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composition have focused mainly on surface waters9,10,11and water-soluble organic matter in soils12,13[note: when applied to soils, the term “DOM” refers to soluble organic matter extracted in situ by pore water samplers14]. The vertical dynamics and environmental controls of DOM in mobile ...
Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spor...
The term "vector" has slightly different meanings and uses in mathematics, physics, machine learning, biology, and more. In the context of digital morphogenesis, you'll most often encounter vectors as they are used in physics, representing discrete physical properties like position, displacement, ve...
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where the exponential term is the survival function, S(d), and R is the recruitment rate (note that the time index is no longer required as time-invariant dynamics are assumed). To find the associated PDF, simply divide the numbers density by the total population size, N. The assumptions...
Throughout the paper, we use the term ‘ridesharing’ to refer to passengers (potentially) using the same vehicle at the same time, also referred to as ‘ridepooling’ (Shaheen and Cohen 2019). In this paper we do not explicitly model the drivers’ incentives. This is common in scenarios...
Its characteristics of being tolerant to drought and barren landscapes and highly adaptable make it widely suitable for reforestation. However, in the long-term management of pure forests of Pinus massoniana, the growth of a single tree species and lack of undergrowth vegetation will lead to strong...
leaf longevity8. High structural investments in leaves (high leaf mass per area) translate to slow but long-term carbon gain (high leaf longevity), while the inverse, mutually exclusive strategy is characterized by high nutrient investments (low leaf mass per area, high leaf nitrogen content per...
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,