An Incrementally Deployed Swarm of MAVs for Localization UsingUltra-Wideband

Knowing the position of a moving target can be crucial, for example when localizing a first responder in an emergency scenario. In recent years, ultra wideband (UWB) has gained a lot of attention due to its localization accuracy. Unfortunately, UWB solutions often demand a manual setup in advance. This is tedious at best and not possible at all in environments with access restrictions (e.g., collapsed buildings). Thus, we propose a solution combining UWB with micro air vehicles (MAVs) to allow for UWB localization in a priori inaccessible environments. More precisely, MAVs equipped with UWB sensors are deployed incrementally into the environment. They localize themselves based on previously deployed MAVs and on-board odometry, before they land and enhance the UWB mesh network themselves. We tested this solution in a lab environment using a motion capture system for ground truth. Four MAVs were deployed as anchors and a fifth MAV was localized for over 80 second at a root mean square (RMS) of 0.206 m averaged over five experiments. For comparison, a setup with ideal anchor position knowledge came with 20 % lower RMS, and a setup purely based on odometry with 81 % higher RMS. The absolute scale of the error with the proposed approach is expected to be low enough for applications envisioned within the scope of this paper (e.g., the localization of a first responder) and thus considered a step towards flexible and accurate localization in a priori inaccessible, GNSS-denied environments.acceptedVersio

Buy Three to Waste One? How Real-World Purchase Data Predict Groups of Food Wasters

Approximately one-third of all food produced for human consumption is either lost or wasted. Given the central position of retailers in the supply chain, they have the potential to effectively reduce consumer food waste by implementing targeted interventions. To do so, however, they should target distinct consumer groups. In this research, we use a unique data set comprising the grocery shopping data of customers who use loyalty cards, complemented with food waste reports, to derive three distinct target groups: traditionals, time-constrained, and convenience lovers. Based on the general behavioral change literature, we discuss diverse target group-specific interventions that retailers can implement to reduce consumer food waste. Overall, we pave a research path to examine how retailers and marketing can effectively shift consumer behavior toward more sustainable food and shopping practices and assume responsibility within the food supply chain

Buy Three to Waste One? How Real-World Purchase Data Predict Groups of Food Wasters

Approximately one-third of all food produced for human consumption is either lost or wasted. Given the central position of retailers in the supply chain, they have the potential to effectively reduce consumer food waste by implementing targeted interventions. To do so, however, they should target distinct consumer groups. In this research, we use a unique data set comprising the grocery shopping data of customers who use loyalty cards, complemented with food waste reports, to derive three distinct target groups: traditionals, time-constrained, and convenience lovers. Based on the general behavioral change literature, we discuss diverse target group-specific interventions that retailers can implement to reduce consumer food waste. Overall, we pave a research path to examine how retailers and marketing can effectively shift consumer behavior toward more sustainable food and shopping practices and assume responsibility within the food supply chain

Additional file 2: of Optimization of lipid production with a genome-scale model of Yarrowia lipolytica

Script for dFBA analysis. (TXT 2 kb

Additional file 1: of Optimization of lipid production with a genome-scale model of Yarrowia lipolytica

This file contains supplemental Tables and Figures and information regarding the validation of the model, a comparison of iMK735 with other models of Y. lipolytica , data for the lipid composition as used in the biomass equation, and a list of changes leading from iND750 to iMK735. (DOCX 2878 kb

What CHO is made of: variations in the biomass composition of Chinese hamster ovary cell lines

Background: Cell line-specific, genome-scale metabolic models enable rigorous and systematic in silico investigation of cellular metabolism. Such models have recently become available for Chinese hamster ovary (CHO) cells. However, a key ingredient, namely an experimentally validated biomass function that summarizes the cellular composition, was so far missing. Here, we close this gap by providing extensive experimental data on the biomass composition of 13 parental and producer CHO cell lines under various conditions. Results: We report total protein, lipid, DNA, RNA and carbohydrate content, cell dry mass, and detailed protein and lipid composition. Furthermore, we present meticulous data on exchange rates between cells and environment and provide detailed experimental protocols on how to determine all of the above. The biomass composition is converted into cell line- and condition-specific biomass functions for use in cell line-specific, genome-scale metabolic models of CHO. Finally, flux balance analysis (FBA) is used to demonstrate consistency between in silico predictions and experimental analysis. Conclusions: Our study reveals a strong variability of the total protein content and cell dry mass across cell lines. However, the relative amino acid composition is independent of the cell line and condition and thus needs not be explicitly measured for each new cell line. In contrast, the lipid composition is strongly influenced by the growth media and thus will have to be determined in each case. These cell line-specific variations in biomass composition have a small impact on growth rate predictions with FBA, as inaccuracies in the predictions are rather dominated by inaccuracies in the exchange rate spectra. Cell-specific biomass variations only become important if the experimental errors in the exchange rate spectra drop below twenty percent