Improvisation, Indeterminacy and Game-Mediated Participation in Network Music Performance

This chapter focuses on the relationship between improvisation and indeterminacy. We discuss the two practices by referring to play theory and game studies and situate it in recent network music performance. We will develop a parallel with game theory in which indeterminacy is seen as a way of articulating situations where structural decisions are left to the discernment of the performers and discuss improvisation as a method of play. The improvisation-indeterminacy relationship is discussed in the context of network music performance, which employs digital networks in the exchange of data between performers and hence relies on topological structures with varying degrees of openness and flexibility. Artists such as Max Neuhaus and The League of Automatic Music Composers initiated the development of a multitude of practices and technologies exploring the network as an environment for music making. Even though the technologies behind “the network” have shifted dramatically since Neuhaus’ use of radio in the 1960’s, a preoccupation with distribution and sharing of artistic agency has remained at the centre of networked practices. Gollo Föllmer, after undertaking an extensive review of network music initiatives, produced a typology that comprises categories as diverse as remix lists, sound toys, real/virtual space installations and network performances. For Föllmer, “the term ‘Net music’ comprises all formal and stylistic kinds of music upon which the specifics of electronic networks leave considerable traces, whereby the electronic networks strongly influence the process of musical production, the musical aesthetic, or the way music is received” (2005: 185).

Androgen-regulated metabolism and biosynthesis in prostate cancer

Metabolic changes are a well-described hallmark of cancer and are responses to changes in the activity of diverse oncogenes and tumour suppressors. For example, steroid hormone biosynthesis is intimately associated with changes in lipid metabolism and represents a therapeutic intervention point in the treatment of prostate cancer (PCa). Both prostate gland development and tumorigenesis rely on the activity of a steroid hormone receptor family member, the androgen receptor (AR). Recent studies have sought to define the biological effect of the AR on PCa by defining the whole-genome binding sites and gene networks that are regulated by the AR. These studies have provided the first systematic evidence that the AR influences metabolism and biosynthesis at key regulatory steps within pathways that have also been defined as points of influence for other oncogenes, including c-Myc, p53 and hypoxia-inducible factor 1α, in other cancers. The success of interfering with these pathways in a therapeutic setting will, however, hinge on our ability to manage the concomitant stress and survival responses induced by such treatments and to define appropriate therapeutic windows.

Improved lexicon-based sentiment analysis for social media analytics

Social media channels, such as Facebook or Twitter, allow for people to express their views and opinions about any public topics. Public sentiment related to future events, such as demonstrations or parades, indicate public attitude and therefore may be applied while trying to estimate the level of disruption and disorder during such events. Consequently, sentiment analysis of social media content may be of interest for different organisations, especially in security and law enforcement sectors. This paper presents a new lexicon-based sentiment analysis algorithm that has been designed with the main focus on real time Twitter content analysis. The algorithm consists of two key components, namely sentiment normalisation and evidence-based combination function, which have been used in order to estimate the intensity of the sentiment rather than positive/negative label and to support the mixed sentiment classification process. Finally, we illustrate a case study examining the relation between negative sentiment of twitter posts related to English Defence League and the level of disorder during the organisation’s related events.

Twitter Sentiment Analysis for Security-Related Information Gathering

Analysing public sentiment about future events, such as demonstration or parades, may provide valuable information while estimating the level of disruption and disorder during these events. Social media, such as Twitter or Facebook, provides views and opinions of users related to any public topics. Consequently, sentiment analysis of social media content may be of interest to different public sector organisations, especially in the security and law enforcement sector. In this paper we present a lexicon-based approach to sentiment analysis of Twitter content. The algorithm performs normalisation of the sentiment in an effort to provide intensity of the sentiment rather than positive/negative label. Following this, we evaluate an evidence-based combining function that supports the classification process in cases when positive and negative words co-occur in a tweet. Finally, we illustrate a case study examining the relation between sentiment of twitter posts related to English Defence League and the level of disorder during the EDL related events.

Stress, eustress and the National Student Survey

The aim was to explore the relationship between sources of stress and a range of coping behaviours on student
satisfaction and motivation. Most research exploring sources of stress construes stress as distress, with little
attempt to consider positive, good stress or ‘eustress’ experiences. A cohort of first-year psychology students (N=88)
were surveyed on a range of stressors. These were amended from the UK National Student Survey (NSS, 2011).
Published university league tables draw heavily on student course satisfaction but study results suggest there was
also merit in measuring students’ intellectual motivation and the extent to which they felt part of a learning
community. Using multiple regression analyses, it was found that even the attributes that normally help one to adjust to change, such as self-efficacy, do little to help the new student adjust to university life, such was the acuteness of perceived stress in the first year. Social opportunities within the university were important to help new students integrate into university life and to help them network and build support. Educators need to consider how course experiences contribute, not just to potential distress but to potential eustress.