Faster randomized partial trace estimation

We develop randomized matrix-free algorithms for estimating partial traces. Our algorithm improves on the typicality-based approach used in [T. Chen and Y-C. Cheng, Numerical computation of the equilibrium-reduced density matrix for strongly coupled open quantum systems, J. Chem. Phys. 157, 064106 (2022)] by deflating important subspaces (e.g. corresponding to the low-energy eigenstates) explicitly. This results in a significant variance reduction for matrices with quickly decaying singular values. We then apply our algorithm to study the thermodynamics of several Heisenberg spin systems, particularly the entanglement spectrum and ergotropy

ARMAX-based transfer function model identification using wide-area measurement for adaptive and coordinated damping control

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. This paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-output (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. The results demonstrate that the measurementbased model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control

Biochar modulates heavy metal toxicity and improves microbial carbon use efficiency in soil

Soil organic carbon is essential to improve soil fertility and ecosystem functioning. Soil microorganisms contribute significantly to the carbon transformation and immobilisation processes. However, microorganisms are sensitive to environmental stresses such as heavy metals. Applying amendments, such as biochar, to contaminated soils can alleviate the metal toxicity and add carbon inputs. In this study, Cd and Pb spiked soils treated with macadamia nutshell biochar (5% w/w) were monitored during a 49days incubation period. Microbial phospholipid fatty acids (PLFAs) were extracted and analysed as biomarkers in order to identify the microbial community composition. Soil properties, metal bioavailability, microbial respiration, and microbial biomass carbon were measured after the incubation period. Microbial carbon use efficiency (CUE) was calculated from the ratio of carbon incorporated into microbial biomass to the carbon mineralised. Total PLFA concentration decreased to a greater extent in metal contaminated soils than uncontaminated soils. Microbial CUE also decreased due to metal toxicity. However, biochar addition alleviated the metal toxicity, and increased total PLFA concentration. Both microbial respiration and biomass carbon increased due to biochar application, and CUE was significantly (p<0.01) higher in biochar treated soils than untreated soils. Heavy metals reduced the microbial carbon sequestration in contaminated soils by negatively influencing the CUE. The improvement of CUE through biochar addition in the contaminated soils could be attributed to the decrease in metal bioavailability, thereby mitigating the biotoxicity to soil microorganisms

Measurements of Aquatic Particle Volume Scattering Function up to 178.5&deg; in the East China Sea

Particulate volume scattering function (VSF), especially at angles larger than 170&deg;, is of particular importance for interpreting ocean optical remote sensing signals and underwater imagery. In this study, a laboratory-based VSF instrument (VSFlab) adopting the periscopic optical system was developed to obtain VSF measurements from 1&deg;&ndash;178.5&deg;. In the VSFlab, a new prism design that simply combines a single prism and a neutral density filter was proposed to more efficiently reduce the stray light in the backward direction, while a detailed calibration procedure was given. A full validation based on standard beads of various sizes and a comparison with the results from LISST-VSF and POLVSM indicated that the VSFlab can provide reliable results from 1&deg; to 178.5&deg;. VSFlab measurements in the East China Sea (ECS) exhibited a moderate increase (not more than 5 times) in VSF from 170&deg; to 178.5&deg; rather than a sharp increase of more than one order of magnitude presented in other instrument results measured in other coastal regions. The estimates of the particulate backscattering coefficient using single angle scattering measurements near 120&deg; or 140&deg; and suitable &chi;p were justified. Two types of the VSFs with different size distribution and shape parameters in the ECS can be distinguished based on the variability of &chi;p after 155&deg;. The measured VSF could provide a basis for the parameterization of VSF in the radiative transfer model and the variability of &chi;p in the backward direction had the potential to be used to characterize the particles in the coastal region of the ECS

A Novel Immunofluorescent Computed Tomography (ICT) Method to Localise and Quantify Multiple Antigens in Large Tissue Volumes at High Resolution

<div><p>Current immunofluorescence protocols are limited as they do not provide reliable antibody staining within large tissue volumes (mm³) and cannot localise and quantify multiple antigens or cell populations in the same tissue at high resolution. To address this limitation, we have developed an approach to three-dimensionally visualise large tissue volumes (mm³) at high resolution (<1 µm) and with multiple antigen labelling, for volumetric and quantitative analysis. This is made possible through computer reconstruction of serial sectioned and sequentially immunostained butyl-methyl methacrylate (BMMA) embedded tissue. Using this novel immunofluorescent computed tomography (ICT) approach, we have three-dimensionally reconstructed part of the murine lower eyelid that contains the meibomian gland and localised cell nuclei (DAPI), Ki67 and cytokeratin 1 (CK1), as well as performing non-linear optical (NLO) microscopy imaging of collagen, to assess cell density, cell proliferation, gland keratinisation and gland volume respectively. Antigenicity was maintained after four iterative stains on the same tissue, suggesting that there is no defined limit to the number of antigens that can be immunostained for reconstruction, as long as the sections remain intact and the previous antibody has been successfully eluted. BMMA resin embedding also preserved fluorescence of transgenic proteins. We propose that ICT may provide valuable high resolution, three-dimensional biological maps of multiple biomolecules within a single tissue or organ to better characterise and quantify tissue structure and function.</p> </div