Gaming Business Communities: Developing online learning organisations to foster communities, develop leadership, and grow interpersonal education

This paper explores, through observation and testing, what possibilities from gaming can be extended into other realms of human interaction to help bring people together, extend education, and grow business. It uses through action learning within the safety of the virtual world within Massively Multiplayer Online Games. Further, I explore how the world of online gaming provides opportunity to train a wide range of skills through extending Revans’ (1980) learning equation and action inquiry methodology. This equation and methodology are deployed in relation to a gaming community to see if the theories could produce strong relationships within organisations and examine what learning, if any, is achievable. I also investigate the potential for changes in business (e.g., employee and customer relationships) through involvement in the gaming community as a unique place to implement action learning. The thesis also asks the following questions on a range of extended possibilities in the world of online gaming: What if the world opened up to a social environment where people could discuss their successes and failures? What if people could take a real world issue and re‐create it in the safe virtual world to test ways of dealing with it? What education answers can the world of online gaming provide

Non-leftmost Unfolding in Partial Evaluation of Logic Programs with Impure Predicates

Abstract. Partial evaluation of logic programs which contain impure predicates poses non-trivial challenges. Impure predicates include those which produce side-effects, raise errors (or exceptions), and those whose truth value varies according to the degree of instantiation of arguments 4. In particular, non-leftmost unfolding steps can produce incorrect results since the independence of the computation rule no longer holds in the presence of impure predicates. Existing proposals allow non-leftmost unfolding steps, but at the cost of accuracy: bindings and failure are not propagated backwards to predicates which are potentially impure. In this work we propose a partial evaluation scheme which substantially reduces the situations in which such backpropagation has to be avoided. With this aim, our partial evaluator takes into account the information about purity of predicates expressed in terms of assertions. This allows achieving some optimizations which are not feasible using existing partial evaluation techniques. We argue that our proposal goes beyond existing ones in that it is a) accurate, since the classification of pure vs impure is done at the level of atoms instead of predicates, b) extensible, as the information about purity can be added to programs using assertions without having to modify the partial evaluator itself, and c) automatic, since (backwards) analysis can be used to automatically infer the required assertions. Our approach has been implemented in the context of CiaoPP, the abstract interpretation-based preprocessor of the Ciao logic programming system.

Detection of Airborne Biological Particles in Indoor Air Using a Real-Time Advanced Morphological Parameter UV-LIF Spectrometer and Gradient Boosting Ensemble Decision Tree Classifiers

We present results from a study evaluating the utility of supervised machine learning to classify single particle ultraviolet laser-induced fluorescence (UV-LIF) signatures to investigate airborne primary biological aerosol particle (PBAP) concentrations in a busy, multifunctional building using a Multiparameter Bioaerosol Spectrometer. First we introduce and demonstrate a gradient boosting ensemble decision tree algorithm’s ability to accurately classify laboratory generated PBAP samples into broad taxonomic classes with a high level of accuracy. We then develop a framework to appraise the classification accuracy and performance using the Hellinger distance metric to compare product parameter probability density function similarity; this framework showed that key training classes were sufficiently different in terms of particle fluorescence and morphology to facilitate classification. We also demonstrate the utility of including advanced morphological parameters to minimise inter-class conflation and improve classification confidence, where relying on the fluorescent spectra alone would likely result in misattribution. Finally, we apply these methods to ambient data collected within a large multi-functional building where ambient bacterial- and fungal-like classes were identified to display trends corresponding to human activity; fungal-like classes displayed a consistent diurnal trend with a maximum at midday and hourly peaks correlating to movements within the building; bacteria-like aerosol displayed complex, episodic events during opening hours. All PBAP classes fell to low baseline concentrations when the building was unoccupied overnight and at weekendsPeer reviewe

Unexpected vertical structure of the Saharan Air Layer and giant dust particles during AER-D

The Saharan Air Layer (SAL) in the summertime eastern Atlantic is typically well mixed and 3-4 km deep, overlying the marine boundary layer (MBL). In this paper, we show experimental evidence that at times a very different structure can be observed. During the AERosol properties - Dust (AER-D) airborne campaign in August 2015, the typical structure described above was observed most of the time, and was associated with a moderate dust content yielding an aerosol optical depth (AOD) of 0.3-0.4 at 355 nm. In an intense event, however, an unprecedented vertical structure was observed close to the eastern boundary of the basin, displaying an uneven vertical distribution and a very large AOD (1.5-2), with most of the dust in a much lower level than usual (0.3-2 km). Estimated dust concentrations and column loadings for all flights during the campaign spanned 300-5500 and 0.8-7.5 g m−2, respectively. The shortwave direct radiative impact of the intense dust event has been evaluated to be as large as −260±30 and −120±15 W m−2 at the surface and top of atmosphere (TOA), respectively. We also report the correlation of this event with anomalous lightning activity in the Canary Islands. In all cases, our measurements detected a broad distribution of aerosol sizes, ranging from ∼0.1 to ∼80 µm (diameter), thus highlighting the presence of giant particles. Giant dust particles were also found in the MBL. We note that most aerosol models may miss the giant particles due to the fact that they use size bins up to 10-25 µm. The unusual vertical structure and the giant particles may have implications for dust transport over the Atlantic during intense events and may affect the estimate of dust deposited to the ocean. We believe that future campaigns could focus more on events with high aerosol load and that instrumentation capable of detecting giant particles will be key to dust observations in this part of the world

Airborne Bacterial and Eukaryotic Community Structure across the United Kingdom Revealed by High-Throughput Sequencing

Primary biological aerosols often include allergenic and pathogenic microorganisms posing potential risks to human health. Moreover, there are airborne plant and animal pathogens that may have ecological and economic impact. In this study, we used high-throughput sequencing techniques (Illumina, MiSeq) targeting the 16S rRNA genes of bacteria and the 18S rRNA genes of eukaryotes, to characterize airborne primary biological aerosols. We used a filtration system on the UK Facility for Airborne Atmospheric Measurements (FAAM) research aircraft to sample a range of primary biological aerosols across southern England overflying surface measurement sites from Chilbolton to Weybourne. We identified 30 to 60 bacterial operational taxonomic units (OTUs) and 108 to 224 eukaryotic OTUs per sample. Moreover, 16S rRNA gene sequencing identified significant numbers of genera that have not been found in atmospheric samples previously or only been described in limited number of atmospheric field studies, which are rather old or published in local journals. This includes the genera Gordonia, Lautropia, and Psychroglaciecola. Some of the bacterial genera found in this study include potential human pathogens, for example, Gordonia, Sphingomonas, Chryseobacterium, Morganella, Fusobacterium, and Streptococcus. 18S rRNA gene sequencing showed Cladosporium to be the major genus in all of the samples, which is a well-known allergen and often found in the atmosphere. There were also genetic signatures of potentially allergenic taxa; for example, Pleosporales, Phoma, and Brassicales. Although there was no significant clustering of bacterial and eukaryotic communities depending on the sampling location, we found meteorological factors explaining significant variations in the community composition. The findings in this study support the application of DNA-based sequencing technologies for atmospheric science studies in combination with complementary spectroscopic and microscopic techniques for improved identification of primary biological aerosols

Query Evaluation in Deductive Databases

It is desirable to answer queries posed to deductive databases by computing fixpoints because such computations are directly amenable to set-oriented fact processing. However, the classical fixpoint procedures based on bottom-up processing — the naive and semi-naive methods — are rather primitive and often inefficient. In this article, we rely on bottom-up meta-interpretation for formalizing a new fixpoint procedure that performs a different kind of reasoning: We specify a top-down query answering method, which we call the Backward Fixpoint Procedure. Then, we reconsider query evaluation methods for recursive databases. First, we show that the methods based on rewriting on the one hand, and the methods based on resolution on the other hand, implement the Backward Fixpoint Procedure. Second, we interpret the rewritings of the Alexander and Magic Set methods as specializations of the Backward Fixpoint Procedure. Finally, we argue that such a rewriting is also needed in a database context for implementing efficiently the resolution-based methods. Thus, the methods based on rewriting and the methods based on resolution implement the same top-down evaluation of the original database rules by means of auxiliary rules processed bottom-up