Putting Soybeans into Permanent Farming

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Inherent-Structure Dynamics and Diffusion in Liquids

The self-diffusion constant D is expressed in terms of transitions among the local minima of the potential (inherent structure, IS) and their correlations. The formulae are evaluated and tested against simulation in the supercooled, unit-density Lennard-Jones liquid. The approximation of uncorrelated IS-transition (IST) vectors, D_{0}, greatly exceeds D in the upper temperature range, but merges with simulation at reduced T ~ 0.50. Since uncorrelated IST are associated with a hopping mechanism, the condition D ~ D_{0} provides a new way to identify the crossover to hopping. The results suggest that theories of diffusion in deeply supercooled liquids may be based on weakly correlated IST.Comment: submitted to PR

Protocol for the United Kingdom Rotator Cuff Study (UKUFF) : a randomised controlled trial of open and arthroscopic rotator cuff repair

This project was funded by the NIHR Health Technology Assessment programme (project number 05/47/02). J. L. Rees has received a grant from Oxford University which is related to this paper. J. Dawson reports that Oxford University has received a grant from HTA which is related to this paper, as well as a study grant.Peer reviewedPublisher PD

Molecular Identification of Eimeria Species in Broiler Chickens in Trinidad, West Indies

Coccidiosis is an intestinal disease of chickens of major economic importance to broiler industries worldwide. Species of coccidia found in chickens include Eimeria acervulina, Eimeria brunetti, Eimeria maxima, Eimeria mitis, Eimeria necatrix, Eimeria praecox, and Eimeria tenella. In recent years, polymerase chain reaction (PCR) has been developed to provide accurate and rapid identification of the seven known Eimeria species of chickens. The aim of this study was to use species-specific real-time PCR (qPCR) to identify which of the seven Eimeria species are present in Trinidad poultry. Seventeen pooled fecal samples were collected from 6 broiler farms (2–5 pens per farm) across Trinidad. Feces were also collected from birds showing clinical signs of coccidiosis in two live bird markets (pluck shops). qPCR revealed the presence of five species of Eimeria (E. acervulina, E. maxima, E. mitis, E. necatrix, and E. tenella), but not E. brunetti or E. praecox. Mixed infections were detected on all broiler farms, and DNA of two highly pathogenic Eimeria species (E. tenella and E. necatrix) was detected in feces taken from clinically sick birds sampled from the two pluck shops

Does the addition of a supportive chatbot promote user engagement with a smoking cessation app? An experimental study

Does the addition of a supportive chatbot promote user engagement with a smoking cessation app? An experimental study Show all authors Olga Perski, David Crane, Emma Beard, ... First Published September 30, 2019 Research Article https://doi.org/10.1177/2055207619880676 Article information Article has an altmetric score of 27 Open AccessCreative Commons Attribution 4.0 License Abstract Objective The objective of this study was to assess whether a version of the Smoke Free app with a supportive chatbot powered by artificial intelligence (versus a version without the chatbot) led to increased engagement and short-term quit success. Methods Daily or non-daily smokers aged ≥18 years who purchased the ‘pro’ version of the app and set a quit date were randomly assigned (unequal allocation) to receive the app with or without the chatbot. The outcomes were engagement (i.e. total number of logins over the study period) and self-reported abstinence at a one-month follow-up. Unadjusted and adjusted negative binomial and logistic regression models were fitted to estimate incidence rate ratios (IRRs) and odds ratios (ORs) for the associations of interest. Results A total of 57,214 smokers were included (intervention: 9.3% (5339); control: 90.7% (51,875). The app with the chatbot compared with the standard version led to a 101% increase in engagement (IRRadj = 2.01, 95% confidence interval (CI) = 1.92–2.11, p < .001). The one-month follow-up rate was 10.6% (intervention: 19.9% (1,061/5,339); control: 9.7% (5,050/51,875). Smokers allocated to the intervention had greater odds of quit success (missing equals smoking: 844/5,339 vs. 3,704/51,875, ORadj = 2.38, 95% CI = 2.19–2.58, p < .001; follow-up only: 844/1,061 vs. 3,704/5,050, ORadj = 1.36, 95% CI = 1.16–1.61, p < .001). Conclusion The addition of a supportive chatbot to a popular smoking cessation app more than doubled user engagement. In view of very low follow-up rates, there is low quality evidence that the addition also increased self-reported smoking cessation

The Inferred Cardiogenic Gene Regulatory Network in the Mammalian Heart

Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was applied to time-course microarray data obtained from the developing mouse heart. Approximately 200 genes of interest were input into the algorithm to generate putative network topologies that are capable of explaining the experimental data via model simulation. To cull specious network interactions, thousands of putative networks are merged and filtered to generate scale-free, hierarchical networks that are statistically significant and biologically relevant. The networks are validated with known gene interactions and used to predict regulatory pathways important for the developing mammalian heart. Area under the precision-recall curve and receiver operator characteristic curve are 9% and 58%, respectively. Of the top 10 ranked predicted interactions, 4 have already been validated. The algorithm is further tested using a network enriched with known interactions and another depleted of them. The inferred networks contained more interactions for the enriched network versus the depleted network. In all test cases, maximum performance of the algorithm was achieved when the purely data-driven method of network inference was combined with a data-independent, functional-based association method. Lastly, the network generated from the list of approximately 200 genes of interest was expanded using gene-profile uniqueness metrics to include approximately 900 additional known mouse genes and to form the most likely cardiogenic gene regulatory network. The resultant network supports known regulatory interactions and contains several novel cardiogenic regulatory interactions. The method outlined herein provides an informative approach to network inference and leads to clear testable hypotheses related to gene regulation

Ultrafast supercontinuum spectroscopy of carrier multiplication and biexcitonic effects in excited states of PbS quantum dots

We examine the multiple exciton population dynamics in PbS quantum dots by ultrafast spectrally-resolved supercontinuum transient absorption (SC-TA). We simultaneously probe the first three excitonic transitions over a broad spectral range. Transient spectra show the presence of first order bleach of absorption for the 1S_h-1S_e transition and second order bleach along with photoinduced absorption band for 1P_h-1P_e transition. We also report evidence of the one-photon forbidden 1S_{h,e}-1P_{h,e} transition. We examine signatures of carrier multiplication (multiexcitons for the single absorbed photon) from analysis of the first and second order bleaches, in the limit of low absorbed photon numbers (~ 10^-2), at pump energies from two to four times the semiconductor band gap. The multiexciton generation efficiency is discussed both in terms of a broadband global fit and the ratio between early- to long-time transient absorption signals.. Analysis of population dynamics shows that the bleach peak due to the biexciton population is red-shifted respect the single exciton one, indicating a positive binding energy.Comment: 16 pages, 5 figure

Clinopyroxene/melt trace element partitioning in sodic alkaline magmas

Clinopyroxene is a key fractionating phase in alkaline magmatic systems, but its impact on metal enrichment processes, and the formation of REE + HFSE mineralisation in particular, is not well understood. To constrain the control of clinopyroxene on REE + HFSE behaviour in sodic (per)alkaline magmas, a series of internally heated pressure vessel experiments was performed to determine clinopyroxene–melt element partitioning systematics. Synthetic tephriphonolite to phonolite compositions were run H2O-saturated at 200 MPa, 650–825°C with oxygen fugacity buffered to log f O2 ≈ ΔFMQ + 1 or log f O2 ≈ ΔFMQ +5. Clinopyroxene–glass pairs from basanitic to phonolitic fall deposits from Tenerife, Canary Islands, were also measured to complement our experimentally-derived data set. The REE partition coefficients are 0·3–53, typically 2–6, with minima for high-aegirine clinopyroxene. Diopside-rich clinopyroxene (Aeg5–25) prefer the MREE and have high REE partition coefficients (DEu up to 53, DSm up to 47). As clinopyroxene becomes more Na- and less Ca-rich (Aeg25–50), REE incorporation becomes less favourable, and both the VIM1 and VIIIM2 sites expand (to 0·79 Å and 1·12 Å), increasing DLREE/DMREE. Above Aeg50 both M sites shrink slightly and HREE (VIri ≤ 0·9 Å ≈ Y) partition strongly onto the VIM1 site, consistent with a reduced charge penalty for REE3+ ↔ Fe3+ substitution. Our data, complemented with an extensive literature database, constrain an empirical model that predicts trace element partition coefficients between clinopyroxene and silicate melt using only mineral major element compositions, temperature and pressure as input. The model is calibrated for use over a wide compositional range and can be used to interrogate clinopyroxene from a variety of natural systems to determine the trace element concentrations in their source melts, or to forward model the trace element evolution of tholeiitic mafic to evolved peralkaline magmatic systems

Astrophysical S-factors for fusion reactions involving C, O, Ne and Mg isotopes

Using the Sao Paulo potential and the barrier penetration formalism we have calculated the astrophysical factor S(E) for 946 fusion reactions involving stable and neutron-rich isotopes of C, O, Ne, and Mg for center-of-mass energies E varying from 2 MeV to 18-30 MeV (covering the range below and above the Coulomb barrier). We have parameterized the energy dependence S(E) by an accurate universal 9-parameter analytic expression and present tables of fit parameters for all the reactions. We also discuss the reduced 3-parameter version of our fit which is highly accurate at energies below the Coulomb barrier, and outline the procedure for calculating the reaction rates. The results can be easily converted to thermonuclear or pycnonuclear reaction rates to simulate various nuclear burning phenomena, in particular, stellar burning at high temperatures and nucleosynthesis in high density environments.Comment: 30 pages including 11 tables, 4 figures, ADNDT, accepte

ABCD transfer matrix model of Gaussian beam propagation in plano-concave optical microresonators

Plano-concave optical microresonators (PCMRs) are optical microcavities formed of one planar and one concave mirror separated by a spacer. PCMRs illuminated by Gaussian laser beams are used as sensors and filters in fields including quantum electrodynamics, temperature sensing, and photoacoustic imaging. To predict characteristics such as the sensitivity of PCMRs, a model of Gaussian beam propagation through PCMRs based on the ABCD matrix method was developed. To validate the model, interferometer transfer functions (ITFs) calculated for a range of PCMRs and beams were compared to experimental measurements. A good agreement was observed, suggesting the model is valid. It could therefore constitute a useful tool for designing and evaluating PCMR systems in various fields. The computer code implementing the model has been made available online