Human Perception of Laughter from Context-free Whole Body Motion Dynamic Stimuli

Laughter is a ubiquitous social signal in human interactions yet it remains understudied from a scientific point of view. The need to understand laughter and its role in human interactions has become more pressing as the ability to create conversational agents capable of interacting with humans has come closer to a reality. This paper reports on three aspects of the human perception of laughter when context has been removed and only the body information from the laughter episode remains. We report on ability to categorise the laugh type and the sex of the laugher; the relationship between personality factors with laughter categorisation and perception; and finally the importance of intensity in the perception and categorisation of laughter.

Probabilistic Planning in AgentSpeak using the POMDP framework.

AgentSpeak is a logic-based programming language, based on the Belief-Desire-Intention (BDI) paradigm, suitable for building complex agent-based systems. To limit the computational complexity, agents in AgentSpeak rely on a plan library to reduce the planning problem to the much simpler problem of plan selection. However, such a plan library is often inadequate when an agent is situated in an uncertain environment. In this paper, we propose the AgentSpeak+ framework, which extends AgentSpeak with a mechanism for probabilistic planning. The beliefs of an AgentSpeak+ agent are represented using epistemic states to allow an agent to reason about its uncertain observations and the uncertain effects of its actions. Each epistemic state consists of a POMDP, used to encode the agent’s knowledge of the environment, and its associated probability distribution (or belief state). In addition, the POMDP is used to select the optimal actions for achieving a given goal, even when facing uncertainty.

Handling Sequential Observations in Intelligent Surveillance

Demand for intelligent surveillance in public transport systems is growing due to the increased threats of terrorist attack, vandalism and litigation. The aim of intelligent surveillance is in-time reaction to information received from various monitoring devices, especially CCTV systems. However, video analytic algorithms can only provide static assertions, whilst in reality, many related events happen in sequence and hence should be modeled sequentially. Moreover, analytic algorithms are error-prone, hence how to correct the sequential analytic results based on new evidence (external information or later sensing discovery) becomes an interesting issue. In this paper, we introduce a high-level sequential observation modeling framework which can support revision and update on new evidence. This framework adapts the situation calculus to deal with uncertainty from analytic results. The output of the framework can serve as a foundation for event composition. We demonstrate the significance and usefulness of our framework with a case study of a bus surveillance project.

Criminal Justice Reforms in Northern Ireland: The Agents of Change

This chapter examines who and what brought about the transformation in the criminal justice system of Northern Ireland between 1998 and 2015, seeking to pinpoint the critical moments which stimulated the reforms, how they were delivered, and through what processes they are now being maintained. It seeks to identify the key agents of change and considers whether it is possible to generalise from Northern Ireland’s experience so that other conflicted societies might benefit from the lessons learned.

Transforming Growth Factor-beta superfamily:evaluation as breast cancer biomarkers and preventive agents

The Transforming Growth Factor-beta (TGFbeta) superfamily of cytokines is comprised of a number of structurally-related, secreted polypeptides that regulate a multitude of cellular processes including proliferation, differentiation and neoplastic transformation. These growth regulatory molecules induce ligand-mediated hetero-oligomerization of distinct type II and type I serine/threonine kinase receptors that transmit signals predominantly through receptor-activated Smad proteins but also induce Smad-independent pathways. Ligands, receptors and intracellular mediators of signaling initiated by members of the TGFbeta family are expressed in the mammary gland and disruption of these pathways may contribute to the development and progression of human breast cancer. Since many facets of TGFbeta and breast cancer have been recently reviewed in several articles, except for discussion of recent developments on some aspects of TGFbeta, the major focus of this review will be on the role of activins, inhibins, BMPs, nodal and MIS-signaling in breast cancer with emphasis on their utility as potential diagnostic, prognostic and therapeutic targets.

Multi-agents modelling of EV purchase willingness based on questionnaires

Traditional experimental economics methods often consume enormous resources of qualified human participants, and the inconsistence of a participant’s decisions among repeated trials prevents investigation from sensitivity analyses. The problem can be solved if computer agents are capable of generating similar behaviors as the given participants in experiments. An experimental economics based analysis method is presented to extract deep information from questionnaire data and emulate any number of participants. Taking the customers’ willingness to purchase electric vehicles (EVs) as an example, multi-layer correlation information is extracted from a limited number of questionnaires. Multi-agents mimicking the inquired potential customers are modelled through matching the probabilistic distributions of their willingness embedded in the questionnaires. The authenticity of both the model and the algorithm is validated by comparing the agent-based Monte Carlo simulation results with the questionnaire-based deduction results. With the aid of agent models, the effects of minority agents with specific preferences on the results are also discussed.

The utility of animal models in developing immunosuppressive agents

The immune system comprises an integrated network of cellular interactions. Some responses are predictable, while others are more stochastic. While in vitro the outcome of stimulating a single type of cell may be stereotyped and reproducible, in vivo this is often not the case. This phenomenon often merits the use of animal models in predicting the impact of immunosuppressant drugs. A heavy burden of responsibility lies on the shoulders of the investigator when using animal models to study immunosuppressive agents. The principles of the three R׳s: refine (less suffering,), reduce (lower animal numbers) and replace (alternative in vitro assays) must be applied, as described elsewhere in this issue. Well designed animal model experiments have allowed us to develop all the immunosuppressive agents currently available for treating autoimmune disease and transplant recipients. In this review, we examine the common animal models used in developing immunosuppressive agents, focusing on drugs used in transplant surgery. Autoimmune diseases, such as multiple sclerosis, are covered elsewhere in this issue. We look at the utility and limitations of small and large animal models in measuring potency and toxicity of immunosuppressive therapies.

Novel microtubule-targeting agents, pyrrolo-1,5-benzoxazepines, induce cell cycle arrest and apoptosis in prostate cancer cells

Advanced hormone-refractory prostate cancer is associated with poor prognosis and limited treatment options. Members of the pyrrolo-1,5-benzoxazepine (PBOX) family of compounds exhibit anti-cancer properties in cancer cell lines (including multi-drug resistant cells), ex vivo patient samples and in vivo mouse tumour models with minimal toxicity to normal cells. Recently, they have also been found to possess anti-angiogenic properties in vitro. However, both the apoptotic pathways and the overall extent of the apoptotic response induced by PBOX compounds tend to be cell-type specific. Since the effect of the PBOX compounds on prostate cancer has not yet been elucidated, the purpose of this study was to investigate if PBOX compounds induce anti-proliferative effects on hormone-refractory prostate cancer cells. We examined the effect of two representative PBOX compounds, PBOX-6 and PBOX-15, on the androgen-independent human prostate adenocarcinoma cell line, PC3. PBOX-6 and -15 displayed anti-proliferative effects on PC3 cells, mediated initially through a sustained G2/M arrest. G2/M arrest, illustrated as DNA tetraploidy, was accompanied by microtubule depolymerisation and phosphorylation of anti-apoptotic proteins Bcl-2 and Bcl-xL and the mitotic spindle checkpoint protein BubR1. Phosphorylation of BubR1 is indicative of an active mitotic checkpoint and results in maintenance of cell cycle arrest. G2/M arrest was followed by apoptosis illustrated by DNA hypoploidy and PARP cleavage and was accompanied by degradation of BubR1, Bcl-2 and Bcl-xL. Furthermore, sequential treatment with the CDK1-inhibitor, flavopiridol, synergistically enhanced PBOX-induced apoptosis. In summary, this in vitro study indicates that PBOX compounds may be useful alone or in combination with other agents in the treatment of hormone-refractory prostate cancer.