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In the current study, late Chinese-English bilinguals performed a facial expression identification task with emotion words in the task-irrelevant dimension, in either their first language (L1) or second language (L2). The investigation examined the automatic access of the emotional content in words appearing in more than one language. Significant congruency effects were present for both L1 and L2 emotion word processing. Furthermore, the magnitude of emotional face-word Stroop effect in the L1 task was greater as compared to the L2 task, indicating that in L1 participants could access the emotional information in words in a more reliable manner. In summary, these findings provide more support for the automatic access of emotional information in words in the bilinguals' two languages as well as attenuated emotionality of L2 processing.

An increase in the accuracy of identification of Activities of Daily Living (ADL) is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL) tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices. A comprehensive literature search was conducted in order to identify relevant English language works aimed at the identification of the environment of ADLs using data acquired with mobile devices, published between 2002 and 2017. In total, 40 studies were analyzed and selected from 115 citations. The results highlight several audio fingerprinting techniques, including Modified discrete cosine transform (MDCT), Mel-frequency cepstrum coefficients (MFCC), Principal Component Analysis (PCA), Fast Fourier Transform (FFT), Gaussian mixture models (GMM), likelihood estimation, logarithmic moduled complex lapped transform (LMCLT), support vector machine (SVM), constant Q transform (CQT), symmetric pairwise boosting (SPB), Philips robust hash (PRH), linear discriminant analysis (LDA) and discrete cosine transform (DCT). This work was supported by FCT project UID/EEA/50008/2013 (Este trabalho foi suportado pelo projecto FCT UID/EEA/50008/2013). The authors would also like to acknowledge the contribution of the COST Action IC1303—AAPELE—Architectures, Algorithms and Protocols for Enhanced Living Environments.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode. Objectives: To evaluate the implementation and adoption of the NHS detailed care records service in “early adopter” hospitals in England. Design: Theoretically informed, longitudinal qualitative evaluation based on case studies. Setting: 12 “early adopter” NHS acute hospitals and specialist caresettings studied over two and a half years. Data sources: Data were collected through in depth interviews, observations, and relevant documents relating directly to case study sites and to wider national developments that were perceived to impact on the implementation strategy. Data were thematically analysed, initially within and then across cases. The dataset consisted of 431 semistructured interviews with key stakeholders, including hospital staff, developers, and governmental stakeholders; 590 hours of observations of strategic meetings and use of the software in context; 334 sets of notes from observations, researcher’ field notes, and notes from national conferences; 809 NHS documents; and 58 regional and national documents. Results: Implementation has proceeded more slowly, with a narrower scope and substantially less clinical functionality than was originally planned. The national strategy had considerable local consequences (summarised under five key themes), and wider national developments impacted heavily on implementation and adoption. More specifically, delays related to unrealistic expectations about the capabilities of systems; the time needed to build, configure, and customise the software; the work needed to ensure that systems were supporting provision of care; and the needs of end users for training and support. Other factors hampering progress included the changing milieu of NHS policy and priorities; repeatedly renegotiated national contracts; different stages of development of diverse NHS care records service systems; and a complex communication process between different stakeholders, along with contractual arrangements that largely excluded NHS providers. There was early evidence that deploying systems resulted in important learning within and between organisations and the development of relevant competencies within NHS hospitals. Conclusions: Implementation of the NHS Care Records Service in “early adopter” sites proved time consuming and challenging, with as yet limited discernible benefits for clinicians and no clear advantages for patients. Although our results might not be directly transferable to later adopting sites because the functionalities we evaluated were new and untried in the English context, they shed light on the processes involved in implementing major new systems. The move to increased local decision making that we advocated based on our interim analysis has been pursued and welcomed by the NHS, but it is important that policymakers do not lose sight of the overall goal of an integrated interoperable solution.