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Replacing long-lived, rarely disturbed vegetation with short-lived, frequently disturbed vegetation is a widespread phenomenon in the Anthropocene that can influence ecosystem functioning and soil development by reducing the abundance of deep roots. We explore how sources and fate of soil CO2 vary with organic substrate source, abundance of respiring biota (i.e., roots and soil microbes), season, and soil depth. We quantified multiple isotopic signatures of CO2 (δ13C, Δ14C, δ18O) as well as concentrations and δ18O of free O2 in the upper 5 m of soil at sites where root abundances and soil organic C have been previously quantified: in late-successional forests, cultivated fields, and ~ 80 y old regenerating pine forests growing on previously cultivated land. We hypothesized that soil CO2sources would vary across soil depth and land cover, reflecting varying abundances of organic substrates, and seasonally as the dominance of root vs. microbial CO2 production changes through the year. δ13C–CO2 revealed respiration of C4-derived substrates in cultivated fields particularly during the growing season. This effect was not evident in soils of regenerating pine or older hardwood forests, suggesting that ~ 80 y of pine inputs to reforested soils have been sufficient to dominate microbial substrate selection over any remnant, historic agricultural C4 inputs. Δ14C–CO2 diverged by land use at 3 and 5 m, indicating that more recently-produced photosynthate is available for mineralization in forests compared to cultivated plots, and in late-successional forests compared to regenerating pine forests. At 1.5, 3, and 5 m in forested plots we observed evidence of respiratory demands on soil pore space O2. In these soils, we observed declines in [O2] compared to other depths and to the agricultural plots and concurrent increases in δ18O of free O2, consistent with the idea that roots and heterotrophic soil microbes are more active where photosynthate is more available. The δ18O–CO2 values, a likely proxy for δ18O of soil porewater, exhibited 18O enrichment during the winter, when many sampling wells were flooded, compared to growing season values. These data suggest an isotopically-distinct and laterally-flowing source of CO2-laden porewater during winter months. Combined, these datasets document how ~ 80 y of forest regeneration can provide sufficient C inputs to mask any microbial mineralization of decades-old organic inputs, but belowground C inputs still lag those of late successional forests. We also infer that lateral and vertical flows of water can serve as a sink for biotically-generated CO2, and that where deep soil [CO2] is lower due to lower root and microbial activities, production of carbonic acid is also diminished. Where reaction rates are weathering limited, a paucity of deep roots imposed by anthropogenic land cover change thus may limit the production of this agent of soil development and the C sink represented by the silicate weathering it can promote. The data suggest deep and persistent effects of the loss of deeply rooted long-lived vegetation on deep soil C storage and transformations that promote acid-dissolution weathering reactions that help form soil itself. [ABSTRACT FROM AUTHOR]

Community composition in semi-arid ecosystems has largely been explained by water availability; however, nitrogen is a common limiting nutrient, and may be an important control on plant function and carbon uptake. We investigated nitrogen relations and photosynthesis of several dominant species at shallow groundwater sites in Owens Valley, California. We measured soil nitrogen (N) availability, leaf N and isotopes, water isotopes, and gas exchange of dominant shrub species Atriplex torreyi and Ericameria nauseosa and grass species Distichlis spicata throughout the summer season in three sites that had similar watertable depths, but that varied in community composition and N availability. Surface soil inorganic N was greatest at the grassland site and declined from June to September at all sites. Leaf N declined throughout the season in all species, and was correlated with soil inorganic N. Photosynthesis of A. torreyi remained relatively constant throughout the season. In contrast, D. spicata and E. nauseosa experienced seasonal declines in photosynthesis at sites with greater inorganic N availability. Leaf N was significantly correlated with photosynthesis in D. spicata across all sites and measurement periods. Controls on N cycling are likely to be an important determinant of photosynthesis of D. spicata in this region.

Mammalian inner ear hair cell loss leads to permanent hearing and balance dysfunction. In contrast to the cochlea, vestibular hair cells of the murine utricle have some regenerative capacity. Whether human utricular hair cells regenerate in vivo remains unknown. Here we procured live, mature utricles from organ donors (9 ears from 6 organ donors) and vestibular schwannoma patients (24 ears from 24 patients), and presented a single-cell transcriptomic atlas at unprecedented resolution. We validated marker genes using immunostaining and RNAscope in situ hybridization and described previously unknown markers of 13 sensory and non-sensory cell types. In addition, we compared and found partial overlap and correlation between transcriptomes of human and mouse hair cells and supporting cells. We further uncovered transcriptomes unique to hair cell precursors, which are validated in both organ donor and vestibular schwannoma utricles. Unexpectedly we found 14-fold more hair cell precursors in vestibular schwannoma utricles, demonstrating the existence of ongoing regeneration in humans. Lastly, supporting cell-to-hair cell trajectory analysis revealed 5 distinct patterns of dynamic gene expression and associated pathways. Our data-set constitutes a foundational resource, accessible via a web-based interface, serving to advance knowledge of the normal and diseased human inner ear. [ABSTRACT FROM AUTHOR]

Summary: Background: Calciphylaxis is a life‐threatening cutaneous ulcerative/necrotic disease characterized by vascular calcification/occlusion. It occurs most commonly in end‐stage kidney disease (ESKD), known as uraemic calciphylaxis (UC) but can also occur in patients with chronic kidney disease (CKD) and normal kidney function (nonuraemic calciphylaxis; NUC). There are few large series of NUC in the literature. Aim: To compare the clinicopathological features of UC and NUC. Methods: We retrospectively compared the clinicopathological features of 35 patients with NUC during the period 2010–2020 with those of 53 patients with UC (control group). Cases were classified as NUC in the absence of all of the following: ESKD, significant CKD (defined as serum creatinine > 3 mg/dL or creatinine clearance < 15 mL/min) and acute kidney injury requiring kidney replacement therapy or kidney transplantation. Results: NUC represented 40% of the total cases, and there was a higher number of women (P < 0.01) and a higher median body mass index (P = 0.06) compared with the control UC group. Elevated parathyroid hormone was present in 44% of patients with NUC. Most of the tested patients were positive for lupus anticoagulants (56%). NUC biopsies showed a higher rate of extravascular calcium deposits (73% vs. 47%, P = 0.03). Dermal reactive vascular proliferation was the most common dermal change (32%). Conclusions: NUC is more common than previously reported and shows a higher predilection for obese postmenopausal women. Undiagnosed hyperparathyroidism shows a possible association with NUC. Lupus anticoagulants were positive in most patients. NUC biopsies are more likely than UC biopsies to display extravascular calcium deposition. [ABSTRACT FROM AUTHOR]

Background: Tumor necrosis factor-α inhibitor (TNFi)-induced psoriasis is a paradoxic reaction characterized by the development of a psoriasiform rash that mimics idiopathic psoriasis subtypes both clinically and histologically. Few studies have investigated the histologic features of TNFi-induced psoriasis skin lesions, and most of these are limited by inclusion of few specimens.Objective: We aimed to characterize histologic features of TNFi-induced psoriasis and identify histologic differences between TNFi-induced psoriasis and idiopathic psoriasis.Methods: We characterized 60 biopsy specimens obtained from 47 unique patients at a single tertiary care referral center between 2004 and 2016 who developed TNFi-induced psoriasis, and we compared histologic features to those of 85 biopsy specimens from a control group of 85 patients with idiopathic psoriasis.Results: The most common histologic reaction pattern in TNFi-induced psoriasis biopsy specimens was psoriasiform (80.0%). Five histologic parameters were significantly different in TNFi-induced psoriasis biopsy specimens compared with idiopathic psoriasis biopsy specimens: at least 3 dermal eosinophils per histologic section, neutrophils in the stratum corneum, neutrophils in the epidermis, papillary plate thinning, and absence of parakeratosis.Limitations: Inability to exclude lesion selection bias as a potential reason for some significant histologic differences.Conclusions: This study supports the idea that histologic differences exist between TNFi-induced psoriasis and idiopathic psoriasis may help distinguish between these conditions, especially for dermal eosinophil counts of 3 or greater. [ABSTRACT FROM AUTHOR]

Since age is the most significant risk factor for the development of Alzheimer’s disease (AD), it is important to understand the effect of normal ageing on brain network characteristics before we can accurately diagnose the condition based on information derived from resting state electroencephalogram (EEG) recordings, aiming to detect brain network disruption. This article proposes a novel brain functional connectivity imaging method, particularly targeting the contribution of nonlinear dynamics of functional connectivity, on distinguishing participants with AD from healthy controls (HC). We describe a parametric method established upon a Nonlinear Finite Impulse Response model, and a revised orthogonal least squares algorithm used to estimate the linear, nonlinear and combined connectivity between any two EEG channels without fitting a full model. This approach, where linear and non-linear interactions and their spatial distribution and dynamics can be estimated independently, offered us the means to dissect the dynamic brain network disruption in AD from a new perspective and to gain some insight into the dynamic behaviour of brain networks in two age groups (above and below 70) with normal cognitive function. Although linear and stationary connectivity dominates the classification contributions, quantitative results have demonstrated that nonlinear and dynamic connectivity can significantly improve the classification accuracy, barring the group of participants below the age of 70, for resting state EEG recorded during eyes open. The developed approach is generic and can be used as a powerful tool to examine brain network characteristics and disruption in a user friendly and systematic way. [ABSTRACT FROM AUTHOR]

Using Genetic Algorithms (GAs) to search for cellular automation (CA) rules from spatio-temporal patterns produced in CA evolution is usually complicated and time-consuming when both the neighborhood structure and the local rule are searched simultaneously. The complexity of this problem motivates the development of a new search which separates the neighborhood detection from the GA search. In this paper, the neighborhood is determined by independently selecting terms from a large term set on the basis of the contribution each term makes to the next state of the cell to be updated. The GA search is then started with a considerably smaller set of candidate rules pre-defined by the detected neighborhood. This approach is tested over a large set of one-dimensional (1-D) and two-dimensional (2-D) CA rules. Simulation results illustrate the efficiency of the new algorithm. Index Terms--Cellular automata, genetic algorithms, identification, spatio-temporal systems.

A multiobjective genetic algorithm (GA) is introduced to identify both the neighborhood and the rule set in the form of a parsimonious Boolean expression for both one- and two-dimensional cellular automata (CA). Simulation results illustrate that the new algorithm performs well even when the patterns are corrupted by static and dynamic noise. Index Terms--Boolean identification, cellular automata, genetic algorithms, spatio-temporal systems.

In this paper, a new method for evaluating output frequency responses of nonlinear systems under multiple inputs, defined as a sum of sinusoids of different frequencies, is developed. The method circumvents difficulties associated with the existing 'frequency-mix vector' based approaches and can easily be applied to investigate nonlinear behaviors of practical systems, including electronic circuits, at the system simulation and design stages. Application of the method to the analysis of nonlinear interference and distortion effects in communication receivers is studied, and specific procedures are proposed which can be directly used in practice for this analysis. Index Terms--Communication receivers, frequency-domain analysis, nonlinear systems/circuits.

Understanding how tree growth strategies may influence tree susceptibility to disturbance is an important goal, especially given projected increases in diverse ecological disturbances this century. We use growth responses of tree rings to climate, relationships between tree-ring stable isotopic signatures of carbon (δ13C) and oxygen (δ18O), wood nitrogen concentration [N], and contemporary leaf [N] and δ13C values to assess potential historic drivers of tree photosynthesis in dying and apparently healthy co-occurring northern red oak (Quercus rubra L. (Fagaceae)) during a region-wide oak decline event in Arkansas, USA. Bole growth of both healthy and dying trees responded negatively to drought severity (Palmer Drought Severity Index) and temperature; healthy trees exhibited a positive, but small, response to growing season precipitation. Contrary to expectations, tree-ring δ13C did not increase with drought severity. A significantly positive relationship between tree-ring δ13C and δ18O was evident in dying trees (P < 0.05) but not in healthy trees. Healthy trees' wood exhibited lower [N] than that of dying trees throughout most of their lives (P < 0.05), and we observed a significant, positive relationship (P < 0.05) in healthy trees between contemporary leaf δ13C and leaf N (by mass), but not in dying trees. Our work provides evidence that for plants in which strong relationships between δ13C and δ18O are not evident, δ13C may be governed by plant N status. The data further imply that historic photosynthesis in healthy trees was linked to N status and, perhaps, C sink strength to a greater extent than in dying trees, in which treering stable isotopes suggest that historic photosynthesis was governed primarily by stomatal regulation. This, in turn, suggests that assessing the relative dominance of photosynthetic capacity vs stomatal regulation as drivers of trees' C accrual may be a feasible means of predicting tree responses to some disturbance events. Our work demonstrates that a dual isotope, tree-ring approach can be integrated with tree N status to begin to unravel a fundamental question in forest ecology: why do some trees die during a disturbance, while other conspecifics with apparently similar access to resources remain healthy? [ABSTRACT FROM AUTHOR]

In this paper, we study the electromagnetic scattering of a conducting and permeable sphere buried in sea sediments. Instead of taking a uniform conducting medium in the previous work, we model marine environments as a layered medium that consists of the air, the sea, and the sediment. We adopt an integral equation technique to compute time-harmonic solutions for background and scattered fields under fundamental source excitations, i.e., vertical and horizontal magnetic dipoles. The corresponding transient scattering responses to causal step waveform are computed through the digital sine transform. The derived fundamental solutions provide convenient formulas tailored for three-layer medium modeling. The numerical experiments demonstrate that the scattered responses computed in the different backgrounds are approaching almost to the same decays at late times. However, the background fields can significantly mask the scattered responses. Subtracting assumed uniform background responses from “measured” total fields in the three-layered medium cannot provide a correct scattering response in the interested time range, i.e., 0.1–25 ms. To remove the background fields, we propose a conceptual gradiometer system that has receiver cubes installed radially symmetric with respect to a transmitting antenna. The results demonstrate that the suitable differential combinations are able to yield the scattering responses that well agree with those of a free space as the layered background fields in these combined receivers are equal and their influence are automatically canceled out. [ABSTRACT FROM PUBLISHER]

Understanding how carbon dioxide (CO2) flux from soils feeds back to climate warming depends in part on our ability to quantify the efficiency with which microorganisms convert soil organic carbon (C) into either biomass or CO2. Quantifying ecosystem-level respiratory CO2 losses often also requires assumptions about stable C isotope fractionations associated with the microbial transformation of soil organic substrates. However, the diversity of organic substrates' δ13C and the challenges of measuring microbial C use efficiency (CUE) in soils fundamentally limit our ability to project soil, and thus ecosystem, C budgets in a warming climate. Here, we quantify the effect of temperature on C fluxes during metabolic transformations of cellobiose, a common microbial substrate, by a cosmopolitan soil microorganism growing at a constant rate. Specific respiration rate increased by 250% between 13 and 26.5 °C, decreasing CUE from 77 to 56%. Specific respiration rate was positively correlated with an increase in respiratory 13C discrimination from 4.4 to 6.7 ‰ across the same temperature range. This first demonstration of a direct link between temperature, microbial CUE and associated isotope fluxes provides a critical step towards understanding δ13C of respired CO2 at multiple scales, and towards a framework for predicting future soil C fluxes. [ABSTRACT FROM AUTHOR]

Multi-input single-output (MISO) nonlinear autoregressive moving average with exogenous inputs (NARMAX) models have been derived to forecast the > 0:8MeV and > 2MeV electron fluxes at geostationary Earth orbit (GEO). The NARMAX algorithm is able to identify mathematical model for a wide class of nonlinear systems from input-output data. The models employ solar wind parameters as inputs to provide an estimate of the average electron flux for the following day, i.e. the 1-day forecast. The identified models are shown to provide a reliable forecast for both > 0:8 and > 2MeV electron fluxes and are capable of providing real-time warnings of when the electron fluxes will be dangerously high for satellite systems. These models, named SNB3GEO> 0:8 and > 2MeV electron flux models, have been implemented online at http://www.ssg.group.shef.ac.uk/USSW/UOSSW.html. [ABSTRACT FROM AUTHOR]

We present a new approach for inverting time-domain electromagnetic data to recover the location and magnetic dipole polarizations of a limited number of buried objects. We form the multichannel electromagnetic induction (EMI) sensor data as a spatial-temporal response matrix (STRM). The rows of the STRM correspond to measurements sampled at different time channels from one sensor and the columns correspond to measurements sampled at the same time channel from different sensors. The singular value decomposition of the STRM produces the left and right singular vectors that are related to the sensor and the temporal spaces, respectively. If the effective rank of the STRM is r, then the first r singular vectors span signal subspaces (SS), and the remaining singular vectors span the noise subspaces. The original data are projected onto the SS, and the temporal orthogonal projection inversion (TOPI) uses these data in a nonlinear inverse problem to solve for source locations of the objects. The polarizations of the targets are then obtained by solving a linear optimization problem in the original data domain. We present theoretical and numerical analyses to investigate the singular value system of the STRM and the sensitivity of the TOPI to the size of an SS. Only a few subspace vectors are required to generate locations of the objects. The results are insensitive to the exact choice of rank, and this differs from usual methods that involve selecting the number of time channels to be used in the inversion and carefully estimating associated uncertainties. The proposed approach is evaluated using the synthetic and real multistatic EMI data. [ABSTRACT FROM PUBLISHER]

The relationship between the solar wind and the proton flux at geosynchronous Earth orbit (GEO) is investigated using the error reduction ratio (ERR) analysis. The ERR analysis is able to search for the most appropriate inputs that control the evolution of the system. This approach is a black box method and is able to derive a mathematical model of a system from input-output data. This method is used to analyse eight energy ranges of the proton flux at GEO from 80 keV to 14.5MeV. The inputs to the algorithm were solar wind velocity, density and pressure; the Dst index; the solar energetic proton (SEP) flux; and a function of the interplanetary magnetic field (IMF) tangential magnitude and clock angle. The results show that for lowest five energy channels (80 to 800 keV) the GEO proton fluxes are controlled by the solar wind velocity with a lag of two to three days. However, above 350 keV, the SEP fluxes, accounts for a significant portion of the GEO proton flux variance. For the highest three energy channels (0.74 to 14.5 MeV), the SEPs account for the majority of the ERR. The results also show an anisotropy of protons with gyrocenters inside GEO and outside GEO, where the protons inside GEO are controlled partly by the Dst index and also an IMF-clock angle function. [ABSTRACT FROM AUTHOR]

The main problem of using a conventional linear damper on a vibration isolation system is that the reduction of the resonant peak in many cases inevitably results in the degradation of the high-frequency transmissibility. Instead of using active control methods which normally depend on the model of the controlled plant and where unmodelled dynamics may induce stability concerns, recent studies have revealed that optimal vibration isolation over a wide frequency range can be achieved by using nonlinear damping. The present study is concerned with the realization of the ideal nonlinear damping characteristic using a feedback-controlled MR damper. Both simulation and experimental studies are conducted to demonstrate the advantages of the simple but effective vibration control strategy. This research work has significant implications for the effective use of MR dampers in the vibration control of a wide range of engineering systems. [ABSTRACT FROM AUTHOR]

When given a complex cellular automata (CA) system, especially a real system, the transition rule over the whole evolution is often not uniform, which means that different spatial positions may have different rules at the same time. Currently, most methods for the identification of CA are only suitable for systems with uniform rules. Therefore, it is necessary to develop an algorithm which can detect the region with a specific rule or partition each region with different rules for a hybrid CA system. Current methods of identification could then be applied to each region to identify the CA model. By mapping the realistic CA pattern to a virtual image, this paper first introduces two popular image segmentation algorithms to aid the identification of hybrid CA. A popular nonlinear filter in image processing, the median filter, is then proposed to remove noise in the segmented image to avoid over-estimation. Two examples, including a one-dimensional and a two-dimensional CA system are then employed to demonstrate the algorithms. It is shown that the results are encouraging by comparing the original rule distribution graph and the detected rule distribution graph, and comparing the reconstructed patterns and the observed patterns. [ABSTRACT FROM AUTHOR]

The selection of the neighbourhood is a very important part of the specification and training of Cellular Automata (CA) in image processing. Rather than guessing or assuming a specific neighbourhood, this paper investigates the selection of the neighbourhood and studies how the level of added noise in the image affects the selection of an optimal neighbourhood. To enhance the performance of noise removal using Cellular Automata. a basic totalistic CA (BTCA) model and a new weighted totalistic CA (WTCA) model are introduced. Both methods require much less memory storage and are feasible in practice even for very large neighbourhoods. Several experiments are presented to demonstrate that both proposed methods produce consistently better performance than the median filter and the traditional CA method for low noise levels, and for filtering at high noise levels, the WTCA model is shown an excellent performance compared to other methods. [ABSTRACT FROM AUTHOR]

An important step in the identification of cellular automata (CA) is to detect the correct neighborhood before parameter estimation. Many authors have suggested procedures based on the removal of redundant neighbors from a very large initial neighborhood one by one to find the real model, but this often induces ill conditioning and overfitting. This is true particularly for a large initial neighborhood where there are few significant terms, and this will be demonstrated by an example in this paper. By introducing a new criteria and three new techniques, this paper proposes a new adaptive fast CA orthogonal-least-square (Adaptive-FCA-OLS) algorithm, which cannot only adaptively search for the correct neighborhood without any preset tolerance but can also considerably reduce the computational complexity and memory usage. Several numerical examples demonstrate that the Adaptive-FCA-OLS algorithm has better robustness to noise and to the size of the initial neighborhood than other recently developed neighborhood detection methods in the identification of binary CA. [ABSTRACT FROM AUTHOR]