Building sensitising terms to understand free-play in open-ended interactive art environments

In this paper we introduce and discuss the nature of free-play in the context of three open-ended interactive art installation works. We observe the interaction work of situated free-play of the participants in these environments and, building on precedent work, devise a set of sensitising terms derived both from the literature and from what we observe from participants interacting there. These sensitising terms act as guides and are designed to be used by those who experience, evaluate or report on open-ended interactive art. That is, we propose these terms as a common-ground language to be used by participants communicating while in the art work to describe their experience, by researchers in the various stages of research process (observation, coding activity, analysis, reporting, and publication), and by inter-disciplinary researchers working across the fields of HCI and art. This work builds a foundation for understanding the relationship between free-play, open-ended environments, and interactive installations and contributes sensitising terms useful for the HCI community for discussion and analysis of open-ended interactive art works.

Clinician-driven automated classification of limb fractures from free-text radiology reports

The aim of this research is to report initial experimental results and evaluation of a clinician-driven automated method that can address the issue of misdiagnosis from unstructured radiology reports. Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to disperse information resources and vast amounts of manual processing of unstructured information, a point-of-care accurate diagnosis is often difficult. A rule-based method that considers the occurrence of clinician specified keywords related to radiological findings was developed to identify limb abnormalities, such as fractures. A dataset containing 99 narrative reports of radiological findings was sourced from a tertiary hospital. The rule-based method achieved an F-measure of 0.80 and an accuracy of 0.80. While our method achieves promising performance, a number of avenues for improvement were identified using advanced natural language processing (NLP) techniques.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

A Cyber-Physical System Simulator for risk-free transport studies

The article introduces a novel platform for conducting controlled and risk-free driving and traveling behavior studies, called Cyber-Physical System Simulator (CPSS). The key features of CPSS are: (1) simulation of multiuser immersive driving in a threedimensional (3D) virtual environment; (2) integration of traffic and communication simulators with human driving based on dedicated middleware; and (3) accessibility of multiuser driving simulator on popular software and hardware platforms. This combination of features allows us to easily collect large-scale data on interesting phenomena regarding the interaction between multiple user drivers, which is not possible with current single-user driving simulators. The core original contribution of this article is threefold: (1) we introduce a multiuser driving simulator based on DiVE, our original massively multiuser networked 3D virtual environment; (2) we introduce OpenV2X, a middleware for simulating vehicle-to-vehicle and vehicle to infrastructure communication; and (3) we present two experiments based on our CPSS platform. The first experiment investigates the “rubbernecking” phenomenon, where a platoon of four user drivers experiences an accident in the oncoming direction of traffic. Second, we report on a pilot study about the effectiveness of a Cooperative Intelligent Transport Systems advisory system.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology

Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.

Hydrogen evolution by a metal-free electrocatalyst

Electrocatalytic reduction of water to molecular hydrogen via the hydrogen evolution reaction may provide a sustainable energy supply for the future, but its commercial application is hampered by the use of precious platinum catalysts. All alternatives to platinum thus far are based on nonprecious metals, and, to our knowledge, there is no report about a catalyst for electrocatalytic hydrogen evolution beyond metals. Here we couple graphitic-carbon nitride with nitrogen-doped graphene to produce a metal-free hybrid catalyst, which shows an unexpected hydrogen evolution reaction activity with comparable overpotential and Tafel slope to some of well-developed metallic catalysts. Experimental observations in combination with density functional theory calculations reveal that its unusual electrocatalytic properties originate from an intrinsic chemical and electronic coupling that synergistically promotes the proton adsorption and reduction kinetics.

Baidu’s perfect paradox : free speech and the right to censor

China’s biggest search engine has a constitutional right to filter its search results, a US court found last month. But that’s just the start of the story. Eight New York-based pro-democracy activists sued Baidu Inc in 2011, seeking damages because Baidu prevents their work from showing up in search results. Baidu follows Chinese law that requires it to censor politically sensitive results. But in what the plaintiffs’ lawyer has dubbed a “perfect paradox”, US District Judge Jesse Furman has dismissed the challenge, explaining that to hold Baidu liable for its decisions to censor pro-democracy content would itself infringe the right to free speech.

Concerted HO2 elimination from alpha-Aminoalkylperoxyl free radicals : Experimental and theoretical evidence from the gas phase NH2 center dot CHCO2- + O-2 reaction

We have investigated the gas-phase reaction of the alpha-aminoacetate (glycyl) radical anion (NH2(sic)CHCO2-) with O-2 using ion trap mass spectrometry, quantum chemistry, and statistical reaction rate theory. This radical is found to undergo a remarkably rapid reaction with O-2 to form the hydroperoxyl radical (HO2(sic)) and an even-electron imine (NHCHCO2-), with experiments and master equation simulations revealing that reaction proceeds at the ion molecule collision rate. This reaction is facilitated by a low-energy concerted HO2(sic) elimination mechanism in the NH2CH(OO(sic))CO2- peroxyl radical. These findings can explain the widely observed free-radical-mediated oxidation of simple amino acids to amides plus alpha-keto acids (their imine hydrolysis products). This work also suggests that imines will be the main intermediates in the atmospheric oxidation of primary and secondary amines, including amine carbon capture solvents such as 2-aminoethanol (commonly known as monoethanolamine, or MEA), in a process that avoids the ozone-promoting conversion of (sic)NO to (sic)NO2 commonly encountered in peroxyl radical chemistry.

Comparison of 3 accelerometer data reduction approaches, step counts, and 2 self-report measures for estimating physical activity in free-living adults

Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

Free for all : a case study examining implementation factors of one-to-one device programs

Despite significant investment in school one-to-one device programs, little is known about which aspects of program implementation work and why. Through a comparison of two implementation models, adopter-diffusion and saturation, and using existing data from the One Laptop per Child Australia laptop program, we explored how factors of implementation may affect device diffusion, learning and educational outcomes, and program sustainability in schools. In this article we argue that more focused research into implementation of one-to-one device programs, moving beyond comparisons of “devices versus without devices,” is needed to provide reliable data to inform future program funding and advance this area of research.

The use of uniaxial and triaxial accelerometers to measure children's "free-play" physical activity

In order to effectively measure the physical activity of children, objective monitoring devices must be able to quantify the intermittent and nonlinear movement of free play. The purpose of this study was to investigate the validity of the Computer Science and Applications (CSA) uniaxial accelerometer and the TriTrac-R3D triaxial accelerometer with respect to their ability to measure 8 "free-play" activities of different intensity. The activities ranged from light to very vigorous in intensity and included activities such as throwing and catching, hopscotch, and basketball. Twenty-eight children, ages 9 to 11, wore a CSA and a heart rate monitor while performing the activities. Sixteen children also wore a Tritrac. Counts from the CSA, Tritrac, and heart rates corresponding to the last 3 min of the 5 min spent at each activity were averaged and used in correlation analyses. Across all 8 activities, Tritrac counts were significantly correlated with predicted MET level (r= 0.69) and heart rate (r= 0.73). Correlations between CSA output, predicted MET level (0.43), and heart rate (0.64) were also significant but were lower than those observed for the Tritrac. These data indicate that accelerometers are an appropriate methodology for measuring children's free-play physical activities.

Label-free SERS for natural product provenance

Introduction Natural product provenance is important in the food, beverage and pharmaceutical industries, for consumer confidence and with health implications. Raman spectroscopy has powerful molecular fingerprint abilities. Surface Enhanced Raman Spectroscopy’s (SERS) sharp peaks allow distinction between minimally different molecules, so it should be suitable for this purpose. Methods Naturally caffeinated beverages with Guarana extract, coffee and Red Bull energy drink as a synthetic caffeinated beverage for comparison (20 µL ea.) were reacted 1:1 with Gold nanoparticles functionalised with anti-caffeine antibody (ab15221) (10 minutes), air dried and analysed in a micro-Raman instrument. The spectral data was processed using Principle Component Analysis (PCA). Results The PCA showed Guarana sourced caffeine varied significantly from synthetic caffeine (Red Bull) on component 1 (containing 76.4% of the variance in the data). See figure 1. The coffee containing beverages, and in particular Robert Timms (instant coffee) were very similar on component 1, but the barista espresso showed minor variance on component 1. Both coffee sourced caffeine samples varied with red Bull on component 2, (20% of variance). ************************************************************ Figure 1 PCA comparing a naturally caffeinated beverage containing Guarana with coffee. ************************************************************ Discussion PCA is an unsupervised multivariate statistical method that determines patterns within data. Figure 1 shows Caffeine in Guarana is notably different to synthetic caffeine. Other researchers have revealed that caffeine in Guarana plants is complexed with tannins. Naturally sourced/ lightly processed caffeine (Monster Energy, Espresso) are more inherently different than synthetic (Red Bull) /highly processed (Robert Timms) caffeine, in figure 1, which is consistent with this finding and demonstrates this technique’s applicability. Guarana provenance is important because it is still largely hand produced and its demand is escalating with recognition of its benefits. This could be a powerful technique for Guarana provenance, and may extend to other industries where provenance / authentication are required, e.g. the wine or natural pharmaceuticals industries.

The free encyclopaedia that anyone can edit: the shifting values of Wikipedia editors

Wikipedia is often held up as an example of the potential of the internet to foster open, free and non-commercial collaboration. However such discourses often conflate these values without recognising how they play out in reality in a peer-production community. As Wikipedia is evolving, it is an ideal time to examine these discourses and the tensions that exist between its initial ideals and the reality of commercial activity in the encyclopaedia. Through an analysis of three failed proposals to ban paid advocacy editing in the English language Wikipedia, this paper highlights the shift in values from the early editorial community that forked encyclopaedic content over the threat of commercialisation, to one that today values the freedom that allows anyone to edit the encyclopaedia.

Ultra sensitive label free surface enhanced Raman spectroscopy method for the detection of biomolecules

We present a proof of concept for a novel nanosensor for the detection of ultra-trace amounts of bio-active molecules in complex matrices. The nanosensor is comprised of gold nanoparticles with an ultra-thin silica shell and antibody surface attachment, which allows for the immobilization and direct detection of bio-active molecules by surface enhanced Raman spectroscopy (SERS) without requiring a Raman label. The ultra-thin passive layer (~1.3 nm thickness) prevents competing molecules from binding non-selectively to the gold surface without compromising the signal enhancement. The antibodies attached on the surface of the nanoparticles selectively bind to the target molecule with high affinity. The interaction between the nanosensor and the target analyte result in conformational rearrangements of the antibody binding sites, leading to significant changes in the surface enhanced Raman spectra of the nanoparticles when compared to the spectra of the un-reacted nanoparticles. Nanosensors of this design targeting the bio-active compounds erythropoietin and caffeine were able to detect ultra-trace amounts the analyte to the lower quantification limits of 3.5×10−13 M and 1×10−9 M, respectively.