2,506 research outputs found
Effects of particle-size ratio on jamming of binary mixtures
We perform a systematic numerical study of the effects of the particle-size
ratio on the properties of jammed binary mixtures. We find that
changing does not qualitatively affect the critical scaling of the pressure
and coordination number with the compression near the jamming transition, but
the critical volume fraction at the jamming transition varies with .
Moreover, the static structure factor (density correlation) strongly
depends on and shows distinct long wave-length behaviors between large and
small particles. Thus the previously reported behavior of in the
long wave-length limit is only a special case in the limit, and cannot
be simply generalized to jammed systems with .Comment: 5 pages and 4 figures, submitted to Soft Matter, special issue on
Granular and Jammed Material
Is it Too Optimistic to Assume Light Touch Interventions can Improve Educational Workersā Wellbeing? Insights from a Field Randomized Control Trial in Canada
Educator wellbeing has broad implications for students and schools. Current approaches to address this problem are generally resource-intensive. This trial used novel nudges to increase wellbeing and decrease burnout among educators and other school-based faculty. We designed a light touch intervention where T1 received evidence-based wellbeing weekly text messages and T2 received weekly messages plus leadership endorsement emails. We evaluated this intervention in a large-scale three-arm RCT with participants (n=1,155) from K-12 schools in Manitoba, Alberta, and British Columbia. When compared to the control group, we saw no significant difference between the control group and T1 and T2 groups on burnout or wellbeing. The failure of these evidence-based text messages in increasing educatorsā wellbeing and reducing their burnout highlights both the difficulty of addressing this problem and the importance of learning lessons from trials with null results to contribute to our knowledge base of improving educatorsā wellbeing
Pharmacokinetic investigation of dose proportionality with a 24-hour controlled-release formulation of hydromorphone
BACKGROUND: The purpose of this study was investigate the dose proportionality of a novel, once-daily, controlled-release formulation of hydromorphone that utilizes the OROS(Ā® )Push-Pullā¢ osmotic pump technology. METHODS: In an open-label, four-way, crossover study, 32 healthy volunteers were randomized to receive a single dose of OROS(Ā® )hydromorphone 8, 16, 32, and 64 mg, with a 7-day washout period between treatments. Opioid antagonism was provided by three or four doses of naltrexone 50 mg, given at 12-hour intervals pre- and post-OROS(Ā® )hydromorphone dosing. Plasma samples for pharmacokinetic analysis were collected pre-dose and at regular intervals up to 48 hours post-dose (72 hours for the 64-mg dose), and were assayed for hydromorphone concentration to determine peak plasma concentration (C(max)), time at which peak plasma concentration was observed (T(max)), terminal half-life (t(1/2)), and area under the concentration-time curve for zero to time t (AUC(0-t)) and zero to infinity (AUC(0āā)). An analysis of variance (ANOVA) model on untransformed and dose-normalized data for AUC(0-t), AUC(0āā), and C(max )was used to establish dose linearity and proportionality. RESULTS: The study was completed by 31 of 32 subjects. Median T(max )(12.0ā16.0 hours) and mean t(1/2 )(10.6ā11.0 hours) were found to be independent of dose. Regression analyses of C(max), AUC(0ā48), and AUC(0āā )by dose indicated that the relationship was linear (slope, P ā¤ 0.05) and that the intercept did not differ significantly from zero (P > 0.05). Similar analyses with dose-normalized parameters also indicated that the slope did not differ significantly from zero (P > 0.05). CONCLUSION: The pharmacokinetics of OROS(Ā® )hydromorphone are linear and dose proportional for the 8, 16, 32, and 64 mg doses. TRIAL REGISTRATION: Clinical Trials.gov NCT0039895
Functional Characterization and Evolution of the Isotuberculosinol Operon in Mycobacterium Tuberculosis and Related Mycobacteria
Terpenoid metabolites are important to the cellular function, structural integrity, and pathogenesis of the human-specific pathogen Mycobacterium tuberculosis (Mtb). Genetic and biochemical investigations have indicated a role for the diterpenoid isotuberculosinol (isoTb) early in the infection process. There are only two genes (Rv3377c and Rv3378c) required for production of isoTb, yet these are found in what appears to be a five-gene terpenoid/isoprenoid biosynthetic operon. Of the three remaining genes (Rv3379c, Rv3382c, and Rv3383c), previous work has indicated that Rv3379c is an inactive pseudo-gene. Here we demonstrate that Rv3382c and Rv3383c encode biochemically redundant machinery for isoprenoid metabolism, encoding a functional 4-hydroxy-3-methylbut-2-enyl diphosphate reductase (LytB) for isoprenoid precursor production and a geranylgeranyl diphosphate (GGPP) synthase, respectively, for which the Mtb genome contains other functional isozymes (Rv1110 and Rv0562, respectively). These results complete the characterization of the isoTb biosynthetic operon, as well as further elucidating isoprenoid metabolism in Mtb. In addition, we have investigated the evolutionary origin of this operon, revealing Mtb-specific conservation of the diterpene synthase genes responsible for isoTb biosynthesis, which supports our previously advanced hypothesis that isoTb acts as a human-specific pathogenic metabolite and is consistent with the human host specificity of Mtb. Intriguingly, our results revealed that many mycobacteria contain orthologs for both Rv3383c and Rv0562, suggesting a potentially important role for these functionally redundant GGPP synthases in the evolution of terpenoid/isoprenoid metabolism in the mycobacteria
Synthesis of novel polymers of intrinsic microporosity for gas and vapour adsorption
Polymers of intrinsic microporosity (PIMs) are a class of highly porous polymeric materials, within
which the microporosity originates from the inability of the rigid and contorted polymeric chains to
pack efficiently. PIMs exhibit outstanding solution processability, large surface areas and great
structural tunability, which makes them promising materials for a range of applications, such as gas
separation, catalysis and sensors. Furthermore, their highly porous nature, along with gas separation
performances, makes PIMs excellent materials for gas adsorption applications, which includes the
capturing and storage of CO2, and the deactivation of chemical warfare agents (CWAs), as they can
efficiently store a significant volume of adsorbate in their pores, which are flexible due to the lack of a
covalent network structure. Additionally, their macromolecular structures can be tailored to show
special selectivity towards the target gases.
The project described in this thesis explored ways to further enhance the gas adsorption
properties of PIMs, via three approaches. First, the incorporation of additional basic, and nucleophilic
functionality onto PIMs was investigated to induce additional acid-base interactions with acidic gases
such as CO2, and the potential catalytic reactivity towards electrophilic compounds such as
organophosphorus-based CWAs. A PIM containing pyridine units was synthesised, and further
functionalised with amidoxime groups. The effect of the basic and nucleophilic functional groups
incorporation on PIMs were studied by comparing their polymer properties, and performances in areas
such as CO2 adsorption, CWA deactivation, and gas separation of the synthesised polymers against that
of related PIM-1 and AO-PIM-1. Secondly, the synthesis of the extremely bulky and rigid structural unit,
naphthopleiadene (NP), with in-built amine functionalities was explored to enhance the porosity of
PIMs, and to increase the affinity of polar gases such as CO2 towards PIMs. Finally, the synthesis of
some -CF3 containing monomers were attempted. These fluorinated PIMs were expected to minimise
interactions between polymeric chains, thus offering the possibility of altered solubility, and reducing
the impact of weak interchain interactions on the porosity, and further enhance the hydrophobicity of
PIMs to increase their selectivity of the target gas molecules over water vapours
Segmental Tracheal Resection in Advanced Thyroid Cancer Patients
https://openworks.mdanderson.org/sumexp22/1134/thumbnail.jp
Stochastic Variational Inference for Hidden Markov Models
Variational inference algorithms have proven successful for Bayesian analysis
in large data settings, with recent advances using stochastic variational
inference (SVI). However, such methods have largely been studied in independent
or exchangeable data settings. We develop an SVI algorithm to learn the
parameters of hidden Markov models (HMMs) in a time-dependent data setting. The
challenge in applying stochastic optimization in this setting arises from
dependencies in the chain, which must be broken to consider minibatches of
observations. We propose an algorithm that harnesses the memory decay of the
chain to adaptively bound errors arising from edge effects. We demonstrate the
effectiveness of our algorithm on synthetic experiments and a large genomics
dataset where a batch algorithm is computationally infeasible.Comment: Appears in Advances in Neural Information Processing Systems (NIPS),
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