Smart Meter Synthetic Data Generator development in python using FBProphet

Data-science is a key component of modern science since it fuels AI, data analytics, etc. As the electrical grid has been modernised into a smart grid, it has also become increasingly dependent on data science to monitor and control grid activity. Realistic data is essential to evaluating the algorithm's workability but it is difficult to obtain real smart meter data due to strict privacy and security policies of many countries. Using the prophet library synthetic data sets are generated in prediction-based Synthetic Data Generator GUI. For that source CSV (real-time) file is used to generate synthetic data in CSV format depending upon the number meter and number days to be calculated. Using FB prophet, time series data can be forecast based on an additive model that integrates seasonality, yearly, weekly, and daily trends, as well as holiday effects into non-linear trends. The algorithm is most effective when there are several seasons of historical data and strong seasonal effects in the data series. FB prophet provide automated forecast for the time series data along with seasonality and trend removals

Data for: Mesoscopic Modeling of the Impact Behavior and Fragmentation of Porous Concrete

In this work, real porous concrete mixtures, which have been experimentally produced and tested, were analyzed numerically. The numerical output was also compared with experimental results

Additional file 1 of Speed dating for enzymes! Finding the perfect phosphopantetheinyl transferase partner for your polyketide synthase

Additional file 1: Table S1. This table contains the primer sequences of both the primers used for gene-amplification and the primer used for initial sanger-sequencing in fragments of around 700 bp, containing at least 50 bp overlap between each fragment. Table S2. This table contains the different plasmids utilized in the project, both the native plasmids used as expression vectors, but also plasmids purchased containing the synthetically derived codon optimized genes. Figure S1. Phylogenetic tree of the PPTases used in the present study (bold) together with 22 additional published PPTases. Bootstrap values (> 70%) from 1000 replications are indicated at the respective nodes. Figure S2. Predicted structure of sfp/ACP interaction with the CoA and Mg2+ ion highlighted by arrows. Figure S3. Production levels of bikaverin and bostrycoidin in the individual strains (relative to OD at 48 h) in the supernatant and pellets. The mean of the supernatant from BY4743::FvPPT1 was set to 100 for both compounds

Speed dating for enzymes! Finding the perfect phosphopantetheinyl transferase partner for your polyketide synthase

Abstract The biosynthetic pathways for the fungal polyketides bikaverin and bostrycoidin, from Fusarium verticillioides and Fusarium solani respectively, were reconstructed and heterologously expressed in S. cerevisiae alongside seven different phosphopantetheinyl transferases (PPTases) from a variety of origins spanning bacterial, yeast and fungal origins. In order to gauge the efficiency of the interaction between the ACP-domains of the polyketide synthases (PKS) and PPTases, each were co-expressed individually and the resulting production of target polyketides were determined after 48 h of growth. In co-expression with both biosynthetic pathways, the PPTase from Fusarium verticillioides (FvPPT1) proved most efficient at producing both bikaverin and bostrycoidin, at 1.4 mg/L and 5.9 mg/L respectively. Furthermore, the remaining PPTases showed the ability to interact with both PKS’s, except for a single PKS-PPTase combination. The results indicate that it is possible to boost the production of a target polyketide, simply by utilizing a more optimal PPTase partner, instead of the commonly used PPTases; NpgA, Gsp and Sfp, from Aspergillus nidulans, Brevibacillus brevis and Bacillus subtilis respectively

Speed dating for enzymes! Finding the perfect phosphopantetheinyl transferase partner for your polyketide synthase

Abstract The biosynthetic pathways for the fungal polyketides bikaverin and bostrycoidin, from Fusarium verticillioides and Fusarium solani respectively, were reconstructed and heterologously expressed in S. cerevisiae alongside seven different phosphopantetheinyl transferases (PPTases) from a variety of origins spanning bacterial, yeast and fungal origins. In order to gauge the efficiency of the interaction between the ACP-domains of the polyketide synthases (PKS) and PPTases, each were co-expressed individually and the resulting production of target polyketides were determined after 48 h of growth. In co-expression with both biosynthetic pathways, the PPTase from Fusarium verticillioides (FvPPT1) proved most efficient at producing both bikaverin and bostrycoidin, at 1.4 mg/L and 5.9 mg/L respectively. Furthermore, the remaining PPTases showed the ability to interact with both PKS’s, except for a single PKS-PPTase combination. The results indicate that it is possible to boost the production of a target polyketide, simply by utilizing a more optimal PPTase partner, instead of the commonly used PPTases; NpgA, Gsp and Sfp, from Aspergillus nidulans, Brevibacillus brevis and Bacillus subtilis respectively