Energy Consumption and Demand as Affected by Heat Pumps that Cool, Heat and Heat Domestic Water

Products or systems that heat, cool and heat domestic water, which are also referred to as integrated systems, have been available for several years. The concept is simple and appeals to consumers. This paper presents methods for evaluating the potential savings by using an integrated system that heats water by desuperheating discharge gas in the refrigeration cycle. The methods may be applied for any specific location, and their accuracy will depend on the accuracy of building loads and water usage estimates. Power demand can also be affected by electric water heaters. The methods presented demonstrate how integrated systems can be of value in reducing daily summertime peaks

Towards Compound Identification of Synthetic Opioids in Non-targeted Screening Using Machine Learning Techniques.

The constant evolution of the illicit drug market makes the identification of unknown compounds problematic. Obtaining certified reference materials for a broad array of new analogues can be difficult and cost prohibitive. Machine learning provides a promising avenue to putatively identify a compound before confirmation against a standard. In this study, machine learning approaches were used to develop class prediction and retention time prediction models. The developed class prediction model used a Naïve Bayes architecture to classify opioids as belonging to either the fentanyl analogues, AH series or U series, with an accuracy of 89.5%. The model was most accurate for the fentanyl analogues, most likely due to their greater number in the training data. This classification model can provide guidance to an analyst when determining a suspected structure. A retention time prediction model was also trained for a wide array of synthetic opioids. This model utilised Gaussian Process Regression to predict the retention time of analytes based on multiple generated molecular features with 79.7% of the samples predicted within ± 0.1 min of their experimental retention time. Once the suspected structure of an unknown compound is determined, molecular features can be generated and input for the prediction model to compare with experimental retention time. The incorporation of machine learning prediction models into a compound identification workflow can assist putative identifications with greater confidence and ultimately save time and money in the purchase and/or production of superfluous certified reference materials

Collision-induced dissociation studies of synthetic opioids for non-targeted analysis

© 2019 Klingberg, Cawley, Shimmon and Fu. The continual introduction of a large number of new psychoactive substances, along with the large turnover of these substances, necessitates the development of non-targeted detection strategies to keep pace with the ever-changing drug market. The production of certified reference materials often lags behind the introduction of new substances to the market, therefore these detection strategies need to be able to function without relying on reference materials or library spectra. Synthetic opioids have recently emerged as a drug class of particular concern due to the health issues caused by their incredibly high potency. A common method which has been used for non-targeted analysis in the past involves the identification of common product ions formed as a result of the fragmentation of the parent molecule. These common fragments can then potentially be used as markers to indicate the presence of a particular class of compounds within a sample. In this study, standards of a number of different synthetic opioids, including 14 fentanyl derivatives, 7 AH series opioids, 4U series opioids, 4W series opioids and MT-45, were subjected to collision-induced dissociation studies to determine how the compounds fragment. The spectra obtained from these studies included a number of diagnostic fragments common to the different opioid classes that, when used in combination, show potential for use as class predictors. By using simple data processing techniques, such as extracted ion chromatograms, these diagnostic product ions identified can be applied to a non-targeted screening workflow

Phenomenological study of the behavior of some silica formers in a high velocity jet fuel burner

Samples of four silica formers: single crystal SiC, sintered alpha-SiC, reaction sintered Si3N4 and polycrystalline MoSi2, were subjected to a Mach 1 jet fuel burner for 1 hr, at a sample temperature of 1375 deg C (2500 deg F). Two phenomena were identified which may be deleterious to a gas turbine application of these materials. The glass layer formed on the MoSi2 deformed appreciably under the aerodynamic load. A scale developed on the samples of the other materials which consisted of particular matter from the gas stream entrapped in a SiO2 matrix

An Example of the Use of Interdigital PVDF Transducers to Generate and Receive a High Order Lamb Wave Mode in a Pipe

From a non-destructive evaluation point of view, Lamb waves are a highly attractive means of inspecting a large area of a structure from a single point. Interdigital PVDF transducers have been used previously in signal processing applications [1] to generate acoustic waves in piezoelectric substrates. This paper in conjunction with that of Monkhouse et al [2] aims to provide an overview of the work accomplished so far at Imperial College in the use of interdigital PVDF transducers to transmit and receive Lamb waves in certain structures for non-destructive evaluation purposes. Interdigital PVDF transducers may be permanently bonded to either flat of curved surfaces and this attribute together with their low cost means that they are potentially suitable for“smart structure” applications

The Impact of Income on the Weight of Elderly Americans

This paper tests whether income affects the body weight and clinical weight classification of elderly Americans using a natural experiment that led otherwise identical retirees to receive significantly different Social Security payments based on their year of birth. We exploit this natural experiment by estimating models of instrumental variables using data from the National Health Interview Surveys. The model estimates rule out even moderate effects of income on weight and on the probability of being underweight or obese, especially for men.

Oxygen diffusion in alpha-Al2O3

Oxygen self diffusion coefficients were determined in single crystal alpha-Al2O3 using the gas exchange technique. The samples were semi-infinite slabs cut from five different boules with varying background impurities. The diffusion direction was parallel to the c-axis. The tracer profiles were determined by two techniques, single spectrum proton activation and secondary ion mass spectrometry. The SIMS proved to be a more useful tool. The determined diffusion coefficients, which were insensitive to impurity levels and oxygen partial pressure, could be described by D = .00151 exp (-572kJ/RT) sq m/s. The insensitivities are discussed in terms of point defect clustering. Two independent models are consistent with the findings, the first considers the clusters as immobile point defect traps which buffer changes in the defect chemistry. The second considers clusters to be mobile and oxygen diffusion to be intrinsic behavior, the mechanism for oxygen transport involving neutral clusters of Schottky quintuplets