PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning

State-of-the-art computer vision algorithms often achieve efficiency by making discrete choices about which hypotheses to explore next. This allows allocation of computational resources to promising candidates, however, such decisions are non-differentiable. As a result, these algorithms are hard to train in an end-to-end fashion. In this work we propose to learn an efficient algorithm for the task of 6D object pose estimation. Our system optimizes the parameters of an existing state-of-the art pose estimation system using reinforcement learning, where the pose estimation system now becomes the stochastic policy, parametrized by a CNN. Additionally, we present an efficient training algorithm that dramatically reduces computation time. We show empirically that our learned pose estimation procedure makes better use of limited resources and improves upon the state-of-the-art on a challenging dataset. Our approach enables differentiable end-to-end training of complex algorithmic pipelines and learns to make optimal use of a given computational budget

Foreign Exchange Markets with Last Look

We examine the Foreign Exchange (FX) spot price spreads with and without Last Look on the transaction. We assume that brokers are risk-neutral and they quote spreads so that losses to latency arbitrageurs (LAs) are recovered from other traders in the FX market. These losses are reduced if the broker can reject, ex-post, loss-making trades by enforcing the Last Look option which is a feature of some trading venues in FX markets. For a given rejection threshold the risk-neutral broker quotes a spread to the market so that her expected profits are zero. When there is only one venue, we find that the Last Look option reduces quoted spreads. If there are two venues we show that the market reaches an equilibrium where traders have no incentive to migrate. The equilibrium can be reached with both venues coexisting, or with only one venue surviving. Moreover, when one venue enforces Last Look and the other one does not, counterintuitively, it may be the case that the Last Look venue quotes larger spreads.Comment: 40 pages, 7 figure

Abstract conceptual feature ratings: the role of emotion, magnitude, and other cognitive domains in the organization of abstract conceptual knowledge.

This study harnessed control ratings of the contribution of different types of information (sensation, action, emotion, thought, social interaction, morality, time, space, quantity, and polarity) to 400 individual abstract and concrete verbal concepts. These abstract conceptual feature (ACF) ratings were used to generate a high dimensional semantic space, from which Euclidean distance measurements between individual concepts were extracted as a metric of the semantic relatedness of those words. The validity of these distances as a marker of semantic relatedness was then tested by evaluating whether they could predict the comprehension performance of a patient with global aphasia on two verbal comprehension tasks. It was hypothesized that if the high-dimensional space generated from ACF control ratings approximates the organization of abstract conceptual space, then words separated by small distances should be more semantically related than words separated by greater distances, and should therefore be more difficult to distinguish for the comprehension-impaired patient, SKO. SKO was significantly worse at identifying targets presented within word pairs with low ACF distances. Response accuracy was not predicted by Latent Semantic Analysis (LSA) cosines, any of the individual feature ratings, or any of the background variables. It is argued that this novel rating procedure provides a window on the semantic attributes of individual abstract concepts, and that multiple cognitive systems may influence the acquisition and organization of abstract conceptual knowledge. More broadly, it is suggested that cognitive models of abstract conceptual knowledge must account for the representation not only of the relationships between abstract concepts but also of the attributes which constitute those individual concepts

Cooperative Lewis pairs based on late transition metals: activation of small molecules by platinum(0) and B(C6F5)3

A Lewis basic platinum(0)–CO complex supported by a diphosphine ligand and B(C6F5)3 act cooperatively, in a manner reminiscent of a frustrated Lewis pair, to activate small molecules such as hydrogen, CO2, and ethene. This cooperative Lewis pair facilitates the coupling of CO and ethene in a new way

Treating asthma: is there a place for leukotriene receptor antagonists?

SummaryAsthma is a chronic disorder, characterized by airway hyperresponsiveness (AHR), airway inflammation and airway remodelling. Evidence has been provided for a relationship between pathophysiology, airway inflammation and remodelling. Moreover, these asthma features have been shown to respond to anti-inflammatory therapy. According to current guidelines, monitoring of asthma is predominantly based on symptoms and lung function data. However, these parameters appeared as poor indices for asthma control. Alternatively, asthma control relates well to exacerbations and (anamnestic) surrogate biomarkers of airway inflammation. Hence, appropriate treatment of asthma should primarily target the airway inflammation.According to current guidelines for asthma management, anti-inflammatory therapy with inhaled corticosteroids (ICS) is the cornerstone in the treatment of persistent asthma. To further optimize asthma control, add-on therapy with long-acting β2-agonists (LABA) or leukotriene receptor antagonists (LTRA) should be combined with low to high doses of ICS. While the first combination focuses on optimal control of symptoms and lung function, the second provides a more complete suppression of the airway inflammation.In this paper we discuss treatment of asthma according to current guidelines versus new insights, addressing practical issues

Alcohol fuels for spark-ignition engines: performance, efficiency, and emission effects at mid to high blend rates for ternary mixtures

This paper follows on from an earlier publication on high-blend-rate binary gasoline-alcohol mixtures and reports results for some equivalent ternary fuels from several investigation streams. In the present work, new findings are presented for high-load operation in a dedicated boosted multi-cylinder engine test facility, for operation in modified production engines, for knock performance in a single-cylinder test engine, and for exhaust particulate emissions at part load using both the prototype multi-cylinder engine and a separate single-cylinder engine. The wide variety of test engines employed have several differences, including their fuel delivery strategies. This range of engine specifications is considered beneficial with regard to the “drop-in fuel” conjecture, since the results presented here bear out the contention, already established in the literature, that when specified according to the known ternary blending rules, such fuels fundamentally perform identically to their binary equivalents in terms of engine performance, and outperform standard gasolines in terms of efficiency. However, in the present work, some differences in particulate emissions performance in direct-injection engines have been found at light load for the tested fuels, with a slight increase in particulate number observed with higher methanol contents than lower. A hypothesis is developed to explain this result but in general it was found that these fuels do not significantly affect PN emissions from such engines. As a result, this investigation supplies further evidence that renewable fuels can be introduced simply into the existing vehicle fleet, with the inherent backwards compatibility that this brings too

Lateral Velocity Gradients in the African Lower Mantle Inferred From Slowness Space Observations of Multipathing

Large low‐velocity provinces (LLVPs) are hypothesized to be purely thermal features or possess some chemical heterogeneity but which exactly remains ambiguous. Regional seismology studies typically use travel time residuals and multipathing identification in the waveforms to infer properties of LLVPs. These studies have not fully analyzed all available information such as measuring the direction and inclination of the arrivals. These measurements would provide more constraints of LLVP properties such as the boundary velocity gradient and help determine their nature. Here, we use array seismology to measure backazimuth (direction) and horizontal slowness (inclination) of arriving waves to identify structures causing multipathing and wavefield perturbation. Following this, we use full‐wavefield forward modeling to estimate the gradients required to produce the observed multipathing. We use SKS and SKKS data from 83 events sampling the African LLVP, which has been extensively studied providing a good comparison to our observations. We find evidence for structures at heights of up to 600 km above the core‐mantle boundary causing multipathing and wavefield perturbation. Forward modeling shows gradients of up to 0.7% δ V s per 100 km (0.0005 km s−1 km−1) can produce multipathing with similar backazimuth and horizontal slowness to our observations. This is an order of magnitude lower than the previous strongest estimates of −3% δ V s per 50 km (0.0044 km s−1 km−1). As this is lower than that predicted for both thermal and thermochemical structures, lateral velocity gradients capable of producing multipathing are not necessarily evidence for a thermochemical nature

Increasing Vaccination Rates of Children up to 24 months old at PMG Milwaukie Family Medicine

Increasing Vaccination Rates of children up to 24 months old at PMG Milwaukie Family Medicine Authors: Justin Ferley DO; Rachel Jackson MD; Aubrey Miller MD; Sebastian Reeve MD; Christelle Serra Van-Brunt DO; Jamie Skreen DO; Jeffrey Sun DO; John Yates MD; Daniel Ruegg MD Introduction: Each year in the US, 42000 adults and 300 children die of vaccine preventable diseases. Yet across the country, clinics – including ours – fall short of the CDC Healthy People 2020 goals of pediatric vaccination rates. This resident-led quality improvement (QI) project aimed to improve our clinic vaccination rates in the under 24mo population. Methods: We identified 3 opportunities for vaccinating children under our clinic current processes: well child visits, medical assistants’ vaccinations visits, and acute care visits. Using a multidisciplinary approach comprising residents, MAs, clinical care coordinators and our nursing quality supervisor, we analyzed our current vaccinations processes and our iterative plan-do-study- cycles (PDSA) included: PDSA #1: standardize our work flow for vaccine reconciliation. PDSA #2: sending personal reminder lebers to patients and overall improving our vaccine recall/ reminder system. PDSA #3: Minimizing provider variation for vaccines given at the 12-18mo WCC. Results: We saw an improvement in our vaccinations rates after personalized reminder letters were sent out, outlining that we do not have a reliable vaccine schedule reminder system. We also noted that different providers created different vaccinations schedules in order to prevent giving 5 vaccines at the same $me – with no system in place to follow on missed vaccination, thus creating missed opportunities and suggesting that we need to implement a clinic-wide vaccine schedule. Conclusion: Our last PDSA cycle was interrupted by current CIVD-19 pandemic. We have however found valuable data to help improve our clinic’s vaccination rates, and plan to continue this project over the next 2 years.https://digitalcommons.psjhealth.org/milwaukie_family/1007/thumbnail.jp