Mixed-mode oscillations and interspike interval statistics in the stochastic FitzHugh-Nagumo model

We study the stochastic FitzHugh-Nagumo equations, modelling the dynamics of neuronal action potentials, in parameter regimes characterised by mixed-mode oscillations. The interspike time interval is related to the random number of small-amplitude oscillations separating consecutive spikes. We prove that this number has an asymptotically geometric distribution, whose parameter is related to the principal eigenvalue of a substochastic Markov chain. We provide rigorous bounds on this eigenvalue in the small-noise regime, and derive an approximation of its dependence on the system's parameters for a large range of noise intensities. This yields a precise description of the probability distribution of observed mixed-mode patterns and interspike intervals.Comment: 36 page

Height and clonality traits determine plant community responses to fertilization

Fertilization via agricultural inputs and nutrient deposition is one of the major threats to global terrestrial plant richness, yet we still do not fully understand the mechanisms by which fertilization decreases plant richness. Tall clonal species have recently been proposed to cause declines in plant species richness by increasing in abundance in response to fertilization and competing strongly with other species. We tested this hypothesis in a fertilization experiment in a low productivity grassland by using a novel experimental manipulation of the presence vs. absence of clonal species and by examining the role of height within these treatments. We found that fertilization decreased species richness more in the presence than absence of clonal species. We also found that only tall species increased in biomass in response to fertilization. In the absence of clonal species, fertilization increased biomass of tall non clonal species. However, in the presence of clonal species, fertilization decreased tall non clonal biomass and only tall clonal biomass increased. Fertilization caused almost all short species to be lost in the presence, but not the absence, of clonal species and caused greater declines in the mean and variance of light levels in the presence of clonal species. These results show that the traits of species in a community can determine the magnitude of species loss due to fertilization. The strongly negative effect of tall clonals on species richness in fertilized plots is likely a result of their capacity to decrease light levels to a greater extent and more uniformly than non clonal species, and thereby drive the exclusion of short species. These results help clarify the mechanisms whereby fertilization decreases grassland plant species richness and suggest that efforts to prevent the loss of species under fertilized conditions may be most effective when they focus on controlling the biomass of tall clonal species

COVID-19 disruption reveals mass-tourism pressure on nearshore sea turtle distributions and access to optima breeding habitat

Quantifying the extent to which animals detect and respond to human presence allows us to identify pressure (disturbance) and inform conservation management objectively; however, obtaining baselines against which to compare human impact is hindered in areas where human activities are already well established. For example, Zakynthos Island (Greece, Mediterranean) receives around 850,000 visitors each summer, while supporting an important loggerhead sea turtle rookery (~300 individuals/season). The coronavirus (COVID-19)-driven absence of tourism in May–June 2020 provided an opportunity to evaluate the distribution dynamics of this population in the absence (2020) vs. presence (2018 and 2019) of visitors using programmed unmanned aerial system (UAS) surveys. Ambient sea temperature transitioned from suboptimal for breeding in May to optimal in late June, with turtle distribution appearing to shift from shallow (to benefit from waters 3–5°C above ambient) to deeper waters in 2018 and 2019, but not 2020. The 2020 data set demonstrated that increased tourism pressure, not temperature, drives turtles offshore. Specifically, >50% of turtles remained within 100 m of shore at densities of 25–50 visitors/km, even when sea temperature rose, with 2018 and 2019 data supporting this trend. Reduced access to warmer, nearshore waters by tourism could delay the onset of nesting and increase the length of the egg maturation period between nesting events (internesting interval) at this site. A coastal refuge zone could be delimited in May–June where touristic infrastructure is minimal, but also where turtles frequently aggregate. In conclusion, sea turtles appear capable of perceiving changes in the level of human pressure at fine spatial and temporal scales and adjusting their distribution accordingly

Functional rescue of dystrophin deficiency in mice caused by frameshift mutations using Campylobacter jejuni Cas9

Duchenne muscular dystrophy (DMD) is a fatal, X-linked muscle wasting disease caused by mutations in the DMD gene. In 51% of DMD cases, a reading frame is disrupted because of deletion of several exons. Here, we show that CjCas9 derived from Campylobacter jejuni can be used as a gene editing tool to correct an out-of-frame Dmd exon in Dmd knockout mice. Herein, we used Cas9 derived from S. pyogenes to generate Dmd knockout (KO) mice with a frameshift mutation in Dmd gene. Then, we expressed CjCas9, its single-guide RNA, and the eGFP gene in the tibialis anterior muscle of the Dmd KO mice using an all-in-one adeno-associated virus (AAV) vector. CjCas9 cleaved the target site in the Dmd gene efficiently in vivo and induced small insertions or deletions at the target site. This treatment resulted in conversion of the disrupted Dmd reading frame from out-of-frame to in-frame, leading to the expression of dystrophin in the sarcolemma. Importantly, muscle strength was enhanced in the CjCas9-treated muscles, without off-target mutations, indicating high efficiency and specificity of CjCas9. This work suggests that in vivo DMD frame correction, mediated by CjCas9 has great potential for the treatment of DMD and other neuromuscular diseases

Self-consistent symmetries in the proton-neutron Hartree-Fock-Bogoliubov approach

Symmetry properties of densities and mean fields appearing in the nuclear Density Functional Theory with pairing are studied. We consider energy functionals that depend only on local densities and their derivatives. The most important self-consistent symmetries are discussed: spherical, axial, space-inversion, and mirror symmetries. In each case, the consequences of breaking or conserving the time-reversal and/or proton-neutron symmetries are discussed and summarized in a tabulated form, useful in practical applications.Comment: 26 RevTex pages, 1 eps figure, 9 tables, submitted to Physical Review

Identification of a surrogate to validate irradiation processing of selected spices

Onion powder and talc were inoculated with one of three groups of Salmonella enterica or a putative surrogate, Enterococcus faecium NRRL B-2354, and the radiation sensitivity of S. enterica was compared to E. faecium. For both inoculated onion powder and inoculated talc, D10-values were greater for E. faecium than any of the three groups of S. enterica. The survival of E. faecium in irradiated talc was used to estimate the potential survival of S. enterica in irradiated spices. Onion powder, dried oregano, whole cumin seeds or peppercorns were mixed with talc inoculated with either S. enterica (previously associated with a foodborne disease outbreak) or E. faecium and irradiated. The D10-values were calculated for each bacterial group and compared between E. faecium and S. enterica within each spice. For each spice, the D10-value for E. faecium was either not statistically different from (P \u3c 0.05) S. entericaor greater than that of S. enterica (onion powder). Quadratic and linear models were developed to allow the estimation of potential surviving populations, and potential decimal reductions of S. enterica, based on surviving populations and decimal reductions determined with E. faecium. The use of E. faecium and these mathematical models would allow a processor to validate an irradiation process by estimating the reduction in S. enterica, based on the population reductions of E. faecium

Neurology

Contains reports on four research projects.U. S. Public Health Service (B-3055-4)U. S. Public Health Service (B-3090-4)U. S. Public Health Service (MH-06175-02)U.S. Navy (Office of Naval Research (Nonr-1841 (70))U. S. Air Force (AF49(638)-1313

A weekly, continually updated dataset of the probability of large wildfires across western US forests and woodlands

There is broad consensus that wildfire activity is likely to increase in western US forests and woodlands over the next century. Therefore, spatial predictions of the potential for large wildfires have immediate and growing relevance to near- and long-term research, planning, and management objectives. Fuels, climate, weather, and the landscape all exert controls on wildfire occurrence and spread, but the dynamics of these controls vary from daily to decadal timescales. Accurate spatial predictions of large wildfires should therefore strive to integrate across these variables and timescales. Here, we describe a high spatial resolution dataset (250&thinsp;m pixel) of the probability of large wildfires ( &gt; 405&thinsp;ha) across forests and woodlands in the contiguous western US, from 2005 to the present. The dataset is automatically updated on a weekly basis using Google Earth Engine and a continuous integration pipeline. Each image in the dataset is the output of a random forest machine-learning algorithm, trained on random samples of historic small and large wildfires and represents the predicted conditional probability of an individual pixel burning in a large fire, given an ignition or fire spread to that pixel. This novel workflow is able to integrate the near-term dynamics of fuels and weather into weekly predictions while also integrating longer-term dynamics of fuels, the climate, and the landscape. As a continually updated product, the dataset can provide operational fire managers with contemporary, on-the-ground information to closely monitor the changing potential for large wildfire occurrence and spread. It can also serve as a foundational dataset for longer-term planning and research, such as the strategic targeting of fuels management, fire-smart development at the wildland–urban interface, and the analysis of trends in wildfire potential over time. Weekly large fire probability GeoTiff products from 2005 to 2017 are archived on the Figshare online digital repository with the DOI https://doi.org/10.6084/m9.figshare.5765967 (available at https://doi.org/10.6084/m9.figshare.5765967.v1). Weekly GeoTiff products and the entire dataset from 2005 onwards are also continually uploaded to a Google Cloud Storage bucket at https://console.cloud.google.com/storage/wffr-preds/V1 (last access: 14 September 2018) and are available free of charge with a Google account. Continually updated products and the long-term archive are also available to registered Google Earth Engine (GEE) users as public GEE assets and can be accessed with the image collection ID users/mgray/wffr-preds within GEE.</p