The EDAM Project: Mining Atmospheric Aerosol Datasets

Data mining has been a very active area of research in the database, machine learning, and mathematical programming communities in recent years. EDAM (Exploratory Data Analysis and Management) is a joint project between researchers in Atmospheric Chemistry and Computer Science at Carleton College and the University of Wisconsin-Madison that aims to develop data mining techniques for advancing the state of the art in analyzing atmospheric aerosol datasets. There is a great need to better understand the sources, dynamics, and compositions of atmospheric aerosols. The traditional approach for particle measurement, which is the collection of bulk samples of particulates on filters, is not adequate for studying particle dynamics and real-time correlations. This has led to the development of a new generation of real-time instruments that provide continuous or semi-continuous streams of data about certain aerosol properties. However, these instruments have added a significant level of complexity to atmospheric aerosol data, and dramatically increased the amounts of data to be collected, managed, and analyzed. Our abilit y to integrate the data from all of these new and complex instruments now lags far behind our data-collection capabilities, and severely limits our ability to understand the data and act upon it in a timely manner. In this paper, we present an overview of the EDAM project. The goal of the project, which is in its early stages, is to develop novel data mining algorithms and approaches to managing and monitoring multiple complex data streams. An important objective is data quality assurance, and real-time data mining offers great potential. The approach that we take should also provide good techniques to deal with gas-phase and semi-volatile data. While atmospheric aerosol analysis is an important and challenging domain that motivates us with real problems and serves as a concrete test of our results, our objective is to develop techniques that have broader applicability, and to explore some fundamental challenges in data mining that are not specific to any given application domain

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Synthesis of nanocrystalline copper-tungsten alloys by mechanical alloying

Copper-tungsten exhibits total absence of solubility in both solid and liquid state. Mechanical alloying (MA) as a solid state, nonequilibrium process can be beneficial to the processing of such an immiscible system with the added features of refinement of structure. A study war undertaken to synthesise various Cu-W alloys and develop an ultrafine microcomposite structure of tungsten in copper matrix by mechanical alloying. Elemental powders of copper and tungsten were milled in high energy ball mills. The milling behaviour was found to depend on the composition milling time and milling atmosphere. The milled powders were characterised for their particle size, microstructure and lattice parameters. Metastable mutual solid solubility in the system was confirmed. Crystallite sizes were found to be in the nanocrystalline regime. The conversion of milling energy effectively to generate deformed surfaces, which in turn led to metastable solid solubility and nanocrystalline structure, was aided by the presence of oxygen in the milling atmosphere, (C) 2001 Elsevier Science B.V. All rights reserved

An Object-Based Data Model and a Deductive Language for Spatio-Temporal Database Applications

: We discuss data models and languages in relation to computational environments in which data access and tools for analysis are integrated in order to support data-intensive and numerically-intensive modelling activities in a class of scientific database systems. We describe a simple model of scientific activity in order to motivate the development of a new conceptual data model for complex, spatio-temporal objects and a deductive, object-oriented language to support the definition and manipulation of such objects. We provide three examples of the application of both the model and the language. 1 Introduction A database system and its conceptual schema provide a model of the phenomena that are represented in the database [Ull88]. Many non-standard database applications may be viewed as system modeling activities. For such applications, the database system must provide a means to represent and manipulate classes of complex objects; it must also provide a means to manipulate informatio..

Characterisation of mechanically alloyed atomised AI-Ni-Ce-Zr alloy system

Aluminium alloys with a combination of mechanical properties and light weight are in great demand for aerospace structural applications. In fact, researcher's full attention is on development of high strength light alloys for high temperature applications through newer processing techniques such as rapid solidification processing (RSP), mechanical alloying (MA) etc. This paper explains the combined effect of atomization and mechanical alloying. A study was taken up to process the atomised Al-Ni-Ce-Zr system by MA. The main jectives were to understand the atomised AI-Ni-Ce-Zr alloy powder and microstructural evelopment by MA. The MA parameters were optimized for obtaining the milled powder. Atomised and milled powders were characterized by metallography and scanning electron microscope (SEM) for understanding the structure and phase contents. Detailed analysis of the XRD data was carried out to evaluate lattice parameter and the crystallite size of the aluminium lattice for different experimental conditions. Effect of MA on the solid solubility of alloying elements in aluminium were understood. The results obtained by various characterisation techniques provided an idea for developing high strength aluminium alloys for high temperature applications

Mobius

Mobile application development is challenging for several reasons: intermittent and limited network connectivity, tight power constraints, server-side scalability concerns, and a number of fault-tolerance issues. Developers handcraft complex solutions that include client-side caching, conflict resolution, disconnection tolerance, and backend database sharding. To simplify mobile app development, we present Mobius, a system that addresses the messaging and data management challenges of mobile application development. Mobius introduces MUD (Messaging Unified with Data). MUD presents the programming abstraction of a logical table of data that spans devices and clouds. Applications using Mobius can asynchronously read from/write to MUD tables, and also receive notifications when tables change via continuous queries on the tables. The system combines dynamic client-side caching (with intelligent policies chosen on the server-side, based on usage patterns across multiple applications), notification services, flexible query processing, and a scalable and highly available cloud storage system. We present an initial prototype to demonstrate the feasibility of our design. Even in our initial prototype, remote read and write latency overhead is less than 52% when compared to a hand-tuned solution. Our dynamic caching reduces the number of messages by a factor of 4 to 8.5 when compared to fixed strategies, thus reducing latency, bandwidth, power, and server load costs, while also reducing data staleness