Developmental features of cotton fibre middle lamellae in relation to cell adhesion and cell detachment in cultivars with distinct fibre qualities.

Background: Cotton fibre quality traits such as fibre length, strength, and degree of maturation are determined by genotype and environment during the sequential phases of cotton fibre development (cell elongation, transition to secondary cell wall construction and cellulose deposition). The cotton fibre middle lamella (CFML) is crucial for both cell adhesion and detachment processes occurring during fibre development. To explore the relationship between fibre quality and the pace at which cotton fibres develop, a structural and compositional analysis of the CFML was carried out in several cultivars with different fibre properties belonging to four commercial species: Gossypium hirsutum, G. barbadense, G. herbaceum and G. arboreum. Results: Cotton fibre cell adhesion, through the cotton fibre middle lamella (CFML), is a developmentally regulated process determined by genotype. The CFML is composed of de-esterified homogalacturonan, xyloglucan and arabinan in all four fibre-producing cotton species: G. hirsutum, G. barbadense, G. herbaceum and G. arboreum. Conspicuous paired cell wall bulges are a feature of the CFML of two G. hirsutum cultivars from the onset of fibre cell wall detachment to the start of secondary cell wall deposition. Xyloglucan is abundant in the cell wall bulges and in later stages pectic arabinan is absent from these regions. Conclusions: The CFML of cotton fibres is re-structured during the transition phase. Paired cell wall bulges, rich in xyloglucan, are significantly more evident in the G. hirsutum cultivars than in other cotton species

Operational atmospheric and wave modelling in the California’s coastline and offshore area with applications to wave energy monitoring and assessment

The article of record as published may be found at https://doi.org/10.1080/1755876X.2017.1349640A new high-resolution operational atmospheric/wave forecasting system for the west coastline of the US, focusing especially to the California near and offshore area, is presented in this work. The new system is the result of the collaboration between two US and one European Universities. It consists of two state-of-the-art numerical prediction models (Regional Atmospheric Modeling System and WAve Model) supported by a new optimisation statistical module for the bias reduction and local adaptation of the results based on non-linear Kalman filtering and Bayesian statistics. The presented system has been evaluated against a wide number of National Data Buoy Center buoys records with very promising results. Moreover, applications to wave energy site assessment are presented revealing areas of the California coastline with increased power potential appropriate for wave power plants installation

New Efficient Optimizing Techniques for Kalman Filters and Numerical Weather Prediction Models

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools

Wave power estimation by means of spectral wave models and satellite records

The aim of this work is to study different approaches for the estimation of the energy potential of sea waves. To this end, numerical models and remote sensing, especially satellites, are utilised for the regions of North Atlantic Ocean and the Mediterranean Sea. In particular, two methods are compared: one based on the full wave spectrum and a second utilising simplified formulas based on specific wave parameters and certain approximations. Moreover, an attempt for a qualitative assessment of the wave model WAM over areas of different wave climatology is made by the comparison of relevant wave spectra. The main outcomes of this work show that simplified calculation approaches of wave energy potential overestimate the energy rate of even 10% on average, varying in the cases of shallow or deep waters. Moreover, the performance of the wave model is satisfactory resulting to small statistical errors in the calculation of wave characteristics, a fact that proves the suitability of WAM model for reliable wave energy assessment. © 2017 Institute of Marine Engineering, Science & Technology