The Voice as Transcursive Inscriber: The Relation of Body and Instrument Understood through the Workings of a Machine

This article examines the relationship of the body with a musical instrument; specifically it looks at the vital threshold conditions that occur during the interplay of voice and instrument. By examining the work ‘IKAS’ (1982) for solo saxophone by German composer Hans-Joachim Hespos, the unusual timbral relationships created between vocal and instrumental sounds are exposed. I argue that this particular work highlights the performer/instrument relation as one marked by Gilles Deleuze’s notion of the workings of a machine and a machine’s relation to a ‘flow’, in particular a machine’s function with view to the break in the flow. By turning towards Deleuze’s concept of the machine, this article offers a slightly different vocabulary for music analysis, one that more easily encompasses certain works of the twentieth century, specifically those that are more timbre- than pitch-based.

Reconfiguring Older Bodies in the Prison Time Machine

It is by mapping an area that the geographer comes to understand the contours and formations of a place. The “place” in this case is the prison world. This article serves to map moments in prison demonstrating how “old” female bodies are performed under the prison gaze. In this article I will illustrate how older women subvert, negotiate, or invoke discourse as a means of reinscribing the normalizing discourses that serve to confine and define older women's experiences in prison. Female elders in prison become defined and confined by regimes of femininity and ageism. They have to endure symbolic and actual intrusions of physical privacy, which serve to remind them of what they were, where they are, and what they have become. This article will critically explore the complexity and contradictions of time use in prison and how they impact on embodied identities. By incorporating the voices of elders, I hope to draw out the contradictions and dilemmas which they experience, thereby illustrating the relationship between time, their involvement in doing time, and the performance of time in a total institution (see Goffman, 1961), and the relationship between temporality and existence. The stories of the women show how their identities are caught within the movement and motion of time and space, both in terms of the time of “the real” on the outside and within prison time. This is the in-between space of carceral time within which women live and which they negotiate. It is by being caught in this network of carceral time that they are constantly being “remade” as their body/performance of identities alters within it. While only a small percentage of the female prison population in the United Kingdom are in later life, one has to question why criminological and gerontological literature fail to address the needs of a growing significant minority.

Cutting edge: Langerin+ dendritic cells in the mesenteric lymph node set the stage for skin and gut immune system cross-talk.

Topical transcutaneous immunization (TCI) presents many clinical advantages, but its underlying mechanism remains unknown. TCI induced Ag-specific IgA Ab-secreting cells expressing CCR9 and CCR10 in the small intestine in a retinoic acid-dependent manner. These intestinal IgA Abs were maintained in Peyer\'s patch-null mice but abolished in the Peyer\'s patch- and lymph node-null mice. The mesenteric lymph node (MLN) was shown to be the site of IgA isotype class switching after TCI. Unexpectedly, langerin(+)CD8alpha(-) dendritic cells emerged in the MLN after TCI; they did not migrate from the skin but rather differentiated rapidly from bone marrow precursors. Depletion of langerin(+) cells impaired intestinal IgA Ab responses after TCI. Taken together, these findings suggest that MLN is indispensable for the induction of intestinal IgA Abs following skin immunization and that cross-talk between the skin and gut immune systems might be mediated by langerin(+) dendritic cells in the MLN.

Support vector machine classification for large data sets via minimum enclosing ball clustering

Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitable for classification of large data sets, because the training complexity of SVM is highly dependent on the size of data set. This paper presents a novel SVM classification approach for large data sets by using minimum enclosing ball clustering. After the training data are partitioned by the proposed clustering method, the centers of the clusters are used for the first time SVM classification. Then we use the clusters whose centers are support vectors or those clusters which have different classes to perform the second time SVM classification. In this stage most data are removed. Several experimental results show that the approach proposed in this paper has good classification accuracy compared with classic SVM while the training is significantly faster than several other SVM classifiers.

Cut down by some cowardly miscreants’: Plant maiming, or the Malicious Cutting of Plants as an Act of Protest in Eighteenth and Nineteenth Century Rural England

Since the publication of Hobsbawm and Rudé's Captain Swing our understanding of the role(s) of covert protests in Hanoverian rural England has advanced considerably. Whilst we now know much about the dramatic practices of incendiarism and animal maiming and the voices of resistance in seemingly straightforward acquisitive acts, one major gap remains. Despite the fact that almost thirty years have passed since E. P. Thompson brought to our attention that under the notorious ‘Black Act’ the malicious cutting of trees was a capital offence, no subsequent research has been published. This paper seeks to address this major lacuna by systematically analysing the practices and patterns of malicious attacks on plants (‘plant maiming’) in the context of late eighteenth- and early nineteenth-century southern England. It is shown that not only did plant maiming take many different forms, attacking every conceivable type of flora, but also that it was universally understood and practised. In some communities plant maiming was the protestors' weapon of choice. As a social practice it therefore embodied wider community beliefs regarding the defence of plebeian livelihoods and identities.

Packet classification by multi-level cutting of the classification space

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs) are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

A hierarchical multiclass support vector machine incorporated with holistic triple learning units

This paper proposes a new hierarchical learning structure, namely the holistic triple learning (HTL), for extending the binary support vector machine (SVM) to multi-classification problems. For an N-class problem, a HTL constructs a decision tree up to a depth of A leaf node of the decision tree is allowed to be placed with a holistic triple learning unit whose generalisation abilities are assessed and approved. Meanwhile, the remaining nodes in the decision tree each accommodate a standard binary SVM classifier. The holistic triple classifier is a regression model trained on three classes, whose training algorithm is originated from a recently proposed implementation technique, namely the least-squares support vector machine (LS-SVM). A major novelty with the holistic triple classifier is the reduced number of support vectors in the solution. For the resultant HTL-SVM, an upper bound of the generalisation error can be obtained. The time complexity of training the HTL-SVM is analysed, and is shown to be comparable to that of training the one-versus-one (1-vs.-1) SVM, particularly on small-scale datasets. Empirical studies show that the proposed HTL-SVM achieves competitive classification accuracy with a reduced number of support vectors compared to the popular 1-vs-1 alternative.