[P,P-Di-tert-butyl-N-trimethylsilyl- P-(trimethylsilylamino)phosphineimidato-N,N]bis(pyridine-N)- lithium(I)

In the title compound, [Li(C14H36N2PSi2)(C5H5N)2], the bulky chelating monoanionic P,P-di-tert-butyl-N-trimethylsilyl-P-(trimethylsilylamino)phosphine imidate ligand and two pyridine ligands bind to Li in a pseudo-tetrahedral arrangement with twofold symmetry. The Li-N [phosphine]distance is 2.048 (5) Å, while the LiP distance is 2.520 (6) Å

i-vector based speaker recognition on short utterances

Robust speaker verification on short utterances remains a key consideration when deploying automatic speaker recognition, as many real world applications often have access to only limited duration speech data. This paper explores how the recent technologies focused around total variability modeling behave when training and testing utterance lengths are reduced. Results are presented which provide a comparison of Joint Factor Analysis (JFA) and i-vector based systems including various compensation techniques; Within-Class Covariance Normalization (WCCN), LDA, Scatter Difference Nuisance Attribute Projection (SDNAP) and Gaussian Probabilistic Linear Discriminant Analysis (GPLDA). Speaker verification performance for utterances with as little as 2 sec of data taken from the NIST Speaker Recognition Evaluations are presented to provide a clearer picture of the current performance characteristics of these techniques in short utterance conditions.

3D ellipsoid fitting for multi-view gait recognition

Gait recognition approaches continue to struggle with challenges including view-invariance, low-resolution data, robustness to unconstrained environments, and fluctuating gait patterns due to subjects carrying goods or wearing different clothes. Although computationally expensive, model based techniques offer promise over appearance based techniques for these challenges as they gather gait features and interpret gait dynamics in skeleton form. In this paper, we propose a fast 3D ellipsoidal-based gait recognition algorithm using a 3D voxel model derived from multi-view silhouette images. This approach directly solves the limitations of view dependency and self-occlusion in existing ellipse fitting model-based approaches. Voxel models are segmented into four components (left and right legs, above and below the knee), and ellipsoids are fitted to each region using eigenvalue decomposition. Features derived from the ellipsoid parameters are modeled using a Fourier representation to retain the temporal dynamic pattern for classification. We demonstrate the proposed approach using the CMU MoBo database and show that an improvement of 15-20% can be achieved over a 2D ellipse fitting baseline.

‘I could eat a horse’! : meal planning determines meal size

Evidence that our food environment can affect meal size is often taken to indicate a failure of ‘conscious control’. By contrast, our research suggests that ‘expected satiation’ (fullness that a food is expected to confer) predicts self-selected meal size. However, the role of meal planning as a determinant of actual meal size remains unresolved, as does the extent to which meal planning is commonplace outside the laboratory. Here, we quantified meal planning and its relation to meal size in a large-cohort study. Participants (N= 764; 25.6 yrs, 78% female) completed a questionnaire containing items relating to their last meal. The majority (91%) of meals were consumed in their entirety. Furthermore, in 92% of these cases the participants decided to consume the whole meal, even before it began. A second major objective was to explore the prospect that meal plans are revised based on within-meal experience (e.g., development of satiation). Only 8% of participants reported ‘unexpected’ satiation that caused them to consume less than anticipated. Moreover, at the end of the meal 57% indicated that they were not fully satiated, and 29% continued eating beyond comfortable satiation (often to avoid wasting food). This pattern was neither moderated by BMI nor dieting status, and was observed across meal types. Together, these data indicate that meals are often planned and that planning corresponds closely with amount consumed. By contrast, we find limited evidence for within-meal modification of these plans, suggesting that ‘pre-meal cognition’ is an important determinant of meal size in humans.

Improving service innovation through structured process-oriented knowledge infrastructure design

Formalised service innovation is a central tenet of enterprise systems lifecycle phases. Event driven process models extended with knowledge objects are found to be not useful in early lifecycle phases. When an upgrade is required, a map of the knowledge infrastructure is needed to better design further service innovation because functional maps no longer adequately describe the context adequately. By looking at formal changes to business processes as service innovations, and recognising the knowledge infrastructure inherent in services generally, changes driven through technology such as ES can be better understood with the application of frameworks such as B-KIDE.

Process mining manifesto

Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.

Clusterin facilitates COMMD1 and I-kB degradation to enhance NF-kB activity in prostate cancer cells

Secretory clusterin (sCLU) is a stress-activated, cytoprotective chaperone that confers broad-spectrum cancer treatment resistance, and its targeted inhibitor (OGX-011) is currently in phase II trials for prostate, lung, and breast cancer. However, the molecular mechanisms by which sCLU inhibits treatment-induced apoptosis in prostate cancer remain incompletely defined. We report that sCLU increases NF-κB nuclear translocation and transcriptional activity by serving as a ubiquitin-binding protein that enhances COMMD1 and I-κB proteasomal degradation by interacting with members of the SCF-βTrCP E3 ligase family. Knockdown of sCLU in prostate cancer cells stabilizes COMMD1 and I-κB, thereby sequestrating NF-κB in the cytoplasm and decreasing NF-κB transcriptional activity. Comparative microarray profiling of sCLU-overexpressing and sCLU-knockdown prostate cancer cells confirmed that the expression of many NF-κB–regulated genes positively correlates with sCLU levels. We propose that elevated levels of sCLU promote prostate cancer cell survival by facilitating degradation of COMMD1 and I-κB, thereby activating the canonical NF-κB pathway.

Stop lecturing me, I want to learn

Re-evaluation of pedagogical practice is driving learning design at Queensland University of Technology. One objective is to support approaches to increase student engagement and attendance in physical and virtual learning spaces through opportunities for active and problem-based learning. This paper provides an overview and preliminary evaluation of the pilot of one of these initiatives, the Open Web Lecture (OWL), a new web-based student response application that seamlessly integrates a virtual learning environment within a physical learning space.

Editorial : International Journal of Knowledge-Based Development

The International Journal of Knowledge Based Development is planned to serve as a platform for the Global Knowledge Based Development Community to exchange academic and professional knowledge and experience, and adopt the learnings in different corners of the globe to achieve a sustainable knowledge-based development. The journal is put together by the executive team of an international think tank (The World Capital Institute – www.worldcapitalinstitute.org). As an international non-profit organization, The World Capital Institute aims to further advance the understanding and application of knowledge capital as the most powerful leverage for development in micro (i.e. individuals-neighborhoods-firms) , mezzo (i.e. communities-cities-clusters), macro (i.e. societies-nations), and supra-macro (supranational-global) levels.