Determination of particle concentration in the breathing zone for four different types of office ventilation systems

Many factors affect the airflow patterns, thermal comfort, contaminant removal efficiency and indoor air quality at individual workstations in office buildings. In this study, four ventilation systems were used in a test chamber designed to represent an area of a typical office building floor and reproduce the real characteristics of a modern office space. Measurements of particle concentration and thermal parameters (temperature and velocity) were carried out for each of the following types of ventilation systems: a) conventional air distribution system with ceiling supply and return; b) conventional air distribution system with ceiling supply and return near the floor; c) underfloor air distribution system; and d) split system. The measurements aimed to analyse the particle removal efficiency in the breathing zone and the impact of particle concentration on an individual at the workstation. The efficiency of the ventilation system was analysed by measuring particle size and concentration, ventilation effectiveness and the Indoor/Outdoor ratio. Each ventilation system showed different airflow patterns and the efficiency of each ventilation system in the removal of the particles in the breathing zone showed no correlation with particle size and the various methods of analyses used.

What lies beneath? : The pattern and abundance of the subterranean tuber bank of the invasive liana cat’s claw creeper, Macfadyena unguis-cati (Bignoniaceae)

Cat’s claw creeper, Macfadyena unguis-cati (L.) Gentry (Bignoniaceae) is a major environmental weed of riparian areas, rainforest communities and remnant natural vegetation in coastal Queensland and New South Wales, Australia. In densely infested areas, it smothers standing vegetation, including large trees, and causes canopy collapse. Quantitative data on the ecology of this invasive vine are generally lacking. The present study examines the underground tuber traits of M. unguis-cati and explores their links with aboveground parameters at five infested sites spanning both riparian and inland vegetation. Tubers were abundant in terms of density (~1000 per m2), although small in size and low in level of interconnectivity. M. unguis-cati also exhibits multiple stems per plant. Of all traits screened, the link between stand (stem density) and tuber density was the most significant and yielded a promising bivariate relationship for the purposes of estimation, prediction and management of what lies beneath the soil surface of a given M. unguis-cati infestation site. The study also suggests that new recruitment is primarily from seeds, not from vegetative propagation as previously thought. The results highlight the need for future biological-control efforts to focus on introducing specialist seed- and pod-feeding insects to reduce seed-output.

BioPatML : pattern sharing for the genomic sciences

Computational biology increasingly demands the sharing of sophisticated data and annotations between research groups. Web 2.0 style sharing and publication requires that biological systems be described in well-defined, yet flexible and extensible formats which enhance exchange and re-use. In contrast to many of the standards for exchange in the genomic sciences, descriptions of biological sequences show a great diversity in format and function, impeding the definition and exchange of sequence patterns. In this presentation, we introduce BioPatML, an XML-based pattern description language that supports a wide range of patterns and allows the construction of complex, hierarchically structured patterns and pattern libraries. BioPatML unifies the diversity of current pattern description languages and fills a gap in the set of XML-based description languages for biological systems. We discuss the structure and elements of the language, and demonstrate its advantages on a series of applications, showing lightweight integration between the BioPatML parser and search engine, and the SilverGene genome browser. We conclude by describing our site to enable large scale pattern sharing, and our efforts to seed this repository.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

Power law distributions in pattern dynamics of attacker-defender dyads in the team sport of Rugby Union : phenomena in a region of self-organized criticality?

In the region of self-organized criticality (SOC) interdependency between multi-agent system components exists and slight changes in near-neighbor interactions can break the balance of equally poised options leading to transitions in system order. In this region, frequency of events of differing magnitudes exhibits a power law distribution. The aim of this paper was to investigate whether a power law distribution characterized attacker-defender interactions in team sports. For this purpose we observed attacker and defender in a dyadic sub-phase of rugby union near the try line. Videogrammetry was used to capture players’ motion over time as player locations were digitized. Power laws were calculated for the rate of change of players’ relative position. Data revealed that three emergent patterns from dyadic system interactions (i.e., try; unsuccessful tackle; effective tackle) displayed a power law distribution. Results suggested that pattern forming dynamics dyads in rugby union exhibited SOC. It was concluded that rugby union dyads evolve in SOC regions suggesting that players’ decisions and actions are governed by local interactions rules.

Human cortical processing of colour and pattern

Investigated human visual processing of simple two-colour patterns using a delayed match to sample paradigm with positron emission tomography (PET). This study is unique in that the authors specifically designed the visual stimuli to be the same for both pattern and colour recognition with all patterns being abstract shapes not easily verbally coded composed of two-colour combinations. The authors did this to explore those brain regions required for both colour and pattern processing and to separate those areas of activation required for one or the other. 10 right-handed male volunteers aged 18–35 yrs were recruited. The authors found that both tasks activated similar occipital regions, the major difference being more extensive activation in pattern recognition. A right-sided network that involved the inferior parietal lobule, the head of the caudate nucleus, and the pulvinar nucleus of the thalamus was common to both paradigms. Pattern recognition also activated the left temporal pole and right lateral orbital gyrus, whereas colour recognition activated the left fusiform gyrus and several right frontal regions.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Kallikrein-related peptidase 4 activation of protease-activated receptor family members and association with prostate cancer

Two areas of particular importance in prostate cancer progression are primary tumour development and metastasis. These processes involve a number of physiological events, the mediators of which are still being discovered and characterised. Serine proteases have been shown to play a major role in cancer invasion and metastasis. The recently discovered phenomenon of their activation of a receptor family known as the protease activated receptors (PARs) has extended their physiological role to that of signaling molecule. Several serine proteases are expressed by malignant prostate cancer cells, including members of the kallikreinrelated peptidase (KLK) serine protease family, and increasingly these are being shown to be associated with prostate cancer progression. KLK4 is highly expressed in the prostate and expression levels increase during prostate cancer progression. Critically, recent studies have implicated KLK4 in processes associated with cancer. For example, the ectopic over-expression of KLK4 in prostate cancer cell lines results in an increased ability of these cells to form colonies, proliferate and migrate. In addition, it has been demonstrated that KLK4 is a potential mediator of cellular interactions between prostate cancer cells and osteoblasts (bone forming cells). The ability of KLK4 to influence cellular behaviour is believed to be through the selective cleavage of specific substrates. Identification of relevant in vivo substrates of KLK4 is critical to understanding the pathophysiological roles of this enzyme. Significantly, recent reports have demonstrated that several members of the KLK family are able to activate PARs. The PARs are relatively new members of the seven transmembrane domain containing G protein coupled receptor (GPCR) family. PARs are activated through proteolytic cleavage of their N-terminus by serine proteases, the resulting nascent N-terminal binds intramolecularly to initiate receptor activation. PARs are involved in a number of patho-physiological processes, including vascular repair and inflammation, and a growing body of evidence suggests roles in cancer. While expression of PAR family members has been documented in several types of cancers, including prostate, the role of these GPCRs in prostate cancer development and progression is yet to be examined. Interestingly, several studies have suggested potential roles in cellular invasion through the induction of cytoskeletal reorganisation and expression of basement membrane-degrading enzymes. Accordingly, this program of research focussed on the activation of the PARs by the prostate cancer associated enzyme KLK4, cellular processing of activated PARs and the expression pattern of receptor and agonist in prostate cancer. For these studies KLK4 was purified from the conditioned media of stably transfected Sf9 insect cells expressing a construct containing the complete human KLK4 coding sequence in frame with a V5 epitope and poly-histidine encoding sequences. The first aspect of this study was the further characterisation of this recombinant zymogen form of KLK4. The recombinant KLK4 zymogen was demonstrated to be activatable by the metalloendopeptidase thermolysin and amino terminal sequencing indicated that thermolysin activated KLK4 had the predicted N-terminus of mature active KLK4 (31IINED). Critically, removal of the pro-region successfully generated a catalytically active enzyme, with comparable activity to a previously published recombinant KLK4 produced from S2 insect cells. The second aspect of this study was the activation of the PARs by KLK4 and the initiation of signal transduction. This study demonstrated that KLK4 can activate PAR-1 and PAR-2 to mobilise intracellular Ca2+, but failed to activate PAR-4. Further, KLK4 activated PAR-1 and PAR-2 over distinct concentration ranges, with KLK4 activation and mobilisation of Ca2+ demonstrating higher efficacy through PAR-2. Thus, the remainder of this study focussed on PAR-2. KLK4 was demonstrated to directly cleave a synthetic peptide that mimicked the PAR-2 Nterminal activation sequence. Further, KLK4 mediated Ca2+ mobilisation through PAR-2 was accompanied by the initiation of the extra-cellular regulated kinase (ERK) cascade. The specificity of intracellular signaling mediated through PAR-2 by KLK4 activation was demonstrated by siRNA mediated protein depletion, with a reduction in PAR-2 protein levels correlating to a reduction in KLK4 mediated Ca2+mobilisation and ERK phosphorylation. The third aspect of this study examined cellular processing of KLK4 activated PAR- 2 in a prostate cancer cell line. PAR-2 was demonstrated to be expressed by five prostate derived cell lines including the prostate cancer cell line PC-3. It was also demonstrated by flow cytometry and confocal microscopy analyses that activation of PC-3 cell surface PAR-2 by KLK4 leads to internalisation of this receptor in a time dependent manner. Critically, in vivo relevance of the interaction between KLK4 and PAR-2 was established by the observation of the co-expression of receptor and agonist in primary prostate cancer and prostate cancer bone lesion samples by immunohistochemical analysis. Based on the results of this study a number of exciting future studies have been proposed, including, delineating differences in KLK4 cellular signaling via PAR-1 and PAR-2 and the role of PAR-1 and PAR-2 activation by KLK4 in prostate cancer cells and bone cells in prostate cancer progression.

Effective pattern taxonomy mining in text documents

Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.

Bit-pattern based integral attack

Integral attacks are well-known to be effective against byte-based block ciphers. In this document, we outline how to launch integral attacks against bit-based block ciphers. This new type of integral attack traces the propagation of the plaintext structure at bit-level by incorporating bit-pattern based notations. The new notation gives the attacker more details about the properties of a structure of cipher blocks. The main difference from ordinary integral attacks is that we look at the pattern the bits in a specific position in the cipher block has through the structure. The bit-pattern based integral attack is applied to Noekeon, Serpent and present reduced up to 5, 6 and 7 rounds, respectively. This includes the first attacks on Noekeon and present using integral cryptanalysis. All attacks manage to recover the full subkey of the final round.

Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.