it possible to explicitly incorporate requirements and constraints, such as power supply, cost of the installation, available water flow, and layout feasibility in accordance with the real terrain profile. The algorithm can operate in both single-objective mode (cost minimization) and multi-objective mode (cost minimization and power supply maximization), including in the latter Pareto dominance analyses. The algorithm is applied to a real scenario in a remote community in Honduras, obtaining good results in terms of generation capacity and cost reduction.