2,109 research outputs found
Global Continuous Optimization with Error Bound and Fast Convergence
This paper considers global optimization with a black-box unknown objective
function that can be non-convex and non-differentiable. Such a difficult
optimization problem arises in many real-world applications, such as parameter
tuning in machine learning, engineering design problem, and planning with a
complex physics simulator. This paper proposes a new global optimization
algorithm, called Locally Oriented Global Optimization (LOGO), to aim for both
fast convergence in practice and finite-time error bound in theory. The
advantage and usage of the new algorithm are illustrated via theoretical
analysis and an experiment conducted with 11 benchmark test functions. Further,
we modify the LOGO algorithm to specifically solve a planning problem via
policy search with continuous state/action space and long time horizon while
maintaining its finite-time error bound. We apply the proposed planning method
to accident management of a nuclear power plant. The result of the application
study demonstrates the practical utility of our method
Onsager's missing steps retraced
Onsager's paper on phase transition and phase coexistence in anisotropic
colloidal systems is a landmark in the theory of lyotropic liquid crystals.
However, an uncompromising scrutiny of Onsager's original derivation reveals
that it would be rigorously valid only for ludicrous values of the system's
number density (of the order of the reciprocal of the number of particles)
Based on Penrose's tree identity and an appropriate variant of the mean-field
approach for purely repulsive, hard-core interactions, our theory shows that
Onsager's theory is indeed valid for a reasonable range of densities
Dimensional Analysis and the Time Required to Urinate
According to the recently discovered 'Law of Urination', mammals, ranging in
size from mice to elephants, take, on the average, 21s to urinate. We attempt
to gain insights into the physical processes responsible for this uniformity
using simple dimensional analysis. We assume that the biological apparatus for
urination in mammals simply scales with linear size, and consider the scenarios
where the driving force is gravity or elasticity, and where the response is
dominated by inertia or viscosity. We ask how the time required for urination
depends on the length scale, and find that for the time to be independent of
body size, the dominant driving force must be elasticity, and the dominant
response viscosity. Our note demonstrates that dimensional analysis can indeed
readily give insights into complex physical and biological processes
Preparation and assessment of ketamine hydrogels for prolonged transdermal anaesthesia
Purpose: To formulate and assess thermoresponsive ketamine hydrogels for prolonged transdermal analgesia/anaesthesia.Methods: Thermoresponsive ketamine hydrogels were prepared from chitosan (CTS) and poloxamer 407. Four different formulations (2 formulations of ketamine with 1 and 2 % w/w CTS and 2 formulations with 10 and 15 % w/w ploxamer 407) were assessed for pH, spreadability, drug content, viscosity, in vitro permeation/diffusion, in vivo skin irritancy, and in vivo analgesia (using the hot plate/writhing method in Wistar rats).Results: The formulations had a high drug content (96.12 ± 1.24 to 98.49 ± 0.07 %) with good spreadability. They showed prolonged drug release/permeation of ketamine across the skin, ranging from 81.23 to 98.28 %, and were non-irritating to the denuded skin of Wistar rats with no erythema or oedema after 24 h. The preparation showed effective analgesia that lasted 24 to 30 h. In the writhing test, CTS hydrogels showed stronger analgesia (60.26 – 58.97 %) than those made with poloxamerbased hydrogels (56.41 and 53.85 %). Compared to the activity shown by the standard, lidocaine (which produced 62.82 % analgesia), the effect of the test formulations seem good for probable therapeutic use. Using the hot plate method, the poloxamer-based hydrogels showed more prolonged analgesia than the CTS-based hydrogels.Conclusion: Ketamine hydrogels of CTS and poloxamer may be useful for prolonged analgesia in neuropathic pain and local anaesthesia in minor surgeries.Keywords: Ketamine, Chitosan, Poloxamer, Thermoresponsive hydrogel, Transdermal, Skin permeatio
Contributions of Repulsive and Attractive Interactions to Nematic Order
Both repulsive and attractive molecular interactions can be used to explain
the onset of nematic order. The object of this paper is to combine these two
nematogenic molecular interactions in a unified theory. This attempt is not
unprecedented; what is perhaps new is the focus on the understanding of
nematics in the high density limit. There, the orientational probability
distribution is shown to exhibit a unique feature: it has compact support on
configuration space. As attractive interactions are turned on, the behavior
changes, and at a critical attractive interaction strength, thermotropic
behavior of the Maier-Saupe type is attained.Comment: 14 pages, 4 figure
Interaction-aware Kalman Neural Networks for Trajectory Prediction
Forecasting the motion of surrounding obstacles (vehicles, bicycles,
pedestrians and etc.) benefits the on-road motion planning for intelligent and
autonomous vehicles. Complex scenes always yield great challenges in modeling
the patterns of surrounding traffic. For example, one main challenge comes from
the intractable interaction effects in a complex traffic system. In this paper,
we propose a multi-layer architecture Interaction-aware Kalman Neural Networks
(IaKNN) which involves an interaction layer for resolving high-dimensional
traffic environmental observations as interaction-aware accelerations, a motion
layer for transforming the accelerations to interaction aware trajectories, and
a filter layer for estimating future trajectories with a Kalman filter network.
Attributed to the multiple traffic data sources, our end-to-end trainable
approach technically fuses dynamic and interaction-aware trajectories boosting
the prediction performance. Experiments on the NGSIM dataset demonstrate that
IaKNN outperforms the state-of-the-art methods in terms of effectiveness for
traffic trajectory prediction.Comment: 8 pages, 4 figures, Accepted for IEEE Intelligent Vehicles Symposium
(IV) 202
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