Data-Driven Control of Stochastic Systems: An Innovation Estimation Approach

Recent years have witnessed a booming interest in the data-driven paradigm for predictive control. However, under noisy data ill-conditioned solutions could occur, causing inaccurate predictions and unexpected control behaviours. In this article, we explore a new route toward data-driven control of stochastic systems through active offline learning of innovation data, which gives an answer to the critical question of how to derive an optimal data-driven model from a noise-corrupted dataset. A generalization of the Willems' fundamental lemma is developed for non-parametric representation of input-output-innovation trajectories, provided realizations of innovation are precisely known. This yields a model-agnostic unbiased output predictor and paves the way for data-driven receding horizon control, whose behaviour is identical to the ``oracle" solution of certainty-equivalent model-based control with measurable states. For efficient innovation estimation, a new low-rank subspace identification algorithm is developed. Numerical simulations show that by actively learning innovation from input-output data, remarkable improvement can be made over present formulations, thereby offering a promising framework for data-driven control of stochastic systems

Data-Driven Predictive Control Using Closed-Loop Data: An Instrumental Variable Approach

Current data-driven predictive control (DDPC) methods heavily rely on data collected in open-loop operation with elaborate design of inputs. However, due to safety or economic concerns, systems may have to be under feedback control, where only closed-loop data are available. In this context, it remains challenging to implement DDPC using closed-loop data. In this paper, we propose a new DDPC method using closed-loop data by means of instrumental variables (IVs). By drawing from closed-loop subspace identification, the use of two forms of IVs is suggested to address the closed-loop issues caused by feedback control and the correlation between inputs and noise. Furthermore, a new DDPC formulation with a novel IV-inspired regularizer is proposed, where a balance between control cost minimization and weighted least-squares data fitting can be made for improvement of control performance. Numerical examples and application to a simulated industrial furnace showcase the improved performance of the proposed DDPC based on closed-loop data.Comment: 6 pages, 7 figure

Genome-Wide Association Study on Root Traits Under Different Growing Environments in Wheat (Triticum aestivum L.)

Plant roots are critical for water and nutrient acquisition, environmental adaptation, and yield formation. Herein, 196 wheat accessions from the Huang-Huai Wheat Region of China were collected to investigate six root traits at seedling stage under three growing environments [indoor hydroponic culture (IHC), outdoor hydroponic culture (OHC), and outdoor pot culture (OPC)] and the root dry weight (RDW) under OPC at four growth stages and four yield traits in four environments. Additionally, a genome-wide association study was performed with a Wheat 660K SNP Array. The results showed that the root traits varied most under OPC, followed by those under both OHC and IHC, and root elongation under hydroponic culture was faster than that under pot culture. Root traits under OHC might help predict those under OPC. Moreover, root traits were significantly negatively correlated with grain yield (GY) and grains per spike (GPS), positively correlated with thousand-kernel weight (TKW), and weakly correlated with number of spikes per area (SPA). Twelve stable chromosomal regions associated with the root traits were detected on chromosomes 1D, 2A, 4A, 4B, 5B, 6D, and unmapped markers. Among them, a stable chromosomal interval from 737.85 to 742.00 Mb on chromosome 4A, which regulated total root length (TRL), was identified under three growing environments. Linkage disequilibrium (LD) blocks were used to identify 27 genes related to root development. Three genes TraesCS4A02G484200, TraesCS4A02G484800, TraesCS4A02G493800, and TraesCS4A02G493900, are involved in cell elongation and differentiation and expressed at high levels in root tissues. Another vital co-localization interval on chromosome 5B (397.72–410.88 Mb) was associated with not only RDW under OHC and OPC but also TKW

Efficacy of transcranial direct current stimulation for improving postoperative quality of recovery in elderly patients undergoing lower limb major arthroplasty: a randomized controlled substudy

BackgroundPrevious studies have demonstrated improvements in motor, behavioral, and emotional areas following transcranial direct current stimulation (tDCS), but no published studies have reported the efficacy of tDCS on postoperative recovery quality in patients undergoing lower limb major arthroplasty. We hypothesized that tDCS might improve postoperative recovery quality in elderly patients undergoing lower limb major arthroplasty.MethodsNinety-six patients (≥65 years) undergoing total hip arthroplasty (THA) or total knee arthroplasty (TKA) were randomized to receive 2 mA tDCS for 20 min active-tDCS or sham-tDCS. The primary outcome was the 15-item quality of recovery (QoR-15) score on postoperative day one (Т2). Secondary outcomes included the QoR-15 scores at the 2nd hour (T1), the 1st month (Т3), and the 3rd month (Т4) postoperatively, numeric rating scale scores, and fatigue severity scale scores.ResultsNinety-six elderly patients (mean age, 71 years; 68.7% woman) were analyzed. Higher QoR-15 scores were found in the active-tDCS group at T2 (123.0 [114.3, 127.0] vs. 109.0 [99.3, 115.3]; median difference, 13.0; 95% CI, 8.0 to 17.0; p < 0.001). QoR-15 scores in the active-tDCS group were higher at T1 (p < 0.001), T3 (p = 0.001), and T4 (p = 0.001). The pain scores in the active-tDCS group were lower (p < 0.001 at motion; p < 0.001 at rest). The fatigue degree scores were lower in the active-tDCS group at T1 and T2 (p < 0.001 for each).ConclusiontDCS may help improve the quality of early recovery in elderly patients undergoing lower limb major arthroplasty.Clinical trial registrationThe trial was registered at the China Clinical Trial Center (ChiCTR2200057777, https://www.chictr.org.cn/showproj.html?proj=162744)

Convergence of the 26S proteasome and the REVOLUTA pathways in regulating inflorescence and floral meristem functions in Arabidopsis

The 26S proteasome is a large multisubunit proteolytic complex, regulating growth and development in eukaryotes by selective removal of short-lived regulatory proteins. Here, it is shown that the 26S proteasome and the transcription factor gene REVOLUTA (REV) act together in maintaining inflorescence and floral meristem (IM and FM) functions. The characterization of a newly identified Arabidopsis mutant, designated ae4 (asymmetric leaves1/2 enhancer4), which carries a mutation in the gene encoding the 26S proteasome subunit, RPN2a, is reported. ae4 and rev have minor defects in phyllotaxy structure and meristem initiation, respectively, whereas ae4 rev demonstrated strong developmental defects. Compared with the rev single mutant, an increased percentage of ae4 rev plants exhibited abnormal vegetative shoot apical and axillary meristems. After flowering, ae4 rev first gave rise to a few normal-looking flowers, and then flowers with reduced numbers of all types of floral organs. In late reproductive development, instead of flowers, the ae4 rev IM produced numerous filamentous structures, which contained cells seen only in the floral organs, and then carpelloid organs. In situ hybridization revealed that expression of the WUSCHEL and CLAVATA3 genes was severely down-regulated or absent in the late appearing ae4 rev primordia, but the genes were strongly expressed in top-layer cells of inflorescence tips. Double mutant plants combining rev with other 26S proteasome subunit mutants, rpn1a and rpn9a, resembled ae4 rev, suggesting that the 26S proteasome might act as a whole in regulating IM and FM functions

Molecular characterization of ultrafine particles using extractive electrospray time-of-flight mass spectrometry

Publisher Copyright: © 2021 The Author(s).Aerosol particles negatively affect human health while also having climatic relevance due to, for example, their ability to act as cloud condensation nuclei. Ultrafine particles (diameter Dp < 100 nm) typically comprise the largest fraction of the total number concentration, however, their chemical characterization is difficult because of their low mass. Using an extractive electrospray time-of-flight mass spectrometer (EESI-TOF), we characterize the molecular composition of freshly nucleated particles from naphthalene and b-caryophyllene oxidation products at the CLOUD chamber at CERN. We perform a detailed intercomparison of the organic aerosol chemical composition measured by the EESI-TOF and an iodide adduct chemical ionization mass spectrometer equipped with a filter inlet for gases and aerosols (FIGAERO-I-CIMS). We also use an aerosol growth model based on the condensation of organic vapors to show that the chemical composition measured by the EESI-TOF is consistent with the expected condensed oxidation products. This agreement could be further improved by constraining the EESI-TOF compound-specific sensitivity or considering condensed-phase processes. Our results show that the EESI-TOF can obtain the chemical composition of particles as small as 20 nm in diameter with mass loadings as low as hundreds of ng m_3 in real time. This was until now difficult to achieve, as other online instruments are often limited by size cutoffs, ionization/thermal fragmentation and/or semicontinuous sampling. Using real-time simultaneous gas- and particle-phase data, we discuss the condensation of naphthalene oxidation products on a molecular level.Peer reviewe

High Gas-Phase Methanesulfonic Acid Production in the OH-Initiated Oxidation of Dimethyl Sulfide at Low Temperatures

Dimethyl sulfide (DMS) influences climate via cloud condensation nuclei (CCN) formation resulting from its oxidation products (mainly methanesulfonic acid, MSA, and sulfuric acid, H2SO4). Despite their importance, accurate prediction of MSA and H2SO4from DMS oxidation remains challenging. With comprehensive experiments carried out in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at CERN, we show that decreasing the temperature from +25 to -10 °C enhances the gas-phase MSA production by an order of magnitude from OH-initiated DMS oxidation, while H2SO4production is modestly affected. This leads to a gas-phase H2SO4-to-MSA ratio (H2SO4/MSA) smaller than one at low temperatures, consistent with field observations in polar regions. With an updated DMS oxidation mechanism, we find that methanesulfinic acid, CH3S(O)OH, MSIA, forms large amounts of MSA. Overall, our results reveal that MSA yields are a factor of 2-10 higher than those predicted by the widely used Master Chemical Mechanism (MCMv3.3.1), and the NOxeffect is less significant than that of temperature. Our updated mechanism explains the high MSA production rates observed in field observations, especially at low temperatures, thus, substantiating the greater importance of MSA in the natural sulfur cycle and natural CCN formation. Our mechanism will improve the interpretation of present-day and historical gas-phase H2SO4/MSA measurements

The gas-phase formation mechanism of iodic acid as an atmospheric aerosol source

Iodine is a reactive trace element in atmospheric chemistry that destroys ozone and nucleates particles. Iodine emissions have tripled since 1950 and are projected to keep increasing with rising O-3 surface concentrations. Although iodic acid (HIO3) is widespread and forms particles more efficiently than sulfuric acid, its gas-phase formation mechanism remains unresolved. Here, in CLOUD atmospheric simulation chamber experiments that generate iodine radicals at atmospherically relevant rates, we show that iodooxy hypoiodite, IOIO, is efficiently converted into HIO3 via reactions (R1) IOIO + O-3 -> IOIO4 and (R2) IOIO4 + H2O -> HIO3 + HOI + O-(1)(2). The laboratory-derived reaction rate coefficients are corroborated by theory and shown to explain field observations of daytime HIO3 in the remote lower free troposphere. The mechanism provides a missing link between iodine sources and particle formation. Because particulate iodate is readily reduced, recycling iodine back into the gas phase, our results suggest a catalytic role of iodine in aerosol formation.Peer reviewe