Characterization of thermally aged AlPO4-coated LiCoO2 thin films

The electrochemical properties and stability during storage of pristine and AlPO4-coated LiCoO2 thin films were characterized. The wide and smooth surface of the thin film electrode might provide an opportunity for one to observe surface reactions with an electrolyte. The rate capability and cyclic performance of the LiCoO2 thin film were enhanced by AlPO4 surface coating. Based on secondary ion mass spectrometry analysis and scanning electron microscopy images of the surface, it was confirmed that the coating layer was successfully protected from the reactive electrolyte during storage at 90°C. In contrast, the surface of the pristine sample was severely damaged after storage

Digital collection management software employed by libraries and museums: examination of metadata semantic mapping functionality

A growing number of organizations are building digital collections using both commercial digital collection management software such as CONTENTdm, Encompass, etc., and open source software such as Greenstone and D-Space. This rapidly growing number of distributed digital collections has brought to the fore the critical issues of resource discovery and sharing across these collections. The goal of this project is to examine the functionality of metadata creation and mapping and the configuration of digital collection management software. This goal relates to the issue of semantic interoperability of concept representation across digital collections. For this, this project aims at examining how digital collection management software provides a mechanism for semantic mapping either between different metadata schemes such as Dublin Core (DC) and MARC or between cataloger-defined field names and a given metadata scheme such as DC. As a first step, we will examine features related to metadata semantic mapping of CONTENTdm software, which provides a feature that allows for catalogers to map cataloger-defined field names onto DC metadata elements

Topological Structure of Dense Hadronic Matter

We present a summary of work done on dense hadronic matter, based on the Skyrme model, which provides a unified approach to high density, valid in the large $N_c$ limit. In our picture, dense hadronic matter is described by the {\em classical} soliton configuration with minimum energy for the given baryon number density. By incorporating the meson fluctuations on such ground state we obtain an effective Lagrangian for meson dynamics in a dense medium. Our starting point has been the Skyrme model defined in terms of pions, thereafter we have extended and improved the model by incorporating other degrees of freedom such as dilaton, kaons and vector mesons.Comment: 13 pages, 8 figures, Talk given at the KIAS-APCTP Symposium in Astro-Hadron Physics "Compact Stars: Quest for New States of Dense Matter", November 10-14, 2003, Seoul, Korea, published by World Scientific. Based on talk by B.-Y. Par

Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications

This paper proposes a novel centralized training and distributed execution (CTDE)-based multi-agent deep reinforcement learning (MADRL) method for multiple unmanned aerial vehicles (UAVs) control in autonomous mobile access applications. For the purpose, a single neural network is utilized in centralized training for cooperation among multiple agents while maximizing the total quality of service (QoS) in mobile access applications.Comment: 2 pages, 4 figure

Visual Simulation Software Demonstration for Quantum Multi-Drone Reinforcement Learning

Quantum computing (QC) has received a lot of attention according to its light training parameter numbers and computational speeds by qubits. Moreover, various researchers have tried to enable quantum machine learning (QML) using QC, where there are also multifarious efforts to use QC to implement quantum multi-agent reinforcement learning (QMARL). Existing classical multi-agent reinforcement learning (MARL) using neural network features non-stationarity and uncertain properties due to its large number of parameters. Therefore, this paper presents a visual simulation software framework for a novel QMARL algorithm to control autonomous multi-drone systems to take advantage of QC. Our proposed QMARL framework accomplishes reasonable reward convergence and service quality performance with fewer trainable parameters than the classical MARL. Furthermore, QMARL shows more stable training results than existing MARL algorithms. Lastly, our proposed visual simulation software allows us to analyze the agents' training process and results.Comment: 5 pages, 4 figure

Inhibition of Hypoxic Pulmonary Vasoconstriction of Rats by Carbon Monoxide

Hypoxic pulmonary vasoconstriction (HPV), a unique response of pulmonary circulation, is critical to prevent hypoxemia under local hypoventilation. Hypoxic inhibition of K+ channel is known as an important O2-sensing mechanism in HPV. Carbon monoxide (CO) is suggested as a positive regulator of Ca2+-activated K+ channel (BKCa), a stimulator of guanylate cyclase, and an O2-mimetic agent in heme moiety-dependent O2 sensing mechanisms. Here we compared the effects of CO on the HPV (Po2, 3%) in isolated pulmonary artery (HPVPA) and in blood-perfused/ventilated lungs (HPVlung) of rats. A pretreatment with CO (3%) abolished the HPVPA in a reversible manner. The inhibition of HPVPA was completely reversed by 1H-[1,2,4]oxadiazolo-[4,3-a]quinoxalin-1-one (ODQ), a guanylate cyclase inhibitor. In contrast, the HPVlung was only partly decreased by CO. Moreover, the partial inhibition of HPVlung by CO was affected neither by the pretreatment with ODQ nor by NO synthase inhibitor (L-NAME). The CO-induced inhibitions of HPVPA and HPVlung were commonly unaffected by tetraethylammonium (TEA, 2 mM), a blocker of BKCa. As a whole, CO inhibits HPVPA via activating guanylate cyclase. The inconsistent effects of ODQ on HPVPA and HPVlung suggest that ODQ may lose its sGC inhibitory action when applied to the blood-containing perfusate

Quantitative Screening of Cervical Cancers for Low-Resource Settings: Pilot Study of Smartphone-Based Endoscopic Visual Inspection After Acetic Acid Using Machine Learning Techniques

Background: Approximately 90% of global cervical cancer (CC) is mostly found in low- and middle-income countries. In most cases, CC can be detected early through routine screening programs, including a cytology-based test. However, it is logistically difficult to offer this program in low-resource settings due to limited resources and infrastructure, and few trained experts. A visual inspection following the application of acetic acid (VIA) has been widely promoted and is routinely recommended as a viable form of CC screening in resource-constrained countries. Digital images of the cervix have been acquired during VIA procedure with better quality assurance and visualization, leading to higher diagnostic accuracy and reduction of the variability of detection rate. However, a colposcope is bulky, expensive, electricity-dependent, and needs routine maintenance, and to confirm the grade of abnormality through its images, a specialist must be present. Recently, smartphone-based imaging systems have made a significant impact on the practice of medicine by offering a cost-effective, rapid, and noninvasive method of evaluation. Furthermore, computer-aided analyses, including image processing-based methods and machine learning techniques, have also shown great potential for a high impact on medicinal evaluations