4,128 research outputs found
Total syntheses of conformationally-locked difluorinated pentopyranose analogues and a pentopyranosyl phosphate mimetic
Trifluoroethanol has been elaborated, via a telescoped sequence involving a metalated difluoroenol, a difluoroallylic alcohol, [2,3]-Wittig rearrangement, and ultimately an RCM reaction and requiring minimal intermediate purification, to a number of cyclooctenone intermediates. Epoxidation of these intermediates followed by transannular ring opening or dihydroxylation, then transannular hemiacetalization delivers novel bicyclic analogues of pentopyranoses, which were elaborated (in one case) to an analogue of a glycosyl phosphate
Separation index of graphs and stacked 2-spheres
In 1987, Kalai proved that stacked spheres of dimension are
characterised by the fact that they attain equality in Barnette's celebrated
Lower Bound Theorem. This result does not extend to dimension . In this
article, we give a characterisation of stacked -spheres using what we call
the {\em separation index}. Namely, we show that the separation index of a
triangulated -sphere is maximal if and only if it is stacked. In addition,
we prove that, amongst all -vertex triangulated -spheres, the separation
index is {\em minimised} by some -vertex flag sphere for .
Furthermore, we apply this characterisation of stacked -spheres to settle
the outstanding -dimensional case of the Lutz-Sulanke-Swartz conjecture that
"tight-neighbourly triangulated manifolds are tight". For dimension ,
the conjecture has already been proved by Effenberger following a result of
Novik and Swartz.Comment: Some typos corrected, to appear in "Journal of Combinatorial Theory
A
Ab initio calculation of the anomalous Hall conductivity by Wannier interpolation
The intrinsic anomalous Hall effect in ferromagnets depends on subtle
spin-orbit-induced effects in the electronic structure, and recent ab-initio
studies found that it was necessary to sample the Brillouin zone at millions of
k-points to converge the calculation. We present an efficient first-principles
approach for computing the anomalous Hall conductivity. We start out by
performing a conventional electronic-structure calculation including spin-orbit
coupling on a uniform and relatively coarse k-point mesh. From the resulting
Bloch states, maximally-localized Wannier functions are constructed which
reproduce the ab-initio states up to the Fermi level. The Hamiltonian and
position-operator matrix elements, needed to represent the energy bands and
Berry curvatures, are then set up between the Wannier orbitals. This completes
the first stage of the calculation, whereby the low-energy ab-initio problem is
transformed into an effective tight-binding form. The second stage only
involves Fourier transforms and unitary transformations of the small matrices
set up in the first stage. With these inexpensive operations, the quantities of
interest are interpolated onto a dense k-point mesh and used to evaluate the
anomalous Hall conductivity as a Brillouin zone integral. The present scheme,
which also avoids the cumbersome summation over all unoccupied states in the
Kubo formula, is applied to bcc Fe, giving excellent agreement with
conventional, less efficient first-principles calculations. Remarkably, we find
that more than 99% of the effect can be recovered by keeping a set of terms
depending only on the Hamiltonian matrix elements, not on matrix elements of
the position operator.Comment: 16 pages, 7 figure
Improving clinical quality indicators through electronic health records: it takes more than just a reminder.
Neural Network Control of Spark Ignition Engines with High EGR Levels
Research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% to 25% exhaust gas recirculation (EGR) in spark ignition (SI) engines [1]. However under high EGR levels the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance. A suite of neural network (NN)-based output feedback controllers with and without reinforcement learning is developed to control the SI engine at high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate control loop was designed for controlling EGR levels. The neural network controllers consists of three NN: a) A NN observer to estimate the states of the engine such as total fuel and air; b) a second NN for generating virtual input; and c) a third NN for generating actual control input. For reinforcement learning, an additional NN is used as the critic. The stability analysis of the closed loop system is given and the boundedness of all signals is ensured without separation principle. Online training is used for the adaptive NN and no offline training phase is needed. Experimental results obtained by testing the controller on a research engine indicate an 80% drop of NOx from stoichiometric levels using 10% EGR. Moreover, unburned hydrocarbons drop by 25% due to NN control as compared to the uncontrolled scenario
Neural Network Controller Development and Implementation for Spark Ignition Engines with High EGR Levels
Past research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate control loop was designed for controlling EGR levels. The stability analysis of the closed-loop system is given and the boundedness of the control input is demonstrated by relaxing separation principle, persistency of excitation condition, certainty equivalence principle, and linear in the unknown parameter assumptions. Online training is used for the adaptive NN and no offline training phase is needed. This online learning feature and model-free approach is used to demonstrate the applicability of the controller on a different engine with minimal effort. Simulation results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller when implemented on an engine model that has been validated experimentally. For a single cylinder research engine fitted with a modern four-valve head (Ricardo engine), experimental results at 15% EGR indicate that cyclic dispersion was reduced 33% by the controller, an improvement of fuel efficiency by 2%, and a 90% drop in NOx from stoichiometric operation without EGR was observed. Moreover, unburned hydrocarbons (uHC) drop by 6% due to NN control as compared to the uncontrolled scenario due to the drop in cyclic dispersion. Similar performance was observed with the controller on a different engine
Radiation-Pressure-Mediated Control of an Optomechanical Cavity
We describe and demonstrate a method to control a detuned movable-mirror
Fabry-Perot cavity using radiation pressure in the presence of a strong optical
spring. At frequencies below the optical spring resonance, self-locking of the
cavity is achieved intrinsically by the optomechanical (OM) interaction between
the cavity field and the movable end mirror. The OM interaction results in a
high rigidity and reduced susceptibility of the mirror to external forces.
However, due to a finite delay time in the cavity, this enhanced rigidity is
accompanied by an anti-damping force, which destabilizes the cavity. The cavity
is stabilized by applying external feedback in a frequency band around the
optical spring resonance. The error signal is sensed in the amplitude
quadrature of the transmitted beam with a photodetector. An amplitude modulator
in the input path to the cavity modulates the light intensity to provide the
stabilizing radiation pressure force
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Plxnd1 Expression in Thymocytes Regulates Their Intrathymic Migration While That in Thymic Endothelium Impacts Medullary Topology
An important role for plexinD1 in thymic development is inferred from studies of germline Plxnd1 knockout (KO) mice where mislocalized CD69+ thymocytes as well as ectopic thymic subcapsular medullary structures were observed. Given embryonic lethality of the Plxnd1−/− genotype, fetal liver transplantation was employed in these prior analyses. Such embryonic hematopoietic reconstitution may have transferred Plxnd1 KO endothelial and/or epithelial stem cells in addition to Plxnd1 KO lymphoid progenitors, thereby contributing to that phenotype. Here we use Plxnd1flox/flox mice crossed to pLck-Cre, pKeratin14-Cre, or pTek-Cre transgenic animals to create cell-type specific conditional knockout (CKO) lines involving thymocytes (D1ThyCKO), thymic epithelium (D1EpCKO), and thymic endothelium (D1EnCKO), respectively. These CKOs allowed us to directly assess the role of plexinD1 in each lineage. Loss of plexinD1 expression on double positive (DP) thymocytes leads to their aberrant migration and cortical retention after TCR-mediated positive selection. In contrast, ectopic medulla formation is a consequence of loss of plexinD1 expression on endothelial cells, in turn linked to dysregulation of thymic angiogenesis. D1EpCKO thymi manifest neither abnormality. Collectively, our findings underscore the non-redundant roles for plexinD1 on thymocytes and endothelium, including the dynamic nature of medulla formation resulting from crosstalk between these thymic cellular components
Association of computed tomographic leg muscle characteristics with lower limb and cardiovascular events in patients with peripheral artery disease
Background
Poor lower extremity physical performance is an independent predictor of unfavorable outcome in patients with peripheral artery disease (PAD); however, few studies have assessed muscle characteristics on imaging directly.
Method and Results
A novel 3‐dimensional semi‐automated protocol was developed to estimate leg muscle volume and density (mean attenuation) from computed tomography images. Patients with PAD who underwent a lower extremity computed tomography scan at a tertiary vascular surgery center were included, and were followed up using hospital records and linked data as part of a retrospective cohort study. The primary outcomes were lower limb events (major amputation or peripheral revascularization) and cardiovascular events (myocardial infarction, stroke, or cardiovascular death). Two hundred and twenty‐three patients with PAD were included (median age 69.0 years; 73% men) and followed for a median of 4.9 [2.6–7.0] years. During this time there were 99 index lower limb events and 97 cardiovascular events. Low leg muscle density was associated with increased risk of lower limb (rate ratio 1.41 [1.11–1.80] per SD reduction) and cardiovascular events (rate ratio 1.60 [1.29–1.99] per SD reduction). Low muscle density remained an independent predictor of cardiovascular (but not lower limb) events, after adjusting for age, sex, traditional cardiovascular risk factors, and angiographic PAD severity (rate ratio 1.39 [1.09–1.77] per lower SD). In contrast, leg muscle volume was not associated with outcomes after adjusting for risk factors and PAD severity.
Conclusions
Low leg muscle density, but not volume, is a strong, independent predictor of major cardiovascular events among people with PAD. Further research is needed to understand the mechanisms underlying these associations
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