On Reduced Input-Output Dynamic Mode Decomposition

The identification of reduced-order models from high-dimensional data is a challenging task, and even more so if the identified system should not only be suitable for a certain data set, but generally approximate the input-output behavior of the data source. In this work, we consider the input-output dynamic mode decomposition method for system identification. We compare excitation approaches for the data-driven identification process and describe an optimization-based stabilization strategy for the identified systems

Multi-Tone Microwave Locking via Real-Time Feedback

Environmental noise coupling to mechanical experiments often introduces low-frequency fluctuations to the resonators, adding noise to measurements and reducing signal to noise. To counter these fluctuations, we demonstrate a dynamic feedback system implemented by the locking of a microwave drive to the noisy cavity. A homodyne interferometer scheme monitors the cavity resonance fluctuations due to low-frequency noise, which is mitigated by frequency-modulating (FM) the microwave generator. The feedback has a bandwidth of $400$ Hz, with a reduction of cavity fluctuations by $84\%$ integrating up to a bandwidth of $2$ kHz. Moreover, the cavity resonance frequency fluctuations are reduced by $73\%$. This scheme can be scaled to enable multi-tone experiments locked to the same feedback signal. As a demonstration, we apply the feedback to an optomechanical experiment and implement a cavity-locked, multi-tone mechanical measurement. As low-frequency cavity frequency noise can be a limiting factor in many experiments, the multi-tone microwave locking technique presented here is expected to be relevant for a wide range of fields of research.Comment: 7 pages, 5 figure

an adaptive neural network model for thermal characterization of building components

Abstract Building materials are usually characterized in stationary or almost-stationary conditions and mono dimensional heat flow regime. The existing standards (such as ISO 9869 or EN ISO 6946, EN 12664, EN 12667, ISO 8302 etc), require experiments carried out in steady-state conditions, with a very fine control of the measuring parameters with the aim to apply a simple and reproducible procedure for the determination of thermal properties. However, the thermodynamic conditions that lead to a steady-state operating mode and mono dimensional flow are very difficult to obtain (in real conditions) or very expensive and time consuming (in climate chambers). In this paper the authors present the development of a method for thermal characterization of building components, inferring the steady-state conditions, when only measures in transient conditions are available. The method, based on an adaptive linear neural network (ALNN) model also could be have the potentialities to determine the thermal diffusivity from a significant transient behavior ad hoc imposed. The study targets multilayered walls homogeneous and the results are compared with the experimental data measured by a climate chamber that operate according to the standard EN 1266

Neural substrates of sensory-guided locomotor decisions in the rat superior colliculus

Deciding in which direction to move is a ubiquitous feature of animal behavior, but the neural substrates of locomotor choices are not well understood. The superior colliculus (SC) is a midbrain structure known to be important for controlling the direction of gaze, particularly when guided by visual or auditory cues, but which may play a more general role in behavior involving spatial orienting. To test this idea, we recorded and manipulated activity in the SC of freely moving rats performing an odor-guided spatial choice task. In this context, not only did a substantial majority of SC neurons encode choice direction during goal-directed locomotion, but many also predicted the upcoming choice and maintained selectivity for it after movement completion. Unilateral inactivation of SC activity profoundly altered spatial choices. These results indicate that the SC processes information necessary for spatial locomotion, suggesting a broad role for this structure in sensory-guided orienting and navigation

N1-acetylspermidine is a determinant of hair follicle stem cell fate

Stem cell differentiation is accompanied by increased mRNA translation. The rate of protein biosynthesis is influenced by the polyamines putrescine, spermidine and spermine, which are essential for cell growth and stem cell maintenance. However, the role of polyamines as endogenous effectors of stem cell fate and whether they act through translational control remains obscure. Here, we investigate the function of polyamines in stem cell fate decisions using hair follicle stem cell (HFSC) organoids. Compared to progenitor cells, HFSCs showed lower translation rates, correlating with reduced polyamine levels. Surprisingly, overall polyamine depletion decreased translation but did not affect cell fate. In contrast, specific depletion of natural polyamines mediated by spermidine/spermine N1-acetyltransferase (SSAT; also known as SAT1) activation did not reduce translation but enhanced stemness. These results suggest a translation-independent role of polyamines in cell fate regulation. Indeed, we identified N1-acetylspermidine as a determinant of cell fate that acted through increasing self-renewal, and observed elevated N1-acetylspermidine levels upon depilation-mediated HFSC proliferation and differentiation in vivo. Overall, this study delineates the diverse routes of polyamine metabolism-mediated regulation of stem cell fate decisions. This article has an associated First Person interview with the first author of the paper.Peer reviewe

Regioselective protein oxidative cleavage enabled by enzyme-like recognition of an inorganic metal oxo cluster ligand

Oxidative modifications of proteins are key to many applications in biotechnology. Metal-catalyzed oxidation reactions efficiently oxidize proteins but with low selectivity, and are highly dependent on the protein surface residues to direct the reaction. Herein, we demonstrate that discrete inorganic ligands such as polyoxometalates enable an efficient and selective protein oxidative cleavage. In the presence of ascorbate (1 mM), the Cu-substituted polyoxometalate K8[Cu2+(H2O)(α2-P2W17O61)], (CuIIWD, 0.05 mM) selectively cleave hen egg white lysozyme under physiological conditions (pH =7.5, 37 °C) producing only four bands in the gel electropherogram (12.7, 11, 10, and 5 kDa). Liquid chromatography/mass spectrometry analysis reveals a regioselective cleavage in the vicinity of crystallographic CuIIWD/lysozyme interaction sites. Mechanistically, polyoxometalate is critical to position the Cu at the protein surface and limit the generation of oxidative species to the proximity of binding sites. Ultimately, this study outlines the potential of discrete, designable metal oxo clusters as catalysts for the selective modification of proteins through radical mechanisms under non-denaturing conditions

The Ability of Soil Pore Network Metrics to Predict Redox Dynamics Is Scale Dependent

Variations in microbial community structure and metabolic efficiency are governed in part by oxygen availability, which is a function of water content, diffusion distance, and oxygen demand; for this reason, the volume, connectivity, and geometry of soil pores may exert primary controls on spatial metabolic diversity in soil. Here, we combine quantitative pore network metrics derived from X-ray computed tomography (XCT) with measurements of electromotive potentials to assess how the metabolic status of soil depends on variations of the overall pore network architecture. Contrasting pore network architectures were generated using a Mollisol—A horizon, and compared to intact control samples from the same soil. Mesocosms from each structural treatment were instrumented with Pt-electrodes to record available energy dynamics during a regimen of varying moisture conditions. We found that volume-based XCT-metrics were more frequently correlated with metrics describing changes in available energy than medial-axis XCT-metrics. An abundance of significant correlations between pore network metrics and available energy parameters was not only a function of pore architecture, but also of the dimensions of the sub-sample chosen for XCT analysis. Pore network metrics had the greatest power to statistically explain changes in available energy in the smallest volumes analyzed. Our work underscores the importance of scale in observations of natural systems

Toward a regional classification to provide a more inclusive examination of the ocean biogeochemistry of iron-binding ligands

© 2017 Hassler, van den Berg and Boyd. Iron-binding ligands are paramount to understanding iron biogeochemistry and its potential to set the productivity and the magnitude of the biological pump in > 30% of the ocean. However, the nature of these ligands is largely uncharacterized and little is known about their sources, sensitivity to photochemistry and biological transformation, or scavenging behavior. Despite many uncertainties, there is no doubt that ligands are produced by a wide range of biotic and abiotic processes, and that the bulk ligand pool encompasses a diverse range of molecules. Despite widespread recognition of the likelihood of a continuum of ligand classes making up the bulk ligand pool, studies to date largely focused on the dominant ligand. Thus, most studies have overlooked the need to assess where these targeted molecules fit across the spectrum of ligands that comprise the bulk ligand pool. Here we summarize present knowledge to critically assess the source(s), function(s), production pathways, and loss mechanisms of three important iron-binding organic ligand groups in order to assess their distinctive characteristics and how they link with observed ligand distributions. We considered that ligands are contained in broad groupings of exopolymer substances (EPS), humic substances (HS), and siderophores; using literature data for speciation modeling suggested that this adequately described the iron speciation reported in the ocean. We hypothesize that a holistic viewpoint of the multi-faceted controls on ligands dynamics is essential to begin to understand why some ligands can be expected to dominate in particular oceanic regions, depth strata, or exhibit seasonality and/or lateral gradients. We advocate that the development of a regional classification will enhance our understanding of the changing composition of the bulk ligand pool across the global ocean and to help address to what extent seasonality influences the makeup of this pool. This classification, based on selected functional ligand classes, can act as a bridge to use future ligand datasets to fill in the gaps in the continuum

Toward a Regional Classification to Provide a More Inclusive Examination of the Ocean Biogeochemistry of Iron-Binding Ligands

Iron-binding ligands are paramount to understanding iron biogeochemistry and its potential to set the productivity and the magnitude of the biological pump in >30% of the ocean. However, the nature of these ligands is largely uncharacterized and little is known about their sources, sensitivity to photochemistry and biological transformation, or scavenging behavior. Despite many uncertainties, there is no doubt that ligands are produced by a wide range of biotic and abiotic processes, and that the bulk ligand pool encompasses a diverse range of molecules. Despite widespread recognition of the likelihood of a continuum of ligand classes making up the bulk ligand pool, studies to date largely focused on the dominant ligand. Thus, most studies have overlooked the need to assess where these targeted molecules fit across the spectrum of ligands that comprise the bulk ligand pool. Here we summarize present knowledge to critically assess the source(s), function(s), production pathways, and loss mechanisms of three important iron-binding organic ligand groups in order to assess their distinctive characteristics and how they link with observed ligand distributions. We considered that ligands are contained in broad groupings of exopolymer substances (EPS), humic substances (HS), and siderophores; using literature data for speciation modeling suggested that this adequately described the iron speciation reported in the ocean. We hypothesize that a holistic viewpoint of the multi-faceted controls on ligands dynamics is essential to begin to understand why some ligands can be expected to dominate in particular oceanic regions, depth strata, or exhibit seasonality and/or lateral gradients. We advocate that the development of a regional classification will enhance our understanding of the changing composition of the bulk ligand pool across the global ocean and to help address to what extent seasonality influences the makeup of this pool. This classification, based on selected functional ligand classes, can act as a bridge to use future ligand datasets to fill in the gaps in the continuum