Reinforcement Learning with Quantum Variational Circuits

The development of quantum computational techniques has advanced greatly in recent years, parallel to the advancements in techniques for deep reinforcement learning. This work explores the potential for quantum computing to facilitate reinforcement learning problems. Quantum computing approaches offer important potential improvements in time and space complexity over traditional algorithms because of its ability to exploit the quantum phenomena of superposition and entanglement. Specifically, we investigate the use of quantum variational circuits, a form of quantum machine learning. We present our techniques for encoding classical data for a quantum variational circuit, we further explore pure and hybrid quantum algorithms for DQN and Double DQN. Our results indicate both hybrid and pure quantum variational circuit have the ability to solve reinforcement learning tasks with a smaller parameter space. These comparison are conducted with two OpenAI Gym environments: CartPole and Blackjack, The success of this work is indicative of a strong future relationship between quantum machine learning and deep reinforcement learning.Comment: Accepted to AIIDE 2020 Updated to better reflect AAAI formattin

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Persistence and Uncertainty in the Academic Career

Understanding how institutional changes within academia may affect the overall potential of science requires a better quantitative representation of how careers evolve over time. Since knowledge spillovers, cumulative advantage, competition, and collaboration are distinctive features of the academic profession, both the employment relationship and the procedures for assigning recognition and allocating funding should be designed to account for these factors. We study the annual production n_{i}(t) of a given scientist i by analyzing longitudinal career data for 200 leading scientists and 100 assistant professors from the physics community. We compare our results with 21,156 sports careers. Our empirical analysis of individual productivity dynamics shows that (i) there are increasing returns for the top individuals within the competitive cohort, and that (ii) the distribution of production growth is a leptokurtic "tent-shaped" distribution that is remarkably symmetric. Our methodology is general, and we speculate that similar features appear in other disciplines where academic publication is essential and collaboration is a key feature. We introduce a model of proportional growth which reproduces these two observations, and additionally accounts for the significantly right-skewed distributions of career longevity and achievement in science. Using this theoretical model, we show that short-term contracts can amplify the effects of competition and uncertainty making careers more vulnerable to early termination, not necessarily due to lack of individual talent and persistence, but because of random negative production shocks. We show that fluctuations in scientific production are quantitatively related to a scientist's collaboration radius and team efficiency.Comment: 29 pages total: 8 main manuscript + 4 figs, 21 SI text + fig

Shedding Light Onto the Nature of Iron Decorated Graphene and Graphite Oxide Nanohybrids for CO₂ Conversion at Atmospheric Pressure

We report on the design and testing of new graphite and graphene oxide‐based extended π‐conjugated synthetic scaffolds for applications in sustainable chemistry transformations. Nanoparticle‐functionalised carbonaceous catalysts for new Fischer Tropsch and Reverse GasWater Shift (RGWS) transformations were prepared: functional graphene oxides emerged from graphite powders via an adapted Hummer's method and subsequently impregnated with uniform‐sized nanoparticles. Then the resulting nanomaterials were imaged by TEM, SEM, EDX, AFM and characterised by IR, XPS and Raman spectroscopies prior to incorporation of Pd(II) promoters and further microscopic and spectroscopic analysis. Newly synthesised 2D and 3D layered nanostructures incorporating carbon‐supported iron oxide nanoparticulate pre‐catalysts were tested, upon hydrogen reduction in situ, for the conversion of CO2 to CO as well as for the selective formation of CH4 and longer chain hydrocarbons. The reduction reaction was also carried out and the catalytic species isolated and fully characterised. The catalytic activity of a graphene oxide‐supported iron oxide pre‐catalyst converted CO2 into hydrocarbons at different temperatures (305, 335, 370 and 405 °C), and its activity compared well with that of the analogues supported on graphite oxide, the 3‐dimensional material precursor to the graphene oxide. Investigation into the use of graphene oxide as a framework for catalysis showed that it has promising activity with respect to reverse gas water shift (RWGS) reaction of CO2 to CO, even at the low levels of catalyst used and under the rather mild conditions employed at atmospheric pressure. Whilst the γ‐Fe2O3 decorated graphene oxide‐based pre‐catalyst displays fairly constant activity up to 405 °C, it was found by GC‐MS analysis to be unstable with respect to decomposition at higher temperatures. The addition of palladium as a promoter increased the activity of the iron functionalised graphite oxide in the RWGS. The activity of graphene oxide supported catalysts was found to be enhanced with respect to that of iron‐functionalised graphite oxide with, or without palladium as a promoter, and comparable to that of Fe@carbon nanotube‐based systems tested under analogous conditions. These results display a significant step forward for the catalytic activity estimations for the iron functionalised and rapidly processable and scalable graphene oxide. The hereby investigated phenomena are of particular relevance for the understanding of the intimate surface morphologies and the potential role of non‐covalent interactions in the iron oxide‐graphene oxide networks, which could inform the design of nano‐materials with performance in future sustainable catalysis applications

Curvature-adapted Remeshing of CAD Surfaces

A common representation of surfaces with complicated topology and geometry is through composite parametric surfaces as is the case for most CAD modelers. A challenging problem is how to generate a mesh of such a surface that well approximates the geometry of the surface, preserves its topology and important geometric features, and contains nicely shaped elements. In this work, we present an optimization-based surface remeshing method that is able to satisfy many of these requirements simultaneously. This method is inspired by the recent work of Levy \ub4 and Bonneel (Proc. 21th International Meshing Roundtable, October 2012), which embeds a smooth surface into a high-dimensional space and remesh it uniformly in that embedding space. Our method works directly in the 3d spaces and uses an embedding space in R6 to evaluate mesh size and mesh quality. It generates a curvatureadapted anisotropic surface mesh that well represents the geometry of the surface with a low number of elements. We illustrate our approach through various examples

The changing environment of conservation conflict: geese and farming in Scotland

Conflict between conservation objectives and human livelihoods is ubiquitous and can be highly damaging, but the processes generating it are poorly understood. Ecological elements are central to conservation conflict, and changes in their dynamics — for instance due to anthropogenic environmental change — are likely to influence the emergence of serious human–wildlife impacts and, consequently, social conflict.  We used mixed-effects models to examine the drivers of historic spatio-temporal dynamics in numbers of Greenland barnacle geese (Branta leucopsis) on the Scottish island of Islay to identify the ecological processes that have shaped the environment in which conflict between goose conservation and agriculture has been triggered.  Barnacle goose numbers on Islay increased from 20,000 to 43,000 between 1987 and 2016. Over the same period, the area of improved grassland increased, the number of sheep decreased and the climate warmed.  Goose population growth was strongly linked to the increasing area of improved grassland, which provided geese with more high quality forage. Changing climatic conditions, particularly warming temperatures on Islay and breeding grounds in Greenland, have also boosted goose numbers.  As the goose population has grown, farms have supported geese more frequently and in larger numbers, with subsequent damaging effects on grassland. The creation of high-quality grassland appears to have largely driven the problem of serious economic damage by geese. Our analysis also reveals the drivers of spatial variation in goose impacts: geese were more likely to occur on farms closer to roosts and those with more improved grassland. However, as geese numbers have increased they have spread to previously less favoured farms.  Synthesis and applications. Our study demonstrates the primary role of habitat modification in the emergence of conflict between goose conservation and agriculture, alongside a secondary role of climate change. Our research illustrates the value of exploring socio-ecological history to understand the processes leading to conservation conflict. In doing so, we identify those elements that are more controllable, such as local habitat management, and less controllable, such as climate change, but which both need to be taken into account when managing conservation conflict

The frontline antibiotic vancomycin induces a zinc starvation response in bacteria by binding to Zn(II).

Vancomycin is a front-line antibiotic used for the treatment of nosocomial infections, particularly those caused by methicillin-resistant Staphylococcus aureus. Despite its clinical importance the global effects of vancomycin exposure on bacterial physiology are poorly understood. In a previous transcriptomic analysis we identified a number of Zur regulon genes which were highly but transiently up-regulated by vancomycin in Streptomyces coelicolor. Here, we show that vancomycin also induces similar zinc homeostasis systems in a range of other bacteria and demonstrate that vancomycin binds to Zn(II) in vitro. This implies that vancomycin treatment sequesters zinc from bacterial cells thereby triggering a Zur-dependent zinc starvation response. The Kd value of the binding between vancomycin and Zn(II) was calculated using a novel fluorometric assay, and NMR was used to identify the binding site. These findings highlight a new biologically relevant aspect of the chemical property of vancomycin as a zinc chelator.This work was supported by funding from the Royal Society, UK (516002.K5877/ROG), the Medical Research Council, UK (G0700141). A.Z. was supported from the Said foundation and Cambridge Trust.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/srep1960

Using Dynamic Oral Dosing of Rifapentine and Rifabutin to Simulate Exposure Profiles of Long-Acting Formulations in a Mouse Model of Tuberculosis Preventive Therapy

Administration of tuberculosis preventive therapy (TPT) to individuals with latent tuberculosis infection is an important facet of global tuberculosis control. The use of long-acting injectable (LAI) drug formulations may simplify and shorten regimens for this indication. Rifapentine and rifabutin have antituberculosis activity and physiochemical properties suitable for LAI formulation, but there are limited data available for determining the target exposure profiles required for efficacy in TPT regimens. The objective of this study was to determine exposure-activity profiles of rifapentine and rifabutin to inform development of LAI formulations for TPT. We used a validated paucibacillary mouse model of TPT in combination with dynamic oral dosing of both drugs to simulate and understand exposure-activity relationships to inform posology for future LAI formulations. This work identified several LAI-like exposure profiles of rifapentine and rifabutin that, if achieved by LAI formulations, could be efficacious as TPT regimens and thus can serve as experimentally determined targets for novel LAI formulations of these drugs. We present novel methodology to understand the exposure-response relationship and inform the value proposition for investment in development of LAI formulations that have utility beyond latent tuberculosis infection

Efficacy and safety of indacaterol 150 μg once-daily in COPD: a double-blind, randomised, 12-week study

<p>Abstract</p> <p>Background</p> <p>Indacaterol is a novel, once-daily (o.d.) inhaled, long-acting <it>β</it>₂-agonist in development for chronic obstructive pulmonary disease (COPD). This 12-week, double-blind study compared the efficacy, safety, and tolerability of indacaterol to that of placebo in patients with moderate-to-severe COPD.</p> <p>Methods</p> <p>Efficacy variables included 24-h trough FEV₁(mean of 23 h 10 min and 23 h 45 min post-dose) at Week 12 (primary endpoint) and after Day 1, and the percentage of COPD days with poor control (i.e., worsening symptoms). Safety was assessed by adverse events (AEs), mean serum potassium and blood glucose, QTc (Fridericia), and vital signs.</p> <p>Results</p> <p>Patients were randomised (n = 416, mean age 63 years) to receive either indacaterol 150 <it>μ</it>g o.d. (n = 211) or placebo (n = 205) via a single-dose dry-powder inhaler; 87.5% completed the study. Trough FEV₁(LSM ± SEM) at Week 12 was 1.48 ± 0.018 L for indacaterol and 1.35 ± 0.019 L for placebo, a clinically relevant difference of 130 ± 24 mL (p < 0.001). Trough FEV₁after one dose was significantly higher with indacaterol than placebo (p < 0.001). Indacaterol demonstrated significantly higher peak FEV₁than placebo, both on Day 1 and at Week 12, with indacaterol-placebo differences (LSM ± SEM) of 190 ± 28 (p < 0.001) and 160 ± 28 mL (p < 0.001), respectively. Standardised AUC measurements for FEV₁(between 5 min and 4 h, 5 min and 1 h, and 1 and 4 h post-dose) at Week 12 were all significantly greater with indacaterol than placebo (p < 0.001), with LSM (± SEM) differences of 170 ± 24, 180 ± 24, and 170 ± 24 mL, respectively. Indacaterol significantly reduced the percentage of days of poor control versus placebo by 22.5% (p < 0.001) and was also associated with significantly reduced use of rescue medication (p < 0.001). The overall rates of AEs were comparable between the groups (indacaterol 49.3%, placebo 46.8%), with the most common AEs being COPD worsening (indacaterol 8.5%, placebo 12.2%) and cough (indacaterol 6.2%, placebo 7.3%). One patient died in the placebo group. Serum potassium and blood glucose levels did not differ significantly between the two groups, and no patient had QTc >500 ms.</p> <p>Conclusions</p> <p>Indacaterol 150 <it>μ</it>g o.d. provided clinically significant and sustained bronchodilation, reduced rescue medication use, and had a safety and tolerability profile similar to placebo.</p> <p>Trial registration</p> <p>NCT00624286</p