In the MOOD for Citizen Psych-Science

People make funny, frustrating and fatal errors on a daily basis. People can also create and apply strategies to avoid and mitigate error – this is called cognitive resilience. Researchers at UCLIC started the Errordiary project in 2009 as a way of raising awareness of human error research. Errordiary (www.errordiary.org) is an online public repository of the errors people make and the cognitive resilience strategies that they use. People contribute to it by using the #errordiary #rsdiary hashtags through Twitter. Over 130 people have contributed so far. The project has allowed researchers to gain a better insight into the resilience strategies that people use (Furniss et al., 2012). It has also been used as a real-life data set for teaching students about the psychology of human error (Wiseman, 2012). During August 2013 we interviewed 8 Errordiary contributors (5 female, 3 male) to find out more about their motivations for taking part. Most of our participants described their contributions as “occasional”, where Errordiary contributions varied from once a week, once a month, to once every 6 months. As one participant describes, “I go through a period of not contributing for weeks and then remembering it exists.” One reason for this is that contributions are event-driven. People cannot contribute whenever they wish - it has to be once they’ve committed an error or used a resilience strategy. Some participants described forgetting to contribute. Those that were regular twitter users were more likely to remember. As one participant describes, “I was already sharing errors on Twitter, now it’s just adding a hashtag.” The content of the error also had an impact on contributions. Sometimes participants did not tweet an error because they thought others might view their contribution as “mundane” or “not funny.” Contributions are visible to a person’s Twitter network, which means they are visible to a volunteer’s followers that may not know about the project. This makes contributing to Errordiary quite different to most other citizen science projects, where people contribute within the “safety” of being among like-minded others who share their interests. A couple of participants even described how they had set up a separate Twitter account just for the purpose of contributing to Errordiary. This highlights an important issue in using Twitter for data collection, as volunteers make a trade-off between convenience and protecting their privacy. These findings also highlight some of the ways in which a citizen psych-science project differs from a typical citizen science project. In citizen science usually volunteers collect or analyse data related to their environment (Haklay, 2013). However in Errordiary, researchers are asking volunteers to contribute their experiences of error. This means that volunteers are helping to collaborate in research, but at the same time they are the participants of the research. We suggest that this makes contributing to Errordiary more personal, and perhaps more sensitive, compared to other projects. The risks associated with sharing errors (e.g. negative perceptions from others, being viewed as incompetent) may counteract a person’s general good will to help researchers. Overall our study reveals several interesting insights concerning the spectrum of citizen science, and pros and cons in using Twitter for data collection. The Errordiary project is currently changing from being an online archive of error to a hub to engage and learn about error. This includes a ‘Discovery Zone’, allowing volunteers to explore research, media and games related to errors. It is now also possible for volunteers to login and contribute via the website – so the project is no longer restricted to Twitter users only. We plan to explore how these changes impact volunteers’ experiences in future research. References: Furniss, D., Back, J. and Blandford, A. (2012). Cognitive resilience: Can we use Twitter to make strategies more tangible? Proceedings of ECCE 2012, 96-99. Haklay, M. (2013). Citizen science and volunteered geographic information: Overview and typology of participation. In D. Sui et al. (Eds.) Crowdsourcing Geographic Knowledge: VGI in Theory and Practice, pp.105-122. Springer Netherlands. Wiseman, S. (2012). Errordiary: Support for teaching human error. ‘A contextualized curriculum for HCI’ workshop at CHI 2012

Evidence for seasonal reproduction in UK domestic cats

Objectives The aims of this study were to analyse a large body of data obtained by the Royal Society for the Prevention of Cruelty to Animals (RSPCA) Greater Manchester Animal Hospital on the breeding pattern of owned domestic cats in the UK, and to provide clear statistical evidence of whether seasonal variation remains present in temperate climates. Methods The total number of cats spayed and the number of cats found to be pregnant were recorded on a monthly basis from December 2005 to July 2014 by the RSPCA Greater Manchester Animal Hospital. The percentage of cats found to be pregnant was calculated for each month and the 8.5 years of data were binned into calendar months. The mean and SD of the monthly pregnancy rate was calculated for each calendar month bin, as was the difference between the mean percentage of detected pregnancies and the global mean. The Z score for each month’s difference was then calculated. Results Data were available for 5414 cats neutered during the 8.5 consecutive years of this study. A global average of 8.9% of cats spayed were found to be pregnant. The mean calendar month pregnancy rate exhibited a very significant variation, with the highest positive deviation being in April (Z score +2.9) and the highest negative deviation being in November/December (Z score -4.5). When aggregated into 3 month averages, an extremely significant difference between ‘spring’ and ‘winter’ months of >7 SE (P <<0.01) was found. Conclusions and relevance This study provides clear statistical evidence, from a large data set, that seasonal breeding patterns are still present under UK temperate conditions. We discuss the impact that this has on charity rescue shelters and propose that a campaign targeted at clients of animal welfare charities encouraging autumn neutering will be the most cost-effective method of cat population control, and help relieve the demand on welfare charity resources

Master Recital

Program listing performers and works performe

The next stage of naval electrical engineering system testing at the Power Networks Demonstration Centre

This paper gives an overview of the Power Hardware in the Loop (PHIL) system, that is now operational at the PNDC (a University of Strathclyde Research Centre), to extend the centres capability for marine electrical system testing. In this paper, the key components of the PHIL system and their corresponding interfaces are presented; representative case studies showing typical applications for the PHIL system at the PNDC are illustrated; and the next stage of future marine power system testing (flywheel energy storage) utilising the PHIL platform is discussed. The objective of this test bed is to: facilitate integration of engineering systems into marine power system platforms; support the development of future electric ships; to de-risk the integration of the next generation of energy weapons and sensors; and to supplement and replace the need for ship demonstrators. This facility development and associated project plan involves a productive mix of industry, academia, UK MoD and US DoD. The two key components of the PHIL test bed are: (1) A Real Time Digital Simulator (RTDS) system that is capable of simulating marine electrical systems in real time; and (2) A Triphase converter, a uniquely modular solution that can be re-configured for AC and DC output, used as the link between simulation and real hardware under test. The RTDS interface with the Triphase converter system employs fibre communication to issue control commands and receive measurement feedback. The hardware to be tested, connected to the Triphase, is interfaced directly to simulation in real time. In this paper it is demonstrated how a flywheel energy storage device could be directly connected to a simulated ship power system and operated in real time. This test setup would be used to evaluate the interaction between the ship power system and flywheel. This test bed can be reconfigured for long term research and development for a multitude of ship power system solutions. The ship power system is represented in simulation which means it can be modified to represent existing or planned ship architectures. This facilitates testing of hardware planned for retrofit in existing ship power systems; and it allows future ship powers systems to be simulated and interfaced with existing hardware. Both options support reduced cost and life cycle time to develop ship power systems

Systematic Comparison of Pre-Treatment Parameters in Forensic Hair Analysis and Investigating Hair-drug Interactions

Forensic toxicological analysis for the purposes of protecting human health and supporting criminal justice activities can be achieved, in part, by means of analysis of human head hair for detection of abused substances. Hair is considered an alternative sample matrix (compared to blood and urine) because of persistent interpretive challenges caused by a lack of standardization in analytical approaches and poor understanding of the biases resulting from physicochemical interactions between major hair components (e.g., melanin) and drugs of abuse. Some of the uncertainty regarding optimal techniques for the pre-treatment of hair specimens results from the unknown nature of the interactions between drugs and hair components, in particular melanin. Thus, the second focus of this work was to study these interactions with select drugs and melanin by UV/Visible spectroscopy. Another source of uncertainty is attributed to the lack of standardization in the analytical approach to hair testing. As a complex solid sample matrix, hair requires pre-treatment measures including decontamination, homogenization, and extraction to remove drug from the hair components to allow for analysis. Optimizing these pre-treatment parameters is essential for accurate toxicological analysis of this matrix. Thus, a major focus of this work was to conduct a comprehensive comparison of the efficacy of decontamination and extraction variables by means of statistical design of experiments (DoE). Major findings of this work were a minimum of four consecutive washes were necessary for the decontamination of hair and solvent swelling of the matrix resulted in the highest extraction of the five analytes under study. The other major conclusion of this work was the interaction between eumelanin and drugs is a result of ionic interactions and van der Waals forces. Additionally, association constants between drugs and eumelanin were determined to provide additional insight into the strength of interactions between drugs with different physicochemical properties and eumelanin. These findings will impact the forensic science community by contributing to a body of research aimed at determining the most effective method(s) for decontaminating hair samples for forensic analysis, the subsequent isolation of drugs from hair, and by investigating the interactions between melanin and select drugs of abuse

Understanding selective college access for minority, low-income high school students

The purpose of this investigation was to explore a contextual intervention of effective college advising programs for ethnic minority students that helps them acquire the skills and personal dispositions necessary to apply to, get into, and stay at selective colleges and universities. Utilizing a regression analysis, this analytical study examined 199 low-income minority high school students in a contextual college intervention program from 2014 to 2015. The central hypothesis being tested was that intervention programs that were successful at getting lower income ethnic minority youth to apply to, get into, and stay at selective colleges and universities attract and maintain students with higher levels of personal factors, especially factors of resilience such as motivation, grit, and perseverance. The research questions sought to examine the relationship between effective college advising programs for minority, low-income students (contextual intervention) and what social and emotional or resilient skills (personal factors) their students possess to become college and career ready, and whether possessing these skills differentiates those students who are accepted into highly selective colleges from those who are accepted to less selective colleges. A growing body of research demonstrates that admittance to selective colleges often leads to increased social status, higher income, and improved job opportunities. It has been demonstrated that getting into a highly selective college matters. Caucasian and minority students alike who graduate from highly selective colleges experience increased lifetime earnings and prestige (Bowen, 1998, Avery, 2003). A total of 199 minority high school student participants were surveyed during their senior year in high school. Survey items were drawn from Solberg’s Success Model Survey (2007) and Duckworth’s Grit Model (2007). Duckworth validated a self-report questionnaire called the Grit Scale where “Grit” is defined as trait-level perseverance and passion for long-term goals. Solberg’s Success Model Survey is a composite of several scales: Career Search Self-Efficacy, Goal-Setting, and Motivation to Attend School; Academic Self-Efficacy; and Social Connections. (Sample survey questions in Table section.) The dataset also included participant demographic data, program participation information, and college admit results. This investigation tested Coleman’s (2006) Minority Student Achievement Model to demonstrate that significant personal factors including academic ability, diligent use of resources, perseverance, and strategic involvement in youth development initiatives, combined with a successful college contextual intervention, were significant indicators regarding increased admittance to selective colleges

Decision support system for sensor-based autonomous filling of grain containers

Autonomous technology in agriculture offers many products that reduce distractions and fatigue experienced by machinery operators, including automatic path guidance, variable rate product delivery, and precision seed placement. However, the size and complexity of modern mechanical harvesting operations have limited the ability of autonomous technology to significantly reduce total negative effects on grain combine operators. Combine operators are highly susceptible to fatigue because several tasks must be performed simultaneously to ensure safe machine operation. These duties include monitoring internal threshing and crop flow intake, maintaining row alignment, avoiding foreign material intake, and overseeing unloading grain. The primary goal of this project was to design a decision support system for autonomous unloading of combines. When unloading grain on-the-go, operators divert more attention away from critical tasks to focus on grain delivery to the adjacent cart. An autonomous system eliminating the need for combine operators to focus on unloading on-the-go potentially reduces operator stress and grain spillage. Critical to the decision support system for autonomous unloading was the input of a two-dimensional fill grid used to describe the grain height in the cart. The inverse distance weighting method, an estimation technique common to spatial data modeling, was used to estimate points in the fill grid of a grain cart prone to being immeasurable or highly variable. This method was successful in estimating missing points in a grain cart under difficult delivery conditions to within 15 cm of underestimation and 25 cm of overestimation. A model to predict the weight of grain in a grain cart was developed using the average grain height measured in the cart. The model demonstrated high robustness by producing mean errors that changed by less than 2% of the total cart volume when the delivery conditions strayed from typical conditions to highly biased conditions. The decision support system that was developed exhibited robust performance when critical features of the system were tested at typical levels. Field testing validated the potential to apply the decision support system to autonomous combine unloading systems by producing predictable and consistent final cart volumes that were within 5% of the total volume

Length-scale enabled quantification of surface damage by indentation: A case study separating the components of contact response due to indentation size, residual stress, and damage caused by surface machining and grinding

Instrumented indentation is a convenient and increasingly rapid method of high resolution mapping of surface properties. There is, however, significant untapped potential for the quantification of these properties, which is only possible by resolution of a number of serious issues that affect the absolute values for mechanical properties obtained from small indentations. The three most pressing currently are the quantification of the contributions to an indentation result due to: the Indentation Size Effect (ISE); Residual stress; and pile-up and sink-in – which is itself affected by residual stress and ISE. We take as a case study the mapping of the residual stress in a cross-section of the machined surface of a previously stress free metal. The effect of surface grinding is compared to milling and is shown to cause work hardening, an increase in residual stress, as well as surface grain size reduction. Hardness based indentation mapping is unable to distinguish these effects. However, by using Continuum based FEA models of the effect of residual stress on Modulus and an indentation modulus map, as well as a hardness map and a determination the ISE coefficient (using self-similar geometry indentation), we are able to separate out the contribution of stress and pile up, indentation size effect, leaving a quantified measurement of the effect of surface treatment on grain size and dislocation density. Since the FEA results can be expressed in parameterised form for general application, this provides an accessible method for improved mechanical property and surface stress mapping