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

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

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

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

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

Magneto-optical signature of massless Kane electrons in Cd3As2

We report on optical reflectivity experiments performed on Cd3As2 over a broad range of photon energies and magnetic fields. The observed response clearly indicates the presence of 3D massless charge carriers. The specific cyclotron resonance absorption in the quantum limit implies that we are probing massless Kane electrons rather than symmetry-protected 3D Dirac particles. The latter may appear at a smaller energy scale and are not directly observed in our infrared experiments.Comment: 5 pages, 4 figures + supplementary materials (17 pages), to be published in Phys. Rev. Let

Recording electrical activity from the brain of behaving octopus

: Octopuses, which are among the most intelligent invertebrates,1,2,3,4 have no skeleton and eight flexible arms whose sensory and motor activities are at once autonomous and coordinated by a complex central nervous system.5,6,7,8 The octopus brain contains a very large number of neurons, organized into numerous distinct lobes, the functions of which have been proposed based largely on the results of lesioning experiments.9,10,11,12,13 In other species, linking brain activity to behavior is done by implanting electrodes and directly correlating electrical activity with observed animal behavior. However, because the octopus lacks any hard structure to which recording equipment can be anchored, and because it uses its eight flexible arms to remove any foreign object attached to the outside of its body, in vivo recording of electrical activity from untethered, behaving octopuses has thus far not been possible. Here, we describe a novel technique for inserting a portable data logger into the octopus and implanting electrodes into the vertical lobe system, such that brain activity can be recorded for up to 12 h from unanesthetized, untethered octopuses and can be synchronized with simultaneous video recordings of behavior. In the brain activity, we identified several distinct patterns that appeared consistently in all animals. While some resemble activity patterns in mammalian neural tissue, others, such as episodes of 2 Hz, large amplitude oscillations, have not been reported. By providing an experimental platform for recording brain activity in behaving octopuses, our study is a critical step toward understanding how the brain controls behavior in these remarkable animals