Making arrangements in talk-in-interaction

Arrangement-making is understood to be a ‘closing-relevant action’ (Schegloff & Sacks 1973), but little attention has been given to how people arrive at mutually acceptable plans for the future. Telephone conversations between clients and staff of Community and Home Care (CHC) services were studied to identify how arrangements for future services were made. A recurrent sequence was observed in which clients were informed of future arrangement and were prompted to reply with ‘response solicitation’ (Jefferson 1981). Response solicitations were observed at two points: either tagged to the end of an informing, or following a recipient’s response to the informing. We show how response solicitations are routinely used in instances where recipients have some discretion in relation to the arrangement under discussion. They are a means by which an informing party can display to their interlocutor that they, as recipient, have some discretion to exercise in the matter. These findings are discussed with reference to prior research on arrangement-making in other settings, which suggests the general nature of this practice.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Toxic state–corporate crimes, Neo-liberalism and green criminology : the hazards and legacies of the oil, chemical and mineral industries

This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.

Performance of buried tunnels subjected to surface blast incorporating fluid structure interaction

This paper uses finite element techniques to investigate the performance of buried tunnels subjected to surface blasts incorporating fully coupled Fluid Structure Interaction and appropriate material models which simulate strain rate effects. Modelling techniques are first validated against existing experimental results and then used to treat the blast induced shock wave propagation and tunnel response in dry and saturated sands. Results show that the tunnel buried in saturated sand responds earlier than that in dry sand. Tunnel deformations decrease with distance from explosive in both sands, as expected. In the vicinity of the explosive, the tunnel buried in saturated sand suffered permanent deformation in both axial and circumferential directions, whereas the tunnel buried in dry sand recovered from most of the axial deformation. Overall, response of the tunnel in saturated sand is more severe for a given blast event and shows the detrimental effect of pore water on the blast response of buried tunnels. The validated modelling techniques developed in this paper can be used to investigate the blast response of tunnels buried in dry and saturated sands.

Elucidating the host–pathogen interaction between human colorectal cells and invading Enterovirus 71 using transcriptomics profiling

Enterovirus 71 (EV71) is one of the main etiological agents for Hand, Foot and Mouth Disease (HFMD) and has been shown to be associated with severe clinical manifestation. Currently, there is no antiviral therapeutic for the treatment of HFMD patients owing to a lack of understanding of EV71 pathogenesis. This study seeks to elucidate the transcriptomic changes that result from EV71 infection. Human whole genome microarray was employed to monitor changes in genomic profiles between infected and uninfected cells. The results reveal altered expression of human genes involved in critical pathways including the immune response and the stress response. Together, data from this study provide valuable insights into the host–pathogen interaction between human colorectal cells and EV71.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Habituated interaction and social objects

In this position paper we draw from critical approaches to the concept of habit from cultural theory to argue that considering the sociality of everyday objects might be productive for understanding and designing for habituated interaction within the emerging Internet of Things.

Vertical dynamic interaction of trains and rail steel bridges

Rail steel bridges are vulnerable to high impact forces due to the passage of trains; unfortunately the determination of these transient impact forces is not straightforward as these are affected by a large number of parameters, including the wagon design, the wheel-rail contact and the design parameters of the bridge deck and track, as well as the operational parameters – wheel load and speed. To determine these impact forces, a detailed rail train-track/bridge dynamic interaction model has been developed, which includes a comprehensive train model using multi-body dynamics approach and a flexible track/bridge model using Euler– Bernoulli beam theory. Single and multi-span bridges have been modelled to examine their dynamic characteristics. From the single span bridge, the train critical speed is determined; the minimum distance of two peak loadings is found to affect the train critical speed. The impact factor and the dynamic characteristics are discussed.

Producing while consuming: Social interaction around photos shared within private group

User-generated content plays a pivotal role in the current social media. The main focus, however, has been on the explicitly generated user content such as photos, videos and status updates on different social networking sites. In this paper, we explore the potential of implicitly generated user content, based on users’ online consumption behaviors. It is technically feasible to record users’ consumption behaviors on mobile devices and share that with relevant people. Mobile devices with such capabilities could enrich social interactions around the consumed content, but it may also threaten users’ privacy. To understand the potentials of this design direction we created and evaluated a low-fidelity prototype intended for photo sharing within private groups. Our prototype incorporates two design concepts, namely, FingerPrint and MoodPhotos that leverage users’ consumption history and emotional responses. In this paper, we report user values and user acceptance of this prototype from three participatory design workshops.

An intuitive multi-touch surface and gesture based interaction for video surveillance systems

This paper discusses the idea and demonstrates an early prototype of a novel method of interacting with security surveillance footage using natural user interfaces in place of traditional mouse and keyboard interaction. Current surveillance monitoring stations and systems provide the user with a vast array of video feeds from multiple locations on a video wall, relying on the user’s ability to distinguish locations of the live feeds from experience or list based key-value pair of location and camera IDs. During an incident, this current method of interaction may cause the user to spend increased amounts time obtaining situational and location awareness, which is counter-productive. The system proposed in this paper demonstrates how a multi-touch screen and natural interaction can enable the surveillance monitoring station users to quickly identify the location of a security camera and efficiently respond to an incident.

Xanthones from fungi, lichens, and bacteria : the natural products and their synthesis

Many fungi, lichens, and bacteria produce xanthones (derivatives of 9H-xanthen-9-one, “xanthone” from the Greek “xanthos”, for “yellow”) as secondary metabolites. Xanthones are typically polysubstituted and occur as either fully aromatized, dihydro-, tetrahydro-, or, more rarely, hexahydro-derivatives. This family of compounds appeals to medicinal chemists because of their pronounced biological activity within a notably broad spectrum of disease states, a result of their interaction with a correspondingly diverse range of target biomolecules. This has led to the description of xanthones as “privileged structures”.(1) Historically, the total synthesis of the natural products has mostly been limited to fully aromatized targets. Syntheses of the more challenging partially saturated xanthones have less frequently been reported, although the development in recent times of novel and reliable methods for the construction of the (polysubstituted) unsaturated xanthone core holds promise for future endeavors. In particular, the fascinating structural and biological properties of xanthone dimers and heterodimers may excite the synthetic or natural product chemist.

Partial mediation role of self-efficacy between positive social interaction and mental health in family caregivers for dementia patients in Shanghai

We explored the mediation effect of caregiver self-efficacy on the influences of behavioral and psychological symptoms (BPSD) of dementia care recipients (CRs) or family caregivers’ (CGs) social supports (informational, tangible and affectionate support and positive social interaction) on CGs’ mental health. We interviewed 196 CGs, using a battery of measures including demographic data of the dyads, CRs’ dementia-related impairments, and CGs’ social support, self-efficacy and the Medical Outcome Study (MOS) Short-Form (SF-36) Health Survey. Multiple regression analyses showed that gathering information on self-efficacy and managing CG distress self-efficacy were the partial mediators of the relationship between positive social interaction and CG mental health. Managing caregiving distress self-efficacy also partial mediated the impact of BPSD on CG mental health. We discuss implications of the results for improving mental health of the target population in mainland China.

Affordance in interaction

The concept of affordance has different interpretations in the field of Human-Computer Interaction (HCI). However, its treatment has been merely as a one-to-one relationship between a user and a technology. We believe that a broader view of affordances is needed which encompasses social and cultural aspects of our everyday life. We propose an interaction-centered view of affordance that can be useful for developing better understandings of designed artefacts. An interaction-centered view of affordance suggests that affordance is an interpretative relationship between users and the technology that emerges during the users' interaction with the technology in the lived environments. We distinguish two broad classes of affordances: affordance in Information and affordance in Articulation. Affordance in information refers to users' understanding of a technology based on their semantic and syntactic interpretation; and affordance in articulation refers to users' interpretations about the use of the technology. We also argue that the notion of affordance should be treated at two levels: at the 'artefact level' and at the 'practice level'. Consequently, we provide two examples to demonstrate our arguments.