Simulated Productivity Lost by Erosion (SimPLE): model development, validation, and use

Non-Peer ReviewedProductivity lost due to soil erosion can be estimated by existing computer simulation models such as EPIC, NTRM and CENTURY. However, these models require extensive input data and, to date, have had limited success in simulating Western Canadian conditions. The objective of this study was to develop a simple spring wheat model which captured the essential relationships between topsoil erosion and productivity loss in Chemozemic soils. Key relationships in our model describe: (i) how plants create yield from water, N, and P; (ii) how the soil provides these nutrients, and (iii) how erosion impacts on the supply of each nutrient. These relationships were logically connected using the Stella® II modeling environment. Agreement was highly significant (r = 0.55***) between predicted and observed grain yields over 75 site years at Indian Head, Saskatchewan. Also, grain yields from scalped Chemozemic soils in Alberta were closely simulated (r = 0.86****) by SimPLE. Fifty representative soil profiles from the Brown, Dark Brown and Black soil zones were eroded in SimPLE to numerically describe the production lost under wet, normal, and dry scenarios, with and without optimum fertilizer. Yield loss, as a percentage of non-eroded yield, increased with increasing soil erosion following a trend very similar to that reported in field studies. SimPLE is flexible and can be used for analysis of "what if' management scenarios or calculating soil loss tolerance (T) values

Developing simplified synergistic relationships to model topsoil erosion and crop yield

Non-Peer ReviewedTopsoil is highly enriched with organic matter, which provides a valuable source of plant nutrients as well as a favorable rooting environment. Over time, erosion processes selectively remove the organic matter-rich fine fraction which causes a measurable reduction in soil productivity. Assessments of past erosion are of little value in predicting future losses in productivity since the synergistic lowering of soil organic matter through lower residue inputs is not considered. Dynamic computer models, which simulate the plant/soil system, can project the long run future costs of soil erosion on crop yield. A simplified erosion-crop yield model was developed by first defining the most important soil productivity variables, then quantifying the effect of erosion on each variable. The model predicted a declining trend in grain yields similar to that observed on soil scalping experiments

Modulation control and spectral shaping of optical fiber supercontinuum generation in the picosecond regime

Numerical simulations are used to study how fiber supercontinuum generation seeded by picosecond pulses can be actively controlled through the use of input pulse modulation. By carrying out multiple simulations in the presence of noise, we show how tailored supercontinuum Spectra with increased bandwidth and improved stability can be generated using an input envelope modulation of appropriate frequency and depth. The results are discussed in terms of the non-linear propagation dynamics and pump depletion.Comment: Aspects of this work were presented in Paper ThJ2 at OECC/ACOFT 2008, Sydney Australia 7-10 July (2008). Journal paper submitted for publication 30 July 200

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Bacterial growth at -15 \ub0C; molecular insights from the permafrost bacterium Planococcus halocryophilus Or1

Planococcus halocryophilus strain Or1, isolated from high Arctic permafrost, grows and divides at -15 \ub0C, the lowest temperature demonstrated to date, and is metabolically active at -25 \ub0C in frozen permafrost microcosms. To understand how P. halocryophilus Or1 remains active under the subzero and osmotically dynamic conditions that characterize its native permafrost habitat, we investigated the genome, cell physiology and transcriptomes of growth at -15 \ub0C and 18% NaCl compared with optimal (25 \ub0C) temperatures. Subzero growth coincides with unusual cell envelope features of encrustations surrounding cells, while the cytoplasmic membrane is significantly remodeled favouring a higher ratio of saturated to branched fatty acids. Analyses of the 3.4 Mbp genome revealed that a suite of cold and osmotic-specific adaptive mechanisms are present as well as an amino acid distribution favouring increased flexibility of proteins. Genomic redundancy within 17% of the genome could enable P. halocryophilus Or1 to exploit isozyme exchange to maintain growth under stress, including multiple copies of osmolyte uptake genes (Opu and Pro genes). Isozyme exchange was observed between the transcriptome data sets, with selective upregulation of multi-copy genes involved in cell division, fatty acid synthesis, solute binding, oxidative stress response and transcriptional regulation. The combination of protein flexibility, resource efficiency, genomic plasticity and synergistic adaptation likely compensate against osmotic and cold stresses. These results suggest that non-spore forming P. halocryophilus Or1 is specifically suited for active growth in its Arctic permafrost habitat (ambient temp. ~ -16 \ub0C), indicating that such cryoenvironments harbor a more active microbial ecosystem than previously thought. \ua9 2013 International Society for Microbial Ecology.Peer reviewed: YesNRC publication: Ye

Prognostication of post-cardiac arrest coma: early clinical and electroencephalographic predictors of outcome

Purpose: To determine the temporal evolution, clinical correlates, and prognostic significance of electroencephalographic (EEG) patterns in post-cardiac arrest comatose patients treated with hypothermia. Methods: Prospective cohort study of consecutive post-anoxic patients receiving hypothermia and continuous EEG monitoring between May 2011 and June 2014 (n = 100). In addition to clinical variables, 5-min EEG clips at 6, 12, 24, 48, and 72 h after return of spontaneous circulation (ROSC) were reviewed. EEG background was classified according to the American Clinical Neurophysiological Society critical care EEG terminology. Clinical outcome at discharge was dichotomized as good [Glasgow outcome scale (GOS) 4–5, low to moderate disability] vs. poor (GOS 1–3, severe disability to death). Results: Non-ventricular fibrillation/tachycardia arrest, longer time to ROSC, absence of brainstem reflexes, extensor or no motor response, lower pH, higher lactate, hypotension requiring >2 vasopressors, and absence of reactivity on EEG were all associated with poor outcome (all p values ≤0.01). Suppression-burst at any time indicated a poor prognosis, with a 0 % false positive rate (FPR) [95 % confidence interval (CI) 0–10 %]. All patients (54/54) with suppression-burst or a low voltage (70 % for good outcome. Conclusions: Suppression-burst or a low voltage at 24 h after ROSC was not compatible with good outcome in this series. Normal background voltage without epileptiform discharges predicted a good outcome.SCOPUS: ar.jinfo:eu-repo/semantics/publishe