Post-Permian tetrapod record in the Ischigualasto-Villa Unión Basin (Talampaya and Tarjados Formations, northwestern Argentina)

Talampaya and Tarjados Formations correspond to the initial stage of the Ischigualasto-Villa Unión Basin filling, and record the oldest post-Permian events in the region. The sequence consists of red beds deposited essentially by ephemeral alluvial and fluvial systems, and overlay in discordance a Permian unit (Patquía =La Colina Formation). Until present contribution, only a manus-pes pair track of a putative therapsid was reported from the Talampaya Formation, whereas fragmentary skeletal remains of dicynodonts were the only mention of tetrapods from the Tarjados Formation. Here, we disclose new material found in recent field work at the upper member of the Tarjados Formation, from the equivalent levels where dicynodont remains were previously recovered. New material includes likely footprints from tetrapod in transversal section, associated with large burrows of morphology and dimensions comparable with burrows in which small therapsid remains were found. In addition, an isolated vertebra of a medium-sized archosaur (ca. 3cm long and 4cm high) was collected. The new record improves our knowledge of the post-Permian tetrapod fauna from Argentina. Thus, during the initial stage of basin filling, two groups of tetrapods, archosaurs and therapsids were present, as part of the beginning of the post-Permian recovery. Basal archosaurs and therapsids are also known from the Early Triassic of South Africa and the Middle Triassic of Brazil, although the fossil record is comparatively scarce in the Talampaya-Tarjados faunal association.Simposio III: Ecosistemas triásicos, su paleobiología y el contexto de recuperación de la gran extinciónFacultad de Ciencias Naturales y Muse

Global Antifungal Profile Optimization of Chlorophenyl Derivatives against Botrytis cinerea and Colletotrichum gloeosporioides

Twenty-two aromatic derivatives bearing a chlorine atom and a different chain in the para or meta position were prepared and evaluated for their in vitro antifungal activity against the phytopathogenic fungi Botrytis cinerea and Colletotrichum gloeosporioides. The results showed that maximum inhibition of the growth of these fungi was exhibited for enantiomers S and R of 1-(40-chlorophenyl)- 2-phenylethanol (3 and 4). Furthermore, their antifungal activity showed a clear structure-activity relationship (SAR) trend confirming the importance of the benzyl hydroxyl group in the inhibitory mechanism of the compounds studied. Additionally, a multiobjective optimization study of the global antifungal profile of chlorophenyl derivatives was conducted in order to establish a rational strategy for the filtering of new fungicide candidates from combinatorial libraries. The MOOPDESIRE methodology was used for this purpose providing reliable ranking models that can be used later

Optimisation of reverse osmosis based wastewater treatment system for the removal of chlorophenol using genetic algorithms

YesReverse osmosis (RO) has found extensive applications in industry as an efficient separation process in comparison with thermal process. In this study, a one-dimensional distributed model based on a wastewater treatment spiral-wound RO system is developed to simulate the transport phenomena of solute and water through the membrane and describe the variation of operating parameters along the x-axis of membrane. The distributed model is tested against experimental data available in the literature derived from a chlorophenol rejection system implemented on a pilot-scale cross-flow RO filtration system with an individual spiral-wound membrane at different operating conditions. The proposed model is then used to carry out an optimisation study using a genetic algorithm (GA). The GA is developed to solve a formulated optimisation problem involving two objective functions of RO wastewater system performance. The model code is written in MATLAB, and the optimisation problem is solved using an optimisation platform written in C++. The objective function is to maximize the solute rejection at different cases of feed concentration and minimize the operating pressure to improve economic aspects. The operating feed flow rate, pressure and temperature are considered as decision variables. The optimisation problem is subjected to a number of upper and lower limits of decision variables, as recommended by the module’s manufacturer, and the constraint of the pressure loss along the membrane length to be within the allowable value. The algorithm developed has yielded a low optimisation execution time and resulted in improved unit performance based on a set of optimal operating conditions

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts