Anaesthetic breathing circuit obstruction due to blockage of tracheal tube connector by a foreign body - two cases

Publisher's copy made available with the permission of the publisher© 1999 Australian Society of AnaesthetistsTwo cases are presented which illustrate the disastrous consequences possible when an anaesthetic breathing circuit is obstructed by a foreign body. Despite reports of previous similar cases, work practices and equipment manufacture or design continue to allow for such events to occur. The importance of both pre-anaesthetic testing of the entire circuit including attachments such as the tracheal tube connector and filters, and the removal of these parts should obstruction occur, is emphasised. Use of “clear” transparent breathing circuit components and opaque or brightly coloured packaging and caps which could potentially cause obstruction should decrease the incidence and facilitate the diagnosis of this problem.M.J. Foreman, D. G. Moye

RG inspired Machine Learning for lattice field theory

Machine learning has been a fast growing field of research in several areas dealing with large datasets. We report recent attempts to use Renormalization Group (RG) ideas in the context of machine learning. We examine coarse graining procedures for perceptron models designed to identify the digits of the MNIST data. We discuss the correspondence between principal components analysis (PCA) and RG flows across the transition for worm configurations of the 2D Ising model. Preliminary results regarding the logarithmic divergence of the leading PCA eigenvalue were presented at the conference and have been improved after. More generally, we discuss the relationship between PCA and observables in Monte Carlo simulations and the possibility of reduction of the number of learning parameters in supervised learning based on RG inspired hierarchical ansatzes.Comment: Talk given by Yannick Meurice at the conference Lattice 2017, Granada, Spai

Design and mathematical analysis of a three-mirror X-ray telescope based on ATM S-056 X-ray telescope hardware

The mathematical design of the aspheric third mirror for the three-mirror X-ray telescope (TMXRT) is presented, along with the imaging characteristics of the telescope obtained by a ray trace analysis. The present design effort has been directed entirely toward obtaining an aspheric third mirror which will be compatible with existing S-056 paraboloidal-hyperboloidal mirrors. This compatability will facilitate the construction of a prototype model of the TMXRT, since it will only be necessary to fabricate one new mirror in order to obtain a working model

Vignetting characteristics of the S-056 X-ray telescope

A ray trace analysis of the vignetting characteristics of the S-056 X ray telescope is presented. The relative energy is calculated in the spot formed in the focal plane of the S-056 X ray telescope by an off axis point source at infinity for off axis angles of 0, 1, 2, ..., 35 arc minutes. At each off axis angle, the relative energies are evaluated using theoretical X ray reflectivity curves for wavelengths of 8.34 A, 17.57 A, and 27.39 A, and also using an experimental X ray reflectivity curve for 8.34 A. The effects of vignetting due purely to the geometry of the S-056 optical system are evaluated separately, as well as jointly with the effects of mirror reflectivity

Long range orbital error estimation for applications satellites

A method of optimum orbital averaging was employed to study the long range accuracy potential of polar orbiting applications satellites. This approach involved the determination of the boundary conditions of one set of differential equations of motion by adjusting the initial conditions in a least square sense with the use of data generated by another set of differential equations of motion

Curing kinetics and effects of fibre surface treatment and curing parameters on the interfacial and tensile properties of hemp/epoxy composites

The curing kinetics of neat epoxy (NE) and hemp fibre/epoxy composites was studied and assessed using two dynamic models (the Kissinger and Flynn-Wall-Ozawa Models) and an isothermal model (the Autocatalytic Model) which was generally supported by the experimental data obtained from dynamic and isothermal differential scanning calorimetry (DSC) scans. The activation energies for the curing of composites exhibited lower values compared to curing of NE which is believed to be due to higher nucleophilic activity of the amine groups of the curing agent in the presence of fibres. The highest tensile strength, σ was obtained with composites produced with an epoxy to curing agent ratio of 1:1 and the highest Young's modulus, E was obtained with an epoxy to curing agent ratio of 1:1.2. Alkali treated hemp fibre/epoxy (ATFE) composites were found to have higher σ and E values compared to those for untreated hemp fibre/epoxy (UTFE) composites which was consistent with the trend for interfacial shear strength (IFSS) values. Composites σ and E were found to be higher for a processing temperature of 70°C than for 25°C for both UTFE and ATFE composites, but were found to decrease as the curing temperature was increased further to 120°C

Influence of accelerated ageing on the physico-mechanical properties of alkali-treated industrial hemp fibre reinforced poly(lactic acid) (PLA) composites

30 wt% aligned untreated long hemp fibre/PLA (AUL) and aligned alkali treated long hemp fibre/PLA (AAL) composites were produced by film stacking and subjected to accelerated ageing. Accelerated ageing was carried out using UV irradiation and water spray at 50 °C for four different time intervals (250, 500, 750 and 1000 h). After accelerated ageing, tensile strength (TS), flexural strength, Young's modulus (YM), flexural modulus and mode I fracture toughness (KIc) were found to decrease and impact strength (IS) was found to increase for both AUL and AAL composites. AUL composites had greatest overall reduction in mechanical properties than that for AAL composites upon exposure to accelerated ageing environment. FTIR analysis and crystallinity contents of the accelerated aged composites support the results of the deterioration of mechanical properties upon exposure to accelerated ageing environment

Architecture for intelligent power systems management, optimization, and storage.

The management of power and the optimization of systems generating and using power are critical technologies. A new architecture is developed to advance the current state of the art by providing an intelligent and autonomous solution for power systems management. The architecture is two-layered and implements a decentralized approach by defining software objects, similar to software agents, which provide for local optimization of power devices such as power generating, storage, and load devices. These software device objects also provide an interface to a higher level of optimization. This higher level of optimization implements the second layer in a centralized approach by coordinating the individual software device objects with an intelligent expert system thus resulting in architecture for total system power management. In this way, the architecture acquires the benefits of both the decentralized and centralized approaches. The architecture is designed to be portable, scalable, simple, and autonomous, with respect to devices and missions. Metrics for evaluating these characteristics are also defined. Decentralization achieves scalability and simplicity through modularization using software device objects that can be added and deleted as modules based on the devices of the power system are being optimized. Centralization coordinates these software device objects to bring autonomy and intelligence of the whole power system and mission to the architecture. The centralization approach is generic since it always coordinates software device objects; therefore it becomes another modular component of the architecture. Three example implementations illustrate the evolution of this power management system architecture. The first implementation is a coal-fired power generating station that utilized a neural network optimization for the reduction of nitrogen oxide emissions. This illustrates the limitations of this type of black-box optimization and serves as a motivation for developing a more functional architecture. The second implementation is of a hydro-generating power station where a white-box, software agent approach illustrates some of the benefits and provides initial justification of moving towards the proposed architecture. The third implementation applies the architecture to a vehicle to grid application where the previous hydro-generating application is ported and a new hybrid vehicle application is defined. This demonstrates portability and scalability in the architecture, and linking these two applications demonstrates autonomy. The simplicity of building this application is also evaluated