Reason, Morality, and Skill

Some economists argue that modern industrial societies must respond to ecological challenges by learning to live with diminishing economic growth. Yet it also seems that low growth societies are doomed to struggle with problems of social instability caused by economic recession, unemployment and a decline in social entitlements. In “Reason, Morality and Skill” John Stopford draws on Ancient Greek economic thought, including Aristotle’s views on the natural limitation of wealth, to discuss the problem of human flourishing in ecologically challenged societies. Economic capability theorists, influenced by the work of Sen and Nussbaum, have recently argued that the transition from a growth driven economy focused on consumption to a stable low growth economy requires us to redefine prosperity as capability development “within limits”. Stopford argues that to understand prosperity in this way we need to reexamine the role of skill in the development of capabilities. The marginalization of skill has become a systematic feature of modern industrial and consumer societies. Yet certain kinds of skill, exemplified in the work of the autonomously productive craftsman, are necessary to the development of the bounded capabilities that low growth societies need to foster

A High Speed Particle Phase Discriminator (PPD-HS) for the classification of airborne particles, as tested in a continuous flow diffusion chamber

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.A new instrument, the High-speed Particle Phase Discriminator (PPD-HS), developed at the University of Hertfordshire, for sizing individual cloud hydrometeors and determining their phase is described herein. PPD-HS performs an in situ analysis of the spatial intensity distribution of near-forward scattered light for individual hydrometeors yielding shape properties. Discrimination of spherical and aspherical particles is based on an analysis of the symmetry of the recorded scattering patterns. Scattering patterns are collected onto two linear detector arrays, reducing the complete 2-D scattering pattern to scattered light intensities captured onto two linear, one-dimensional strips of light sensitive pixels. Using this reduced scattering information, we calculate symmetry indicators that are used for particle shape and ultimately phase analysis. This reduction of information allows for detection rates of a few hundred particles per second. Here, we present a comprehensive analysis of instrument performance using both spherical and aspherical particles generated in a well-controlled laboratory setting using a vibrating orifice aerosol generator (VOAG) and covering a size range of approximately 3-32 μm. We use supervised machine learning to train a random forest model on the VOAG data sets that can be used to classify any particles detected by PPD-HS. Classification results show that the PPD-HS can successfully discriminate between spherical and aspherical particles, with misclassification below 5% for diameters >3μm. This phase discrimination method is subsequently applied to classify simulated cloud particles produced in a continuous flow diffusion chamber setup. We report observations of small, near-spherical ice crystals at early stages of the ice nucleation experiments, where shape analysis fails to correctly determine the particle phase. Nevertheless, in the case of simultaneous presence of cloud droplets and ice crystals, the introduced particle shape indicators allow for a clear distinction between these two classes, independent of optical particle size. From our laboratory experiments we conclude that PPD-HS constitutes a powerful new instrument to size and discriminate the phase of cloud hydrometeors. The working principle of PPD-HS forms a basis for future instruments to study microphysical properties of atmospheric mixed-phase clouds that represent a major source of uncertainty in aerosol-indirect effect for future climate projections..Peer reviewe

A Critical Assessment Of The Role Of The Imagination In Kant’s Exposition Of The Mathematical Sublime

Kant argues in the Critique of Judgment (CJ) that there are two distinct modes of the sublime. This essay will concentrate on the mathematical mode. It is helpful to begin an examination of the mathematical sublime by elucidating the difference between logical estimation and aesthetic estimation; it is aesthetic estimation under strain, so Kant argues, that instigates the moment of the sublime. Logical estimation forms the cognitive basis of scientific calculations. He argues that scientific enquiry only requires an understanding of the logical relationship of numbers and so does not require an aesthetic experience of those numbers

Discrete mode laser diodes with ultra narrow linewidth emission <3kHz

Ex-facet, free-running ultra-low linewidth (<3 kHz), single mode laser emission is demonstrated using low cost, regrowth-free ridge waveguide discrete mode Fabry-Perot laser diode chips

The Universal Cloud and Aerosol Sounding System (UCASS): a low-cost miniature optical particle counter for use in dropsonde or balloon-borne sounding systems

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. An earlier version of this work was published in Atmospheric Measurement Techniques Discussions: https://dx.doi.org/10.5194/amt-2019-70.A low-cost miniaturized particle counter has been developed by The University of Hertfordshire (UH) for the measurement of aerosol and droplet concentrations and size distributions. The Universal Cloud and Aerosol Sounding System (UCASS) is an optical particle counter (OPC), which uses wide-angle elastic light scattering for the high-precision sizing of fluid-borne particulates. The UCASS has up to 16 configurable size bins, capable of sizing particles in the range 0.4–40 µm in diameter. Unlike traditional particle counters, the UCASS is an open-geometry system that relies on an external air flow. Therefore, the instrument is suited for use as part of a dropsonde, balloon-borne sounding system, as part of an unmanned aerial vehicle (UAV), or on any measurement platform with a known air flow. Data can be logged autonomously using an on-board SD card, or the device can be interfaced with commercially available meteorological sondes to transmit data in real time. The device has been deployed on various research platforms to take measurements of both droplets and dry aerosol particles. Comparative results with co-located instrumentation in both laboratory and field settings show good agreement for the sizing and counting ability of the UCASS.Peer reviewe

A framework for the simulation of structural software evolution

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 ACM.As functionality is added to an aging piece of software, its original design and structure will tend to erode. This can lead to high coupling, low cohesion and other undesirable effects associated with spaghetti architectures. The underlying forces that cause such degradation have been the subject of much research. However, progress in this field is slow, as its complexity makes it difficult to isolate the causal flows leading to these effects. This is further complicated by the difficulty of generating enough empirical data, in sufficient quantity, and attributing such data to specific points in the causal chain. This article describes a framework for simulating the structural evolution of software. A complete simulation model is built by incrementally adding modules to the framework, each of which contributes an individual evolutionary effect. These effects are then combined to form a multifaceted simulation that evolves a fictitious code base in a manner approximating real-world behavior. We describe the underlying principles and structures of our framework from a theoretical and user perspective; a validation of a simple set of evolutionary parameters is then provided and three empirical software studies generated from open-source software (OSS) are used to support claims and generated results. The research illustrates how simulation can be used to investigate a complex and under-researched area of the development cycle. It also shows the value of incorporating certain human traits into a simulation—factors that, in real-world system development, can significantly influence evolutionary structures

System development guidelines from a review of motion-based technology for people with MCI or dementia

As the population ages and the number of people living with dementia or mild cognitive impairment (MCI) continues to increase, it is critical to identify creative and innovative ways to support and improve their quality of life. Motion-based technology has shown significant potential for people living with dementia or MCI by providing opportunities for cognitive stimulation, physical activity and participation in meaningful leisure activities, while simultaneously functioning as a useful tool for research and development of interventions. However, many of the current systems created using motion-based technology have not been designed specifically for people with dementia or MCI. Additionally, the usability and accessibility of these systems for these populations has not been thoroughly considered. This paper presents a set of system development guidelines derived from a review of the state of the art of motion-based technologies for people with dementia or MCI. These guidelines highlight three overarching domains of consideration for systems targeting people with dementia or MCI: (i) cognitive, (ii) physical, and (iii) social. We present the guidelines in terms of relevant design and use considerations within these domains and the emergent design themes within each domain. Our hope is that these guidelines will aid in designing motion-based software to meet the needs of people with dementia or MCI such that the potential of these technologies can be realized

Predicting a Containership's Arrival Punctuality in Liner Operations by Using a Fuzzy Rule-Based Bayesian Network (FRBBN)

One of the biggest concerns in liner operations is punctuality of containerships. Managing the time factor has become a crucial issue in today's liner shipping operations. A statistic in 2015 showed that the overall punctuality for containerships only reached an on-time performance of 73%. However, vessel punctuality is affected by many factors such as the port and vessel conditions and knock-on effects of delays. As a result, this paper develops a model for analyzing and predicting the arrival punctuality of a liner vessel at ports of call under uncertain environments by using a hybrid decision-making technique, the Fuzzy Rule-Based Bayesian Network (FRBBN). In order to ensure the practicability of the model, two container vessels have been tested by using the proposed model. The results have shown that the differences between prediction values and real arrival times are only 4.2% and 6.6%, which can be considered as reasonable. This model is capable of helping liner shipping operators (LSOs) to predict the arrival punctuality of their vessel at a particular port of call. © 2017 The Korean Association of Shipping and Logistics, Inc