Determination of Equilibrium Constants for the Reaction between Acetone and HO_2 Using Infrared Kinetic Spectroscopy

The reaction between the hydroperoxy radical, HO_2, and acetone may play an important role in acetone removal and the budget of HO_x radicals in the upper troposphere. We measured the equilibrium constants of this reaction over the temperature range of 215–272 K at an overall pressure of 100 Torr using a flow tube apparatus and laser flash photolysis to produce HO_2. The HO_2 concentration was monitored as a function of time by near-IR diode laser wavelength modulation spectroscopy. The resulting [HO_2] decay curves in the presence of acetone are characterized by an immediate decrease in initial [HO_2] followed by subsequent decay. These curves are interpreted as a rapid (<100 μs) equilibrium reaction between acetone and the HO_2 radical that occurs on time scales faster than the time resolution of the apparatus, followed by subsequent reactions. This separation of time scales between the initial equilibrium and ensuing reactions enabled the determination of the equilibrium constant with values ranging from 4.0 × 10^(–16) to 7.7 × 10^(–1)8 cm^3 molecule^(–1) for T = 215–272 K. Thermodynamic parameters for the reaction determined from a second-law fit of our van’t Hoff plot were Δ_(r)H°_(245) = −35.4 ± 2.0 kJ mol^(–1) and Δ_(r)S°_(245) = −88.2 ± 8.5 J mol^(–1) K^(–1). Recent ab initio calculations predict that the reaction proceeds through a prereactive hydrogen-bonded molecular complex (HO_2–acetone) with subsequent isomerization to a hydroxy–peroxy radical, 2-hydroxyisopropylperoxy (2-HIPP). The calculations differ greatly in the energetics of the complex and the peroxy radical, as well as the transition state for isomerization, leading to significant differences in their predictions of the extent of this reaction at tropospheric temperatures. The current results are consistent with equilibrium formation of the hydrogen-bonded molecular complex on a short time scale (100 μs). Formation of the hydrogen-bonded complex will have a negligible impact on the atmosphere. However, the complex could subsequently isomerize to form the 2-HIPP radical on longer time scales. Further experimental studies are needed to assess the ultimate impact of the reaction of HO_2 and acetone on the atmosphere

Correlation between Subjective Nasal Patency and Intranasal Airflow Distribution

Objectives (1) Analyze the relationship between intranasal airflow distribution and subjective nasal patency in healthy and nasal airway obstruction (NAO) cohorts using computational fluid dynamics (CFD). (2) Determine whether intranasal airflow distribution is an important objective measure of airflow sensation that should be considered in future NAO virtual surgery planning. Study Design Cross-sectional. Setting Academic tertiary medical center and academic dental clinic. Subjects and Methods Three-dimensional models of nasal anatomy were created based on computed tomography scans of 15 patients with NAO and 15 healthy subjects and used to run CFD simulations of nasal airflow and mucosal cooling. Subjective nasal patency was quantified with a visual analog scale (VAS) and the Nasal Obstruction Symptom Evaluation (NOSE). Regional distribution of nasal airflow (inferior, middle, and superior) was quantified in coronal cross sections in the narrowest nasal cavity. The Pearson correlation coefficient was used to quantify the correlation between subjective scores and regional airflows. Results Healthy subjects had significantly higher middle airflow than patients with NAO. Subjective nasal patency had no correlation with inferior and superior airflows but a high correlation with middle airflow (|r| = 0.64 and |r| = 0.76 for VAS and NOSE, respectively). Anterior septal deviations tended to shift airflow inferiorly, reducing middle airflow and reducing mucosal cooling in some patients with NAO. Conclusion Reduced middle airflow correlates with the sensation of nasal obstruction, possibly due to a reduction in mucosal cooling in this region. Further research is needed to elucidate the role of intranasal airflow distribution in the sensation of nasal airflow

Stabilizer Quantum Error Correction with Qubus Computation

In this paper we investigate stabilizer quantum error correction codes using controlled phase rotations of strong coherent probe states. We explicitly describe two methods to measure the Pauli operators which generate the stabilizer group of a quantum code. First, we show how to measure a Pauli operator acting on physical qubits using a single coherent state with large average photon number, displacement operations, and photon detection. Second, we show how to measure the stabilizer operators fault-tolerantly by the deterministic preparation of coherent cat states along with one-bit teleportations between a qubit-like encoding of coherent states and physical qubits.Comment: 4 pages, 5 figure

Universally Sloppy Parameter Sensitivities in Systems Biology

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring \emph{in vivo} biochemical parameters is difficult, and collectively fitting them to other data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a `sloppy' spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.Comment: Submitted to PLoS Computational Biology. Supplementary Information available in "Other Formats" bundle. Discussion slightly revised to add historical contex