798 research outputs found
Behavioral Analysis of Cuttlefish Traveling Waves and Its Implications for Neural Control
SummaryTraveling waves (from action potential propagation to swimming body motions or intestinal peristalsis) are ubiquitous phenomena in biological systems and yet are diverse in form, function, and mechanism. An interesting such phenomenon occurs in cephalopod skin, in the form of moving pigmentation patterns called “passing clouds” [1]. These dynamic pigmentation patterns result from the coordinated activation of large chromatophore arrays [2]. Here, we introduce a new model system for the study of passing clouds, Metasepia tullbergi, in which wave displays are very frequent and thus amenable to laboratory investigations. The mantle of Metasepia contains four main regions of wave travel, each supporting a different propagation direction. The four regions are not always active simultaneously, but those that are show synchronized activity and maintain a constant wavelength and a period-independent duty cycle, despite a large range of possible periods (from 1.5 s to 10 s). The wave patterns can be superposed on a variety of other ongoing textural and chromatic patterns of the skin. Finally, a traveling wave can even disappear transiently and reappear in a different position (“blink”), revealing ongoing but invisible propagation. Our findings provide useful clues about classes of likely mechanisms for the generation and propagation of these traveling waves. They rule out wave propagation mechanisms based on delayed excitation from a pacemaker [3] but are consistent with two other alternatives, such as coupled arrays of central pattern generators [3] and dynamic attractors on a network with circular topology [4]
Culture Display Rules of Smiling and Personal Well-being: Mutually Reinforcing or Compensatory Phenomena? Polish - Canadian Comparisons
Cultures vary in terms of emotional display rules, which include the expression of satisfaction and dissatisfaction. In Poland there is a norm of negativity, deriving from a culture of complaining (Wojciszke & Baryła, 2005), whereas in Canada, there is a tendency to express happiness (Safdar, Friedlmeier, Matsumoto, Yoo, Kwantes, Kakai, & Shigemasu, E., 2009). In the present research project, norms and values regarding smiling in public situations, norms regarding the affirmation of life and complaining, as well as individual measures of optimism (LOT-R) and well-being (SWLS) were measured among Poles and Canadians. The results showed that the cultural display rules endorsed by Canadian students affirmed smiling and positivity in social life more than those for Polish students. Contrary to expectations, optimism and the level of satisfaction with their own lives were significantly higher among Poles than Canadians. This may indicate a compensatory mechanism between normative displays and subjective experience. Other potential interpretations are also considered
Nurses\u27 Alumnae Association Bulletin, May 1957
Alumnae Notes
Committee Reports
Digest of Alumnae Meetings
Graduation Awards - 1956
Letter from Hong Kong
Leukemia
Marriages
Necrology
New Arrivals
Physical Advances at Jefferson
President\u27s Message
School of Nursing Report
Two Year Programs in Nursing
White Haven Repor
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning
Trust region methods rigorously enabled reinforcement learning (RL) agents to learn monotonically improving policies, leading to superior performance on a variety of tasks. Unfortunately, when it comes to multi-agent reinforcement learning (MARL), the property of monotonic improvement may not simply apply; this is because agents, even in cooperative games, could have conflicting directions of policy updates. As a result, achieving a guaranteed improvement on the joint policy where each agent acts individually remains an open challenge. In this paper, we extend the theory of trust region learning to cooperative MARL. Central to our findings are the multi-agent advantage decomposition lemma and the sequential policy update scheme. Based on these, we develop Heterogeneous-Agent Trust Region Policy Optimisation (HATPRO) and Heterogeneous-Agent Proximal Policy Optimisation (HAPPO) algorithms. Unlike many existing MARL algorithms, HATRPO/HAPPO do not need agents to share parameters, nor do they need any restrictive assumptions on decomposibility of the joint value function. Most importantly, we justify in theory the monotonic improvement property of HATRPO/HAPPO. We evaluate the proposed methods on a series of Multi-Agent MuJoCo and StarCraftII tasks. Results show that HATRPO and HAPPO significantly outperform strong baselines such as IPPO, MAPPO and MADDPG on all tested tasks, thereby establishing a new state of the art
Nurses\u27 Alumnae Association Bulletin - Volume 18 Number 1
Alumnae Notes
Central Dressing Room
Committee Reports
Digest of Alumnae Association Meetings
Graduation Awards - 1952
Greetings from Miss Childs
Greetings from the President
Marriages
Modern Trends in Orthopaedic Surgery
Necrology
New Arrivals
Physical Advances at Jefferson Hospital - 1953
Staff Activities - 1952-1953
Student Activities
The Artificial Heart Lung Machin
Advanced cryo-tomography workflow developments - correlative microscopy, milling automation and cryo-lift-out
Cryo-electron tomography (cryo-ET) is a groundbreaking technology for 3D visualisation and analysis of biomolecules in the context of cellular structures. It allows structural investigations of single proteins as well as their spatial arrangements within the cell. Cryo-tomograms provide a snapshot of the complex, heterogeneous and transient subcellular environment. Due to the excellent structure preservation in amorphous ice, it is possible to study interactions and spatial relationships of proteins in their native state without interference caused by chemical fixatives or contrasting agents. With the introduction of focused ion beam (FIB) technology, the preparation of cellular samples for electron tomography has become much easier and faster. The latest generation of integrated FIB and scanning electron microscopy (SEM) instruments (dual beam microscopes), specifically designed for cryo-applications, provides advances in automation, imaging and the preparation of high-pressure frozen bulk samples using cryo-lift-out technology. In addition, correlative cryo-fluorescence microscopy provides cellular targeting information through integrated software and hardware interfaces. The rapid advances, based on the combination of correlative cryo-microscopy, cryo-FIB and cryo-ET, have already led to a wealth of new insights into cellular processes and provided new 3D image data of the cell. Here we introduce our recent developments within the cryo-tomography workflow, and we discuss the challenges that lie ahead. Lay Description This article describes our recent developments for the cryo-electron tomography (cryo-ET) workflow. Cryo-ET offers superior structural preservation and provides 3D snapshots of the interior of vitrified cells at molecular resolution. Before a cellular sample can be imaged by cryo-ET, it must be made accessible for transmission electron microscopy. This is achieved by preparing a 200-300 nm thin cryo-lamella from the cellular sample using a cryo-focused ion beam (cryo-FIB) microscope. Cryo-correlative light and electron microscopy (cryo-CLEM) is used within the workflow to guide the cryo-lamella preparation to the cellular areas of interest. We cover a basic introduction of the cryo-ET workflow and show new developments for cryo-CLEM, which facilitate the connection between the cryo-light microscope and the cryo-FIB. Next, we present our progress in cryo-FIB software automation to streamline cryo-lamella preparation. In the final section we demonstrate how the cryo-FIB can be used for 3D imaging and how bulk-frozen cellular samples (obtained by high-pressure freezing) can be processed using the newly developed cryo-lift-out technology
Influence of Solvent Temperature and Type on Naphthalene Solubility for Tar Removal in a Dual Fluidized Bed Biomass Gasification Process
Tar condensation is a cause of blockage in downstream application of the gasification process. An oil scrubber is considered as an effective method for tar removal. In this research, the naphthalene solubility in different local Thai oils and water was investigated in a laboratory-scale test-rig. The solubility value was conducted at 30, 50, 70, and 80°C. Biodiesels investigated were rapeseed methyl ester (RME) and two different palm methyl esters (PME 1 and PME 2). Furthermore, vegetable oils including sunflower oil, rice bran oil, crude palm oil, and refined palm oil were examined. The results showed that higher temperature enhanced naphthalene solubility in all types of investigated oils. Biodiesel has the highest value of naphthalene solubility. All scrubbing oils have similar naphthalene solubility trends at the temperature range of 50-80°C in the order of RME > PME 1 > PME 2 > diesel > sunflower oil > refined palm oil > rice bran oil > crude palm oil. Based on these experimental investigations, PME 1 has a naphthalene solubility value similar to RME. Therefore, PME 1 has been selected to be tested as scrubbing solvent in the 1 MWel prototype dual fluidized gasifier located in Nong Bua district, Nakhon Sawan province, Thailand
Settling the Variance of Multi-Agent Policy Gradients
Policy gradient (PG) methods are popular reinforcement learning (RL) methods where a baseline is often applied to reduce the variance of gradient estimates. In multi-agent RL (MARL), although the PG theorem can be naturally extended, the effectiveness of multi-agent PG (MAPG) methods degrades as the variance of gradient estimates increases rapidly with the number of agents. In this paper, we offer a rigorous analysis of MAPG methods by, firstly, quantifying the contributions of the number of agents and agents’ explorations to the variance of MAPG estimators. Based on this analysis, we derive the optimal baseline (OB) that achieves the minimal variance. In comparison to the OB, we measure the excess variance of existing MARL algorithms such as vanilla MAPG and COMA. Considering using deep neural networks, we also propose a surrogate version of OB, which can be seamlessly plugged into any existing PG methods in MARL. On benchmarks of Multi-Agent MuJoCo and StarCraft challenges, our OB technique effectively stabilises training and improves the performance of multi-agent PPO and COMA algorithms by a significant margin. Code is released at https://github.com/morning9393/Optimal-Baseline-for-Multi-agent-Policy-Gradients
Cutting edges at random in large recursive trees
We comment on old and new results related to the destruction of a random
recursive tree (RRT), in which its edges are cut one after the other in a
uniform random order. In particular, we study the number of steps needed to
isolate or disconnect certain distinguished vertices when the size of the tree
tends to infinity. New probabilistic explanations are given in terms of the
so-called cut-tree and the tree of component sizes, which both encode different
aspects of the destruction process. Finally, we establish the connection to
Bernoulli bond percolation on large RRT's and present recent results on the
cluster sizes in the supercritical regime.Comment: 29 pages, 3 figure
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