A comparison of GC-FID and PTR-MS toluene measurements in ambient air under conditions of enhanced monoterpene loading

Toluene was measured using both a gas chromatographic system (GC), with a flame ionization detector (FID), and a proton transfer reaction-mass spectrometer (PTR-MS) at the AIRMAP atmospheric monitoring station Thompson Farm (THF) in rural Durham, NH during the summer of 2004. Simultaneous measurements of monoterpenes, including alpha- and beta-pinene, camphene, Delta(3)-carene, and d-limonene, by GC-FID demonstrated large enhancements in monoterpene mixing ratios relative to toluene, with median and maximum enhancement ratios of similar to 2 and similar to 30, respectively. A detailed comparison between the GC-FID and PTR-MS toluene measurements was conducted to test the specificity of PTR-MS for atmospheric toluene measurements under conditions often dominated by biogenic emissions. We derived quantitative estimates of potential interferences in the PTR-MS toluene measurements related to sampling and analysis of monoterpenes, including fragmentation of the monoterpenes and some of their primary carbonyl oxidation products via reactions with H(3)O(+), O(2)(+) and NO(+) in the PTR-MS drift tube. The PTR-MS and GC-FID toluene measurements were in good quantitative agreement and the two systems tracked one another well from the instrumental limits of detection to maximum mixing ratios of similar to 0.5 ppbv. A correlation plot of the PTR-MS versus GC-FID toluene measurements was described by the least squares regression equation y=(1.13 +/- 0.02)x-(0.008 +/- 0.003) ppbv, suggesting a small similar to 13% positive bias in the PTR-MS measurements. The bias corresponded with a similar to 0.055 ppbv difference at the highest measured toluene level. The two systems agreed quantitatively within the combined 1 sigma measurement precisions for 60% of the measurements. Discrepancies in the measured mixing ratios were not well correlated with enhancements in the monoterpenes. Better quantitative agreement between the two systems was obtained by correcting the PTR-MS measurements for contributions from monoterpene fragmentation in the PTR-MS drift tube; however, the improvement was minor (\u3c10%). Interferences in the PTRMS measurements from fragmentation of the monoterpene oxidation products pinonaldehyde, caronaldehyde and alpha-pinene oxide were also likely negligible. A relatively large and variable toluene background in the PTR-MS instrument likely drove the measurement bias; however, the precise contribution was difficult to accurately quantify and thus was not corrected for in this analysis. The results from THF suggest that toluene can be reliably quantified by PTR-MS using our operating conditions (drift tube pressure, temperature and voltage of 2.0 mbar, 45 degrees C and 600V, respectively) under the ambient compositions probed. This work extends the range of field conditions under which PTR-MS validation studies have been conducted

When the path is never shortest: a reality check on shortest path biocomputation

Shortest path problems are a touchstone for evaluating the computing performance and functional range of novel computing substrates. Much has been published in recent years regarding the use of biocomputers to solve minimal path problems such as route optimisation and labyrinth navigation, but their outputs are typically difficult to reproduce and somewhat abstract in nature, suggesting that both experimental design and analysis in the field require standardising. This chapter details laboratory experimental data which probe the path finding process in two single-celled protistic model organisms, Physarum polycephalum and Paramecium caudatum, comprising a shortest path problem and labyrinth navigation, respectively. The results presented illustrate several of the key difficulties that are encountered in categorising biological behaviours in the language of computing, including biological variability, non-halting operations and adverse reactions to experimental stimuli. It is concluded that neither organism examined are able to efficiently or reproducibly solve shortest path problems in the specific experimental conditions that were tested. Data presented are contextualised with biological theory and design principles for maximising the usefulness of experimental biocomputer prototypes.Comment: To appear in: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

Geometric quantum computation using fictitious spin- 1/2 subspaces of strongly dipolar coupled nuclear spins

Geometric phases have been used in NMR, to implement controlled phase shift gates for quantum information processing, only in weakly coupled systems in which the individual spins can be identified as qubits. In this work, we implement controlled phase shift gates in strongly coupled systems, by using non-adiabatic geometric phases, obtained by evolving the magnetization of fictitious spin-1/2 subspaces, over a closed loop on the Bloch sphere. The dynamical phase accumulated during the evolution of the subspaces, is refocused by a spin echo pulse sequence and by setting the delay of transition selective pulses such that the evolution under the homonuclear coupling makes a complete $2\pi$ rotation. A detailed theoretical explanation of non-adiabatic geometric phases in NMR is given, by using single transition operators. Controlled phase shift gates, two qubit Deutsch-Jozsa algorithm and parity algorithm in a qubit-qutrit system have been implemented in various strongly dipolar coupled systems obtained by orienting the molecules in liquid crystal media.Comment: 37 pages, 17 figure

Robust constrained model predictive control based on parameter-dependent Lyapunov functions

The problem of robust constrained model predictive control (MPC) of systems with polytopic uncertainties is considered in this paper. New sufficient conditions for the existence of parameter-dependent Lyapunov functions are proposed in terms of linear matrix inequalities (LMIs), which will reduce the conservativeness resulting from using a single Lyapunov function. At each sampling instant, the corresponding parameter-dependent Lyapunov function is an upper bound for a worst-case objective function, which can be minimized using the LMI convex optimization approach. Based on the solution of optimization at each sampling instant, the corresponding state feedback controller is designed, which can guarantee that the resulting closed-loop system is robustly asymptotically stable. In addition, the feedback controller will meet the specifications for systems with input or output constraints, for all admissible time-varying parameter uncertainties. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques

Realization of quantum process tomography in NMR

Quantum process tomography is a procedure by which the unknown dynamical evolution of an open quantum system can be fully experimentally characterized. We demonstrate explicitly how this procedure can be implemented with a nuclear magnetic resonance quantum computer. This allows us to measure the fidelity of a controlled-not logic gate and to experimentally investigate the error model for our computer. Based on the latter analysis, we test an important assumption underlying nearly all models of quantum error correction, the independence of errors on different qubits.Comment: 8 pages, 7 EPS figures, REVTe

Contribution analysis of a Bolivian innovation grant fund: mixing methods to verify relevance, efficiency and effectiveness

We used contribution analysis to verify the key assumption in the intervention logic of an innovation fund in Bolivia directed to economic farmer organisations to develop value-added activities. We focused the research on three sub-components of the intervention logic: relevance of the farmer groups for local economic development, effectiveness of the fund in strengthening these group, and efficiency of the grant allocation mechanism. We used a case-based comparative analysis to assess effectiveness: improved market access for members, strengthened organisational capacities and the capacity to pay organisational costs. We showed that the grants to already well-endowed organisations were particularly unsuccessful

Optimal low-thrust trajectories to asteroids through an algorithm based on differential dynamic programming

In this paper an optimisation algorithm based on Differential Dynamic Programming is applied to the design of rendezvous and fly-by trajectories to near Earth objects. Differential dynamic programming is a successive approximation technique that computes a feedback control law in correspondence of a fixed number of decision times. In this way the high dimensional problem characteristic of low-thrust optimisation is reduced into a series of small dimensional problems. The proposed method exploits the stage-wise approach to incorporate an adaptive refinement of the discretisation mesh within the optimisation process. A particular interpolation technique was used to preserve the feedback nature of the control law, thus improving robustness against some approximation errors introduced during the adaptation process. The algorithm implements global variations of the control law, which ensure a further increase in robustness. The results presented show how the proposed approach is capable of fully exploiting the multi-body dynamics of the problem; in fact, in one of the study cases, a fly-by of the Earth is scheduled, which was not included in the first guess solution

A gas chromatographic instrument for measurement of hydrogen cyanide in the lower atmosphere

A gas-chromatographic (GC) instrument was developed for measuring hydrogen cyanide (HCN) in the lower atmosphere. The main features of the instrument are (1) a cryogen-free cooler for sample dehumidification and enrichment, (2) a porous polymer PLOT column for analyte separation, (3) a flame thermionic detector (FTD) for sensitive and selective detection, and (4) a dynamic dilution system for calibration. We deployed the instrument for a ∼4 month period from January–June, 2010 at the AIRMAP atmospheric monitoring station Thompson Farm 2 (THF2) in rural Durham, NH. A subset of measurements made during 3–31 March is presented here with a detailed description of the instrument features and performance characteristics. The temporal resolution of the measurements was ~20 min, with a 75 s sample capture time. The 1σ measurement precision was <10% and the instrument response linearity was excellent on a calibration scale of 0.10–0.75 ppbv (±5%). The estimated method detection limit (MDL) and accuracy were 0.021 ppbv and 15%, respectively. From 3–31 March 2010, ambient HCN mixing ratios ranged from 0.15–1.0 ppbv (±15%), with a mean value of 0.36 ± 0.16 ppbv (1σ). The approximate mean background HCN mixing ratio of 0.20 ± 0.04 ppbv appeared to agree well with tropospheric column measurements reported previously. The GC-FTD HCN measurements were strongly correlated with acetonitrile (CH<sub>3</sub>CN) measured concurrently with a proton transfer-reaction mass spectrometer (PTR-MS), as anticipated given our understanding that the nitriles share a common primary biomass burning source to the global atmosphere. The nitriles were overall only weakly correlated with carbon monoxide (CO), which is reasonable considering the greater diversity of sources for CO. However, strong correlations with CO were observed on several nights under stable atmospheric conditions and suggest regional combustion-based sources for the nitriles. These results demonstrate that the GC-FTD instrument is capable of making long term, in-situ measurements of HCN in the lower atmosphere. To date, similar measurements have not been performed, yet they are critically needed to (1) better evaluate the regional scale distribution of HCN in the atmosphere and (2) discern the influence of biomass burning on surface air composition in remote regions

A comparison of GC-FID and PTR-MS toluene measurements in ambient air under conditions of enhanced monoterpene loading

Toluene was measured using both a gas chromatographic system (GC), with a flame ionization detector (FID), and a proton transfer reaction-mass spectrometer (PTR-MS) at the AIRMAP atmospheric monitoring station Thompson Farm (THF) in rural Durham, NH during the summer of 2004. Simultaneous measurements of monoterpenes, including α- and β-pinene, camphene, Δ <sup>3</sup>-carene, and <i>d</i>-limonene, by GC-FID demonstrated large enhancements in monoterpene mixing ratios relative to toluene, with median and maximum enhancement ratios of ~2 and ~30, respectively. A detailed comparison between the GC-FID and PTR-MS toluene measurements was conducted to test the specificity of PTR-MS for atmospheric toluene measurements under conditions often dominated by biogenic emissions. We derived quantitative estimates of potential interferences in the PTR-MS toluene measurements related to sampling and analysis of monoterpenes, including fragmentation of the monoterpenes and some of their primary carbonyl oxidation products via reactions with H<sub>3</sub>O<sup>+</sup>, O<sub>2</sub><sup>+</sup> and NO<sup>+</sup> in the PTR-MS drift tube. The PTR-MS and GC-FID toluene measurements were in good quantitative agreement and the two systems tracked one another well from the instrumental limits of detection to maximum mixing ratios of ~0.5 ppbv. A correlation plot of the PTR-MS versus GC-FID toluene measurements was described by the least squares regression equation <i>y</i>=(1.13± 0.02)<i>x</i>−(0.008±0.003) ppbv, suggesting a small ~13% positive bias in the PTR-MS measurements. The bias corresponded with a ~0.055 ppbv difference at the highest measured toluene level. The two systems agreed quantitatively within the combined 1σ measurement precisions for 60% of the measurements. Discrepancies in the measured mixing ratios were not well correlated with enhancements in the monoterpenes. Better quantitative agreement between the two systems was obtained by correcting the PTR-MS measurements for contributions from monoterpene fragmentation in the PTR-MS drift tube; however, the improvement was minor (<10%). Interferences in the PTR-MS measurements from fragmentation of the monoterpene oxidation products pinonaldehyde, caronaldehyde and α-pinene oxide were also likely negligible. A relatively large and variable toluene background in the PTR-MS instrument likely drove the measurement bias; however, the precise contribution was difficult to accurately quantify and thus was not corrected for in this analysis. The results from THF suggest that toluene can be reliably quantified by PTR-MS using our operating conditions (drift tube pressure, temperature and voltage of 2.0 mbar, 45 °C and 600 V, respectively) under the ambient compositions probed. This work extends the range of field conditions under which PTR-MS validation studies have been conducted

Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control

Decentralized multi-agent control has broad applications, ranging from multi-robot cooperation to distributed sensor networks. In decentralized multi-agent control, systems are complex with unknown or highly uncertain dynamics, where traditional model-based control methods can hardly be applied. Compared with model-based control in control theory, deep reinforcement learning (DRL) is promising to learn the controller/policy from data without the knowing system dynamics. However, to directly apply DRL to decentralized multi-agent control is challenging, as interactions among agents make the learning environment non-stationary. More importantly, the existing multi-agent reinforcement learning (MARL) algorithms cannot ensure the closed-loop stability of a multi-agent system from a control-theoretic perspective, so the learned control polices are highly possible to generate abnormal or dangerous behaviors in real applications. Hence, without stability guarantee, the application of the existing MARL algorithms to real multi-agent systems is of great concern, e.g., UAVs, robots, and power systems, etc. In this paper, we aim to propose a new MARL algorithm for decentralized multi-agent control with a stability guarantee. The new MARL algorithm, termed as a multi-agent soft-actor critic (MASAC), is proposed under the well-known framework of "centralized-training-with-decentralized-execution". The closed-loop stability is guaranteed by the introduction of a stability constraint during the policy improvement in our MASAC algorithm. The stability constraint is designed based on Lyapunov's method in control theory. To demonstrate the effectiveness, we present a multi-agent navigation example to show the efficiency of the proposed MASAC algorithm.Comment: Accepted to The 2nd International Conference on Distributed Artificial Intelligenc