Search results for "REEs"
showing 10 items of 921 documents
Sensitivity of L-band vegetation optical depth to carbon stocks in tropical forests: a comparison to higher frequencies and optical indices
2019
Supplementary data to this article can be found online at https://doi.org/10.1016/j.rse.2019.111303. Monitoring vegetation carbon in tropical regions is essential to the global carbon assessment and to evaluate the actions oriented to the reduction of forest degradation. Mainly, satellite optical vegetation indices and LiDAR data have been used to this purpose. These two techniques are limited by cloud cover and are sensitive only to the top of vegetation. In addition, the vegetation attenuation to the soil microwave emission, represented by the vegetation optical depth (VOD), has been applied for biomass estimation using frequencies ranging from 4 to 30¿GHz (C- to K-bands). Atmosphere is t…
Effect of water stress on dry matter accumulation and partitioning in pot-grown olive trees (cv Leccino and Racioppella)
2013
Abstract Three different water regimes were applied on young pot-grown olive trees of the cultivars Leccino and Racioppella, amounting to 100% (treatment T100), 50% (treatment T50) and 25% (treatment T25) of water transpiration as determined by pot weight. During the two-year trial the following parameters were measured: midday stem water potential, shoots growth, total leaf area per tree, dry matter accumulation and partitioning in different parts of the plant (root, wood, leaves and fruits). Dry matter was affected by the water regime and cultivar. The cv Leccino, for T100, displayed a greater accumulation of total dry matter and fruit dry matter, while these two parameters were greatly r…
L-band vegetation optical depth seasonal metrics for crop yield assessment
2018
Attenuation of surface microwave emission due to the overlying vegetation is proportional to the density of the canopy and to its water content. The vegetation optical depth (VOD) parameter measures this attenuation. VOD could be a valuable source of information on agroecosystems, especially at lower frequencies for which greater portion of the vegetation canopy contributes to the observed brightness temperature. In the past, visible-infrared indices have been used to provide yield estimates based on measuring the photosynthetic activity from the surface canopy layer. These indices are affected by clouds and apply only in the presence of solar illumination. In this study we instead use the …
Specialization and interaction strength in a tropical plant–frugivore network differ among forest strata
2011
The degree of interdependence and potential for shared coevolutionary history of frugivorous animals and fleshy-fruited plants are contentious topics. Recently, network analyses revealed that mutualistic relationships between fleshy-fruited plants and frugivores are mostly built upon generalized associations. However, little is known about the determinants of network structure, especially from tropical forests where plants' dependence on animal seed dispersal is particularly high. Here, we present an in-depth analysis of specialization and interaction strength in a plant-frugivore network from a Kenyan rain forest. We recorded fruit removal from 33 plant species in different forest strata (…
Exposure to moderate concentrations of tropospheric ozone impairs tree stomatal response to carbon dioxide.
2011
With rising concentrations of both atmospheric carbon dioxide (CO(2)) and tropospheric ozone (O(3)), it is important to better understand the interacting effects of these two trace gases on plant physiology affecting land-atmosphere gas exchange. We investigated the effect of growth under elevated CO(2) and O(3), singly and in combination, on the primary short-term stomatal response to CO(2) concentration in paper birch at the Aspen FACE experiment. Leaves from trees grown in elevated CO(2) and/or O(3) exhibited weaker short-term responses of stomatal conductance to both an increase and a decrease in CO(2) concentration from current ambient level. The impairement of the stomatal CO(2) respo…
A Trajectory-Driven 3D Channel Model for Human Activity Recognition
2021
This paper concerns the design, analysis, and simulation of a 3D non-stationary channel model fed with inertial measurement unit (IMU) data. The work in this paper provides a framework for simulating the micro-Doppler signatures of indoor channels for human activity recognition by using radiofrequency-based sensing technologies. The major human body segments, such as wrists, ankles, torso, and head, are modelled as a cluster of moving point scatterers. We provide expressions for the time variant (TV) speed and TV angles of motion based on 3D trajectories of the moving person. Moreover, we present mathematical expressions for the TV Doppler shifts and TV path gains associated with each movin…
Modeling of biomolecular machines in non-equilibrium steady states
2021
Numerical computations have become a pillar of all modern quantitative sciences. Any computation involves modeling--even if often this step is not made explicit--and any model has to neglect details while still being physically accurate. Equilibrium statistical mechanics guides both the development of models and numerical methods for dynamics obeying detailed balance. For systems driven away from thermal equilibrium such a universal theoretical framework is missing. For a restricted class of driven systems governed by Markov dynamics and local detailed balance, stochastic thermodynamics has evolved to fill this gap and to provide fundamental constraints and guiding principles. The next step…
Improving the QM/MM Description of Chemical Processes: A Dual Level Strategy To Explore the Potential Energy Surface in Very Large Systems.
2005
Potential energy surfaces are fundamental tools for the analysis of reaction mechanisms. The accuracy of these surfaces for reactions in very large systems is often limited by the size of the system even if hybrid quantum mechanics/molecular mechanics (QM/MM) strategies are employed. The large number of degrees of freedom of the system requires hundreds or even thousands of optimization steps to reach convergence. Reactions in condensed media (such as enzymes or solutions) are thus usually restricted to be analyzed using low level quantum mechanical methods, thus introducing a source of error in the description of the QM region. In this paper, an alternative method is proposed, coupled to t…
In vivo models and decision trees for formulation development in early drug development: A review of current practices and recommendations for biopha…
2018
The ability to predict new chemical entity performance using in vivo animal models has been under investigation for more than two decades. Pharmaceutical companies use their own strategies to make decisions on the most appropriate formulation starting early in development. In this paper the biopharmaceutical decision trees available in four EFPIA partners (Bayer, Boehringer Ingelheim, Bristol Meyers Squibb and Janssen) were discussed by 7 companies of which 4 had no decision tree currently defined. The strengths, weaknesses and opportunities for improvement are discussed for each decision tree. Both pharmacokineticists and preformulation scientists at the drug discovery & development interf…
Modelling of thermo-chemical properties over the sub-solidus MgO–FeO binary, as a function of iron spin configuration, composition and temperature
2014
Thermo-chemical properties and T–X phase relations diagram of the (Mg,Fe)O solid solution are modelled using mixing Helmholtz energy, ΔF(T,x)mixing, calculated by quantum mechanical and semi-empirical techniques. The sub-solidus MgO–FeO binary has been explored as a function of composition, with iron either in high-spin (HS) or low-spin (LS) configuration. Only the HS model provides physically sound results at room pressure, yielding a correct trend of cell edge versus composition, whereas LS’s issues are at variance with observations. Mixing Helmholtz energy has been parametrized by the following relationship: ΔF(T,x)mixing = x × y × [U0(T) + U1(T) × (x – y) + U2(T) × (x − y)2]−T × S(x,y)c…