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AbstractThe tropical forests of the Congo Basin and Gulf of Guinea harbor some of the greatest terrestrial and aquatic biological diversity in the world. However, our knowledge of the rich biological diversity of this region and the evolutionary processes that have shaped it remains limited, as is our understanding of the capacity for species to adapt or otherwise respond to current and projected environmental change. In this regard, research efforts are needed to increase current scientific knowledge of this region's biodiversity, identify the drivers of past diversification, evaluate the potential for species to adapt to environmental change and identify key populations for future conservation. Moreover, when evolutionary research is combined with ongoing environmental monitoring efforts, it can also provide an important set of tools for assessing and mitigating the impacts of development activities. Building on a set of recommendations developed at an international workshop held in Gabon in 2011, we highlight major areas for future evolutionary research that could be directly tied to conservation priorities for the region. These research priorities are centered around five disciplinary themes: (1) documenting and discovering biodiversity; (2) identifying drivers of evolutionary diversification; (3) monitoring environmental change; (4) understanding community and ecosystem level processes; (5) investigating the ecology and epidemiology of disease from an evolutionary perspective (evolutionary epidemiology). Furthermore, we also provide an overview of the needs and priorities for biodiversity education and training in Central Africa.

Energy efficiency is a key issue for outdoor Wireless Body Area Networks (WBANs) that wireless sensor operates near or in the human body. WBAN suffered from a major problem of energy consumption. As a result, in outdoor simulation based on ZigBee S1 pro-type used as transmit and receiver model. The investigation has been carried out based on channel propagation characteristics of what used in simulation-based on ZigBee network with multiple sensing nodes, and the design can calculate the channel characteristic such as received power, path loss, path loss-free space, and path gain. The simulation enables to choose the best route to reduce energy consumption depending on the values that have been obtained. Simulation has two routes to using a multi-point route to transmit the data from patient nodes to the hospital. The power of the transmitter can be significantly reduced and effectively by using the method proposed, the method can effectively reduce the energy needed for sending the data.

Abstract Knowing the exact parameters of a turbogenerator is essential for the analysis of its operation, control, maintenance and performance. Some generator parameters may change over time. The most common changes occur due to the degradation of the magnetic characteristics of the generator. This paper points out the limitations of the on-site measurement method (IEEE Std 1110, Annex D) for calculating saturated synchronous reactances of a turbogenerator. It has been proven that the method from the standard is highly sensitive even to a small error (1–2%) in determining the unsaturated synchronous reactance along d axes. The error occurs when the impact of magnetic hysteresis is neglected and the no-load and short-circuit tests are not conducted after the over-haul of a turbogenerator. The paper proposes improvements for reducing the disadvantages of the on-site methods. Furthermore, several weaknesses of this method have been identified and the proposed corrections are detailed herewith. The improvements shown in this paper are suitable for the use in steady-state analysis of turbogenerators.

This research aims to examine the validity of the Environmental Kuznets Curve (EKC) hypothesis in 37 Organization for Economic Co-operation and Development (OECD) countries over the period from 1960 to 2019. Panel Quantile Regressions (QR) show that for the lower quartile, economic growth does not impact emissions; for the central quartile a U-shaped curve emerges; while for the upper quartile, an N-shaped curve is found. In addition, cointegrating regressions highlight that economic growth, fossil fuel consumption, and population exert a detrimental effect on the environment, while renewable energy consumption reduces carbon dioxide (CO2) emissions. These results are confirmed by panel causality tests since a feedback mechanism is found between CO2 emissions and the remaining series. Furthermore, single-country estimates provide evidence of great variability in the sample.

The viability and accuracy of large-eddy simulation (LES) with wall modeling for high Reynolds number complex turbulent flows is investigated by considering the flow around a circular cylinder in the supercritical regime. A simple wall stress model is employed to provide approximate boundary conditions to the LES. The results are compared with those obtained from steady and unsteady Reynolds-averaged Navier–Stokes (RANS) solutions and the available experimental data. The LES solutions are shown to be considerably more accurate than the RANS results. They capture correctly the delayed boundary layer separation and reduced drag coefficients consistent with experimental measurements after the drag crisis. The mean pressure distribution is predicted reasonably well at ReD=5×105 and 106. However, the Reynolds number dependence is not captured, and the solution becomes less accurate at increased Reynolds numbers.

Abstract While Germany and Japan are going through major energy reforms, natural gas consumption is taking a growing share in their energy supply. This paper adopts a Machine Learning approach to assess the causal link between natural gas consumption and economic growth for both economies. A Causal Direction from Dependency (D2C) algorithm with the interconnection of the sub-class is employed using yearly data from 1970 to 2018. The interconnections of the sub-classes are found for both economies, indicating evidence of causalities operating in both directions. In addition, the propagation over the seven eras is linear and homogeneously continue for Japan, while this effect meets a stabilization phase in the fifth era for Germany. The empirical findings claim strong support for the existence of a bidirectional causality between these variables in Germany and Japan, which is in line with the “feedback hypothesis”. Although the strength of this bidirectional relationship is clear for both economies, its time-propagation is expected to be longer for Japan. Accordingly, this study claims that the gas supply should be further strengthened to progressively replace the most polluting fuels (oil and coal) and ensure a feasible transition towards a renewable path.

Biomass associated with low upstream emissions offers cost-effective renewable arbon for negative emissions and production of chemicals, aviation and shipping fuels, reducing the need for more costly options like direct air capture. Policy support for sustainable biomass use alongside emerging technologies reduces energy system costs and the risk of missing emissions targets.

Abstract The recent increasing attention in energy production from renewable energy sources has led to photovoltaic (PV) elements, being located on greenhouse roofs. However, their assessment is almost underdeveloped in Italy. The present paper investigated the lack of a spatial database of PV greenhouses in Italy. The first aim is to detect the evolution of PV panels on the roof of greenhouses during several Energy counts (E.C.). The succeeding goal instead aims to examine the shading of PV panels of a prototype greenhouse that enables an environmentally adapting to the intrinsic characteristics. The shading on crops is one of the major limits for the PV installation on the roofs of greenhouses because it causes problems regarding the usual sequence of agricultural activity. Until now many studies applied PV panels as covering material of greenhouses concentrated on flat structures. The present study investigates tunnel greenhouses which, due to their curved shape, do not lend themselves to accommodate easily PV panels on their coverage. The shading variation was analysed inside our prototype greenhouse, by installing PV panels in a checkerboard arrangement. The transparent flexible PV panels, with dimensions of 1.116 m × 0.165 m, are manufactured using mono-crystalline silicon cells, with an efficiency of 18%, incorporated into polymers with high resistance. The difference and distribution of the shading percentage were examined regarding the surface area affected by the PV roof, the total area and the section of the greenhouse. Particularly, variations in the percentage of shading and the size of the shaded area have been observed on the twenty-first day of each month of the year. Results exposed some consistency in the shading percentage, primarily because of the curvilinear shape of the section of the greenhouse. From mid-March to mid-September, the shading was practically and constantly inside the greenhouse during the daytime; while it was partly inside and partly outside the tunnel greenhouse during the remaining months. The percentage of shading with the PV arrangement adopted never exceeds 40% during the year.