Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques

Imaging and imagination: understanding the endo-lysosomal system

Lysosomes are specialized compartments for the degradation of endocytosed and intracellular material and essential regulators of cellular homeostasis. The importance of lysosomes is illustrated by the rapidly growing number of human disorders related to a defect in lysosomal functioning. Here, we review current insights in the mechanisms of lysosome biogenesis and protein sorting within the endo-lysosomal system. We present increasing evidence for the existence of parallel pathways for the delivery of newly synthesized lysosomal proteins directly from the trans-Golgi network (TGN) to the endo-lysosomal system. These pathways are either dependent or independent of mannose 6-phosphate receptors and likely involve multiple exits for lysosomal proteins from the TGN. In addition, we discuss the different endosomal intermediates and subdomains that are involved in sorting of endocytosed cargo. Throughout our review, we highlight some examples in the literature showing how imaging, especially electron microscopy, has made major contributions to our understanding of the endo-lysosomal system today

Root System Architecture

An increasing body of evidence indicates that the engineering of root system architecture has the potential to support a second green revolution targeting crop performance under suboptimal water and nutrient supply. This chapter summarizes the recent evolution of this field and underlines important challenges to be addressed in a near future. Due to its importance for many plant functions, root system architecture has become a topic on its own in many research communities. Impressive progress has been achieved in our understanding of the developmental processes underlying root system architecture, and, in parallel, a large number of QTL studies have been reported for root architectural traits. We discuss several limitations that impede the exploitation of the genetic variability and available functional information on root system architecture in conventional breeding

Root age distribution: how does it matter in plant processes? A focus on water uptake

Aims and background Root growth creates a gradient in age at both the scale of the single root, from distal to proximal parts, but also at the root system level when young branch roots emerge from the axis or new nodal roots are emitted that may reach same soil domain as older roots. It is known that a number of root functions will vary with root type and root tissue age (e.g. respiration, exudation, ion uptake, root hydraulic conductance, mucilage release…) and so will the resulting rhizosphere properties. The impact of the distribution of root demography with depth, and related functions, on the overall functioning of the root system is fundamental for an integration of processes at the root system scale. Scope and conclusion Starting from methods for measuring root demography, we discuss the availability of data related to root age and its spatial distribution, considering plant types (monocot/dicot, perennial/annuals) which may exhibit different patterns. We then give a detailed review of variation of root/rhizosphere properties related to root age, focusing on root water uptake processes. We examine the type of response of certain properties to changes in age and whether a functional relationship can be derived. Integration of changing root properties with age intomodelling approaches is shown from 3D models at the single plant scale to approaches at the field scale based on integrated root system age. Functional structural modelling combined with new development in non-invasive imaging of roots show promises for integrating influence of age on root properties, from the local to whole root system scales. However, experimental quantification of these properties, such as hydraulic conductance variation with root age and root types, or impact of mucilage and its degradation products on rhizosphere hydraulic properties, presently lag behind the theoretical developments and increase in computational power