Field-ready implementation of linear economic model predictive control for microgrid dispatch in small and medium enterprises

The increasing share of distributed renewable energy resources (DER) in the grid entails a paradigm shift in energy system operation demanding more flexibility on the prosumer side. In this work we show an implementation of linear economic model predictive control (MPC) for flexible microgrid dispatch based on time-variable electricity prices. We focus on small and medium enterprises (SME) where information and communications technology (ICT) is available on an industrial level. Our implementation uses field devices and is evaluated in a hardware-in-the-loop (HiL) test bench to achieve high technological maturity. We use available forecasting techniques for power demand and renewable energy generation and evaluate their influence on energy system operation compared to optimal operation under perfect knowledge of the future and compared to a status-quo operation strategy without control. The evaluation scenarios are based on an extensive electricity price analysis to increase representativeness of the simulation results and are based on the use of historic real-world measurements in an existing production facility. Due to real-world restrictions (imperfect forecast knowledge, implementation on field hardware, power fluctuations), between 72.2% and 85.5% of the economic optimum (rather than 100%) is reached. Together with reduced operation cost, the economic MPC implementation on field-typical industrial ICT leads to an increased share of renewable energy demand

Inferring transmission fitness advantage of SARS-CoV-2 variants of concern from wastewater samples using digital PCR, Switzerland, December 2020 through March 2021

BackgroundThroughout the COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterised by increased transmissibility, increased virulence or reduced neutralisation by antibodies obtained from prior infection or vaccination. Tracking the introduction and transmission of VOCs relies on sequencing, typically whole genome sequencing of clinical samples. Wastewater surveillance is increasingly used to track the introduction and spread of SARS-CoV-2 variants through sequencing approaches.AimHere, we adapt and apply a rapid, high-throughput method for detection and quantification of the relative frequency of two deletions characteristic of the Alpha, Beta, and Gamma VOCs in wastewater.MethodsWe developed drop-off RT-dPCR assays and an associated statistical approach implemented in the R package WWdPCR to analyse temporal dynamics of SARS-CoV-2 signature mutations (spike Δ69-70 and ORF1a Δ3675-3677) in wastewater and quantify transmission fitness advantage of the Alpha VOC.ResultsBased on analysis of Zurich wastewater samples, the estimated transmission fitness advantage of SARS-CoV-2 Alpha based on the spike Δ69-70 was 0.34 (95% confidence interval (CI): 0.30-0.39) and based on ORF1a Δ3675-3677 was 0.53 (95% CI: 0.49-0.57), aligning with the transmission fitness advantage of Alpha estimated by clinical sample sequencing in the surrounding canton of 0.49 (95% CI: 0.38-0.61).ConclusionDigital PCR assays targeting signature mutations in wastewater offer near real-time monitoring of SARS-CoV-2 VOCs and potentially earlier detection and inference on transmission fitness advantage than clinical sequencing. Keywords: B.1.1.7; SARS-CoV-2; digital PCR; drop-off assays; transmission fitness

Field-Ready Implementation of Linear Economic Model Predictive Control for Microgrid Dispatch in Small and Medium Enterprises

The increasing share of distributed renewable energy resources (DER) in the grid entails a paradigm shift in energy system operation demanding more flexibility on the prosumer side. In this work we show an implementation of linear economic model predictive control (MPC) for flexible microgrid dispatch based on time-variable electricity prices. We focus on small and medium enterprises (SME) where information and communications technology (ICT) is available on an industrial level. Our implementation uses field devices and is evaluated in a hardware-in-the-loop (HiL) test bench to achieve high technological maturity. We use available forecasting techniques for power demand and renewable energy generation and evaluate their influence on energy system operation compared to optimal operation under perfect knowledge of the future and compared to a status-quo operation strategy without control. The evaluation scenarios are based on an extensive electricity price analysis to increase representativeness of the simulation results and are based on the use of historic real-world measurements in an existing production facility. Due to real-world restrictions (imperfect forecast knowledge, implementation on field hardware, power fluctuations), between 72.2% and 85.5% of the economic optimum (rather than 100%) is reached. Together with reduced operation cost, the economic MPC implementation on field-typical industrial ICT leads to an increased share of renewable energy demand

Analyzing signaling activity and function in hematopoietic cells

Cells constantly sense their environment, allowing the adaption of cell behavior to changing needs. Fine-tuned responses to complex inputs are computed by signaling pathways, which are wired in complex connected networks. Their activity is highly context-dependent, dynamic, and heterogeneous even between closely related individual cells. Despite lots of progress, our understanding of the precise implementation, relevance, and possible manipulation of cellular signaling in health and disease therefore remains limited. Here, we discuss the requirements, potential, and limitations of the different current technologies for the analysis of hematopoietic stem and progenitor cell signaling and its effect on cell fates.ISSN:0022-1007ISSN:1540-0069ISSN:1540-953

Embryonic stem cell ERK, AKT, plus STAT3 response dynamics combinatorics are heterogeneous but NANOG state independent

Signaling is central in cell fate regulation, and relevant information is encoded in its activity over time (i.e., dynamics). However, simultaneous dynamics quantification of several pathways in single mammalian stem cells has not yet been accomplished. Here we generate mouse embryonic stem cell (ESC) lines simultaneously expressing fluorescent reporters for ERK, AKT, and STAT3 signaling activity, which all control pluripotency. We quantify their single-cell dynamics combinations in response to different self-renewal stimuli and find striking heterogeneity for all pathways, some dependent on cell cycle but not pluripotency states, even in ESC populations currently assumed to be highly homogeneous. Pathways are mostly independently regulated, but some context-dependent correlations exist. These quantifications reveal surprising single-cell heterogeneity in the important cell fate control layer of signaling dynamics combinations and raise fundamental questions about the role of signaling in (stem) cell fate control.ISSN:2213-671

NfκB signaling dynamics and their target genes differ between mouse blood cell types and induce distinct cell behavior

Cells can use signaling pathway activity over time (ie, dynamics) to control cell fates. However, little is known about the potential existence and function of signaling dynamics in primary hematopoietic stem and progenitor cells (HSPCs). Here, we use time-lapse imaging and tracking of single murine HSPCs from green fluorescent protein-p65/H2BmCherry reporter mice to quantify their nuclear factor κB (NfκB) activity dynamics in response to tumor necrosis factor α and interleukin 1β. We find response dynamics to be heterogeneous between individual cells, with cell type–specific dynamics distributions. Transcriptome sequencing of single cells physically isolated after live dynamics quantification shows activation of different target gene programs in cells with different dynamics. Finally, artificial induction of oscillatory NfκB activity causes changes in granulocyte/monocyte progenitor behavior. Thus, HSPC behavior can be influenced by signaling dynamics, which are tightly regulated during hematopoietic differentiation and enable cell type–specific responses to the same signaling inputs.ISSN:0006-4971ISSN:1528-002

Asymmetric organelle inheritance predicts human blood stem cell fate

Understanding human hematopoietic stem cell fate control is important for its improved therapeutic manipulation. Asymmetric cell division, the asymmetric inheritance of factors during division instructing future daughter cell fates, was recently described in mouse blood stem cells. In human blood stem cells, the possible existence of asymmetric cell division remained unclear because of technical challenges in its direct observation. Here, we use long-term quantitative single-cell imaging to show that lysosomes and active mitochondria are asymmetrically inherited in human blood stem cells and that their inheritance is a coordinated, nonrandom process. Furthermore, multiple additional organelles, including autophagosomes, mitophagosomes, autolysosomes, and recycling endosomes, show preferential asymmetric cosegregation with lysosomes. Importantly, asymmetric lysosomal inheritance predicts future asymmetric daughter cell-cycle length, differentiation, and stem cell marker expression, whereas asymmetric inheritance of active mitochondria correlates with daughter metabolic activity. Hence, human hematopoietic stem cell fates are regulated by asymmetric cell division, with both mechanistic evolutionary conservation and differences to the mouse system.ISSN:0006-4971ISSN:1528-002