Functional evaluation and testing of a newly developed Teleost’s Fish Otolith derived biocomposite coating for healthcare

Polymers such as polycaprolactone (PCL) possess biodegradability, biocompatibility and affinity with other organic media that makes them suitable for biomedical applications. In this work, a novel biocomposite coating was synthesised by mixing PCL with layers of calcium phosphate (hydroxyapatite, brushite and monetite) from a biomineral called otolith extracted from Teleost fish (Plagioscion Squamosissimus) and multiwalled carbon nanotubes in different concentrations (0.5, 1.0 and 1.5 g/L). The biocomposite coating was deposited on an osteosynthesis material Ti6Al4V by spin coating and various tests such as Fourier transformation infrared spectroscopy (FTIR), Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), scratch tests, MTT reduction cytotoxicity, HOS cell bioactivity (human osteosarcoma) by alkaline phosphatase (ALP) and fluorescence microscopy were performed to comprehensively evaluate the newly developed biocoating. It was found that an increase in the concentration of carbon nanotube induced microstructural phase changes of calcium phosphate (CP) leading to the formation of brushite, monetite and hydroxyapatite. While we discovered that an increase in the concentration of carbon nanotube generally improves the adhesion of the coating with the substrate, a certain threshold exists such that the best deposition surfaces were obtained as PCL/CP/CNT 0.0 g/L and PCL/CP/CNT 0.5 g/L

Design of an electroflotation system for the concentration and harvesting of freshwater microalgae

Microalgae are considered as one of the most promising alternatives for the integrated use of agro-industrial water residues and the production of metabolites of high industrial interest. This is due to algae can grow on wastewater which in turn can reduce the emission of nutrients to rivers and lakes. However, the greatest scientific-technological barrier is the concentration and separation of the biomass produced. There are several processes used at different levels (from laboratory to industrial scale) such as flocculation, centrifugation, flotation, etc. These can be very expensive or can (possibly) contaminate the biomass. Unlike the previous ones, electroflotation has been proposed as a cost-efficient method, nevertheless its final efficiency will depend heavily on the type of alga and culture medium. Taking into account the above, the present project aims to design an electroflotation system for the concentration and harvest of microalgae biomass. The effect of several factors (pH, time, voltage and distance between the electrodes) and for types of materials (Copper, Aluminium, Iron and Steel) on biomass recovery efficiency from a culture of Chlorella vulgaris UTEX 1803 was evaluated by the implementation of a Design of experiments (43 non-factorial design) using STATISTICA 7.0. Results show that, the materials with higher concentration efficiency were cooper and aluminium with 40 and 80% respectively, and the most relevant factors were distance between electrodes (1-2 cm), time (>20 min) and Voltage (>15V). In order to increase the efficiency of the overall process a new 43 experimental factorial design was proposed using as factors distance between electrodes, time, voltage and agitation. Results show that agitation positively affects the total efficiency until reaching a total concentration of the biomass (100%). It was found that a voltage close to 50V and a time greater than 25 min positively affect the final efficiency of the copper and aluminium electrodes, however aluminium has the highest efficiency (> 95%) compared to copper (<85%)

Towards a global understanding of vegetation-climate dynamics at multiple timescales

Funding Information: Acknowledgements. This paper has been realized within the Earth System Data Lab project funded by the European Space Agency. The authors acknowledge Lina Fürst for initiation of the preliminary study laying the foundation for this project. The authors acknowledge support from Ulrich Weber for data management and preprocessing. Lina M. Estupinan-Suarez acknowledges the support of the DAAD and its Graduate School Scholarship Programme (57395813). Nora Linscheid acknowledges the support of the TUM Graduate School. Lina M. Estupinan-Suarez and Nora Linscheid acknowledge the continuous support of the International Max Planck Research School for Global Biogeochemical Cycles. Felix Cre-mer acknowledges the support of the German Research Foundation project HyperSense (grant no. TH 1435/4-1). Publisher Copyright: © Author(s) 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Climate variables carry signatures of variability at multiple timescales. How these modes of variability are reflected in the state of the terrestrial biosphere is still not quantified or discussed at the global scale. Here, we set out to gain a global understanding of the relevance of different modes of variability in vegetation greenness and its covariability with climate. We used > 30 years of remote sensing records of the normalized difference vegetation index (NDVI) to characterize biosphere variability across timescales from submonthly oscillations to decadal trends using discrete Fourier decomposition. Climate data of air temperature (Tair) and precipitation (Prec) were used to characterize atmosphere-biosphere covariability at each timescale. Our results show that short-term (intra-annual) and longerterm (interannual and longer) modes of variability make regionally highly important contributions to NDVI variability: short-term oscillations focus in the tropics where they shape 27% of NDVI variability. Longer-term oscillations shape 9% of NDVI variability, dominantly in semiarid shrublands. Assessing dominant timescales of vegetation-climate covariation, a natural surface classification emerges which captures patterns not represented by conventional classifications, especially in the tropics. Finally, we find that correlations between variables can differ and even invert signs across timescales. For southern Africa for example, correlation between NDVI and Tair is positive for the seasonal signal but negative for short-term and longer-term oscillations, indicating that both short- and long-term temperature anomalies can induce stress on vegetation dynamics. Such contrasting correlations between timescales exist for 15% of vegetated areas for NDVI with Tair and 27% with Prec, indicating global relevance of scale-specific climate sensitivities. Our analysis provides a detailed picture of vegetation-climate covariability globally, characterizing ecosystems by their intrinsic modes of temporal variability. We find that (i) correlations of NDVI with climate can differ between scales, (ii) nondominant subsignals in climate variables may dominate the biospheric response, and (iii) possible links may exist between short-term and longer-term scales. These heterogeneous ecosystem responses on different timescales may depend on climate zone and vegetation type, and they are to date not well understood and do not always correspond to transitions in dominant vegetation types. These scale dependencies can be a benchmark for vegetation model evaluation and for comparing remote sensing products.publishersversionpublishe

NASA SPoRT Initialization Datasets for Local Model Runs in the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can be used to initialize local model runs within the Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). These real-time datasets consist of surface-based information updated at least once per day, and produced in a composite or gridded product that is easily incorporated into the WRF EMS. The primary goal for making these NASA datasets available to the WRF EMS community is to provide timely and high-quality information at a spatial resolution comparable to that used in the local model configurations (i.e., convection-allowing scales). The current suite of SPoRT products supported in the WRF EMS include a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Greenness Vegetation Fraction (GVF) composite, and Land Information System (LIS) gridded output. The SPoRT SST composite is a blend of primarily the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer for Earth Observing System data for non-precipitation coverage over the oceans at 2-km resolution. The composite includes a special lake surface temperature analysis over the Great Lakes using contributions from the Remote Sensing Systems temperature data. The Great Lakes Environmental Research Laboratory Ice Percentage product is used to create a sea-ice mask in the SPoRT SST composite. The sea-ice mask is produced daily (in-season) at 1.8-km resolution and identifies ice percentage from 0 100% in 10% increments, with values above 90% flagged as ice

Removal of nutrients and pesticides from agricultural runoff using microalgae and cyanobacteria

The use of pesticides in agriculture has ensured the production of different crops. However, pesticides have become an emerging public health problem for Latin American countries due to their excessive use, inadequate application, toxic characteristics, and minimal residue control. The current project evaluates the ability of two strains of algae (Chlorella and Scenedesmus sp.) and one cyanobacteria (Hapalosyphon sp.) to remove excess pesticides and other nutrients present in runoff water from rice production. Different concentrations of wastewater and carbon sources (Na2CO3 and NaHCO3 ) were evaluated. According to the results, all three strains can be grown in wastewater without dilution (100%), with a biomass concentration comparable to a synthetic medium. All three strains significantly reduced the concentration of NO3 and PO4 (95 and 85%, respectively), with no difference between Na2CO3 or NaHCO3 . Finally, Chlorella sp. obtained the highest removal efficiency of the pesticide (Chlorpyrifos), followed by Scenedesmus and Hapalosyphon sp. (100, 75, and 50%, respectively). This work shows that it is possible to use this type of waste as an alternative source of nutrients to obtain biomass and metabolites of interest, such as lipids and carbohydrates, to produce biofuels

A scalable monitoring for the CMS Filter Farm based on elasticsearch

A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small documents using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured information can be queried in non-predetermined ways. The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing natural horizontal scaling. A separate central" es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters. The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2