Investigating the level of awareness of building assessment tools in the construction industry of Botswana

Environmental building assessment tools have been developed to measure how well or poorly a building is performing, or likely to perform, against a declared set of criteria, or environmental considerations, in order to achieve sustainability principles. Knowledge of environmental building assessment tools is therefore important for successful design and construction of environmentally friendly buildings for countries. The purpose of the research is to investigate the knowledge and level of awareness of environmental building assessment tools among industry practitioners in Botswana. One hundred and seven paper-based questionnaires were delivered to industry practitioners, including architects, engineers, quantity surveyors, real estate developers and academics. Users were asked what they know about building assessment, whether they have used any building assessment tool in the past, and what they perceive as possible barriers to the implementation of environmental building assessment tools in Botswana. Sixty five were returned and statistical analysis, using IBM SPSS V19 software, was used for analysis. Almost 85 per cent of respondents indicate that they are extremely or moderately aware of environmental design. Furthermore, the results indicate that 32 per cent of respondents have gone through formal training, which suggests ‘reasonable knowledge’. This however does not correspond with the use of the tools on the ground as 69 per cent of practitioners report never to have used any environmental building assessment tool in any project. The study highlights the need to develop an assessment tool for Botswana to enhance knowledge and further improve the level of awareness of environmental issues relating to building design and construction.

Computational fluid dynamics modelling of the air movement in an environmental test chamber with a respiring manikin

In recent years, computational fluid dynamics (CFD) has been widely used as a method of simulating airflow and addressing indoor environment problems. The complexity of airflows within the indoor environment would make experimental investigation difficult to undertake and also imposes significant challenges on turbulence modelling for flow prediction. This research examines through CFD visualization how air is distributed within a room. Measurements of air temperature and air velocity have been performed at a number of points in an environmental test chamber with a human occupant. To complement the experimental results, CFD simulations were carried out and the results enabled detailed analysis and visualization of spatial distribution of airflow patterns and the effect of different parameters to be predicted. The results demonstrate the complexity of modelling human exhalation within a ventilated enclosure and shed some light into how to achieve more realistic predictions of the airflow within an occupied enclosure.

Assessment of plant uptake models used in exposure assessment tools for soils contaminated with organic pollutants

The aim of this study was to evaluate and improve the accuracy of plant uptake models for neutral hydrophobic organic pollutants (1 < logKOW < 9, −8 < logKAW < 0) used in regulatory exposure assessment tools, using uncertainty and sensitivity analyses. The models considered were RAIDAR, EUSES, CSOIL, CLEA, and CalTOX. In this research, CSOIL demonstrated the best performance of all five exposure assessment tools for root uptake from polluted soil in comparison with observed data, but no model predicted shoot uptake well. Recalibration of the transpiration and volatilisation parameters improved the performance of CSOIL and CLEA. The dominant pathway for shoot uptake simulated differed according to the properties of the chemical under consideration; those with a higher air–water partition coefficient were transported into shoots via the soil-air-plant pathway, while chemicals with a lower octanol–water partition coefficient and air–water partition coefficient were transported via the root. The soil organic carbon content was a particularly sensitive parameter in each model and using a site specific value improved model performance.

Translation and usability of autism screening and diagnostic tools for autism spectrum conditions in India

There is a critical need for screening and diagnostic tools (SDT) for autism spectrum conditions (ASC) in regional languages in South Asia. To address this, we translated four widely used SDT (Social Communication Disorder Checklist, Autism Spectrum Quotient, Social Communication Questionnaire, and Autism Diagnostic Observation Schedule) into Bengali and Hindi, two main regional languages (∼ 360 million speakers), and tested their usability in children with and without ASC. We found a significant difference in scores between children with ASC (n = 45 in Bengali, n = 40 in Hindi) and typically developing children (n = 43 in Bengali, n = 42 in Hindi) on all SDTs. These results demonstrate that these SDTs are usable in South Asia, and constitute an important resource for epidemiology research and clinical diagnosis in the region.

Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections

A fast simple climate modelling approach is developed for predicting and helping to understand general circulation model (GCM) simulations. We show that the simple model reproduces the GCM results accurately, for global mean surface air temperature change and global-mean heat uptake projections from 9 GCMs in the fifth coupled model inter-comparison project (CMIP5). This implies that understanding gained from idealised CO2 step experiments is applicable to policy-relevant scenario projections. Our approach is conceptually simple. It works by using the climate response to a CO2 step change taken directly from a GCM experiment. With radiative forcing from non-CO2 constituents obtained by adapting the Forster and Taylor method, we use our method to estimate results for CMIP5 representative concentration pathway (RCP) experiments for cases not run by the GCMs. We estimate differences between pairs of RCPs rather than RCP anomalies relative to the pre-industrial state. This gives better results because it makes greater use of available GCM projections. The GCMs exhibit differences in radiative forcing, which we incorporate in the simple model. We analyse the thus-completed ensemble of RCP projections. The ensemble mean changes between 1986–2005 and 2080–2099 for global temperature (heat uptake) are, for RCP8.5: 3.8 K (2.3 × 1024 J); for RCP6.0: 2.3 K (1.6 × 1024 J); for RCP4.5: 2.0 K (1.6 × 1024 J); for RCP2.6: 1.1 K (1.3 × 1024 J). The relative spread (standard deviation/ensemble mean) for these scenarios is around 0.2 and 0.15 for temperature and heat uptake respectively. We quantify the relative effect of mitigation action, through reduced emissions, via the time-dependent ratios (change in RCPx)/(change in RCP8.5), using changes with respect to pre-industrial conditions. We find that the effects of mitigation on global-mean temperature change and heat uptake are very similar across these different GCMs.

Stencil dies: new tools for an old trade

Traces the invention and development of stencil dies in the USA in the middle decades of the nineteenth century, focussing on the work of M. J. Metcalf, A. J. Fullam, and S. M. Spencer.

Computational analysis of the LRRK2 interactome

LRRK2 was identified in 2004 as the causative protein product of the Parkinson’s disease locus designated PARK8. In the decade since then, genetic studies have revealed at least 6 dominant mutations in LRRK2 linked to Parkinson’s disease, alongside one associated with cancer. It is now well established that coding changes in LRRK2 are one of the most common causes of Parkinson’s. Genome-wide association studies (GWAs) have, more recently, reported single nucleotide polymorphisms (SNPs) around the LRRK2 locus to be associated with risk of developing sporadic Parkinson’s disease and inflammatory bowel disorder. The functional research that has followed these genetic breakthroughs has generated an extensive literature regarding LRRK2 pathophysiology; however, there is still no consensus as to the biological function of LRRK2. To provide insight into the aspects of cell biology that are consistently related to LRRK2 activity, we analysed the plethora of candidate LRRK2 interactors available through the BioGRID and IntAct data repositories. We then performed GO terms enrichment for the LRRK2 interactome. We found that, in two different enrichment portals, the LRRK2 interactome was associated with terms referring to transport, cellular organization, vesicles and the cytoskeleton. We also verified that 21 of the LRRK2 interactors are genetically linked to risk for Parkin- son’s disease or inflammatory bowel disorder. The implications of these findings are discussed, with particular regard to potential novel areas of investigation.

Review of monitoring tools for e-learning platforms

The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The Learning Management System (LMS) is the core of the entire e-learning process along with technology, content, and services. This paper investigates the role of model-driven personalisation support modalities in providing enhanced levels of learning and trusted assimilation in an e-learning delivery context. We present an analysis of the impact of an integrated learning path that an e-learning system may employ to track activities and evaluate the performance of learners.

High-resolution melt and morphological analyses of mealybugs (Hemiptera: Pseudococcidae) from cacao: tools for the control of Cacao Swollen Shoot Virus spread

BACKGROUND: Mealybugs (Hemiptera: Coccoidea: Pseudococcidae) are key vectors of badnaviruses, including Cacao Swollen Shoot Virus (CSSV) the most damaging virus affecting cacao (Theobroma cacao L.). The effectiveness of mealybugs as virus vectors is species dependent and it is therefore vital that CSSV resistance breeding programmes in cacao incorporate accurate mealybug identification. In this work the efficacy of a CO1-based DNA barcoding approach to species identification was evaluated by screening a range of mealybugs collected from cacao in seven countries. RESULTS: Morphologically similar adult females were characterised by scanning electron microscopy and then, following DNA extraction, were screened with CO1 barcoding markers. A high degree of CO1 sequence homology was observed for all 11 individual haplotypes including those accessions from distinct geographical regions. This has allowed for the design of a High Resolution Melt (HRM) assay capable of rapid identification of the commonly encountered mealybug pests of cacao. CONCLUSIONS: HRM Analysis (HRMA) readily differentiated between mealybug pests of cacao that can not necessarily be identified by conventional morphological analysis. This new approach, therefore, has potential to facilitate breeding for resistance to CSSV and other mealybug transmitted diseases.

Synapses in digital medium: computational investigations of neural basis of anticipation

Anticipation is an emerging concept that can provide a bridge between the deepest philosophical theories about the nature of life and cognition on one hand and the empirical biological sciences steeped in reductionist and Newtonian conception of causality. Three conceptions of anticipation have been emerging from the literature that may be operationalised in a way leading to a viable empirical programme. The discussion of the research into a novel dynamical concept of anticipating synchronisation lends credence to such a possibility and suggests further links between the three anticipation paradigms. A careful progress mindful to the deep philosophical concerns but also respecting empirical evidence will ultimately lead towards unifying theoretical and empirical biological sciences and may offer progress where reductionist science have been so far faltering.

A survey of data mining techniques for social media analysis

Social network has gained remarkable attention in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. The heavy reliance on social network sites causes them to generate massive data characterised by three computational issues namely; size, noise and dynamism. These issues often make social network data very complex to analyse manually, resulting in the pertinent use of computational means of analysing them. Data mining provides a wide range of techniques for detecting useful knowledge from massive datasets like trends, patterns and rules [44]. Data mining techniques are used for information retrieval, statistical modelling and machine learning. These techniques employ data pre-processing, data analysis, and data interpretation processes in the course of data analysis. This survey discusses different data mining techniques used in mining diverse aspects of the social network over decades going from the historical techniques to the up-to-date models, including our novel technique named TRCM. All the techniques covered in this survey are listed in the Table.1 including the tools employed as well as names of their authors.

TCL/TK for EDA tools

Tcl/Tk scripting language has become the de-facto standard for EDA tools. This paper explains how to start working with Tcl/Tk using simple examples. Two complete applications are presented to show in more detail the capabilities of the language. In one script average power consumption of a digital system is automated. A second script creates a virtual display driven by the simulation of a graphic card.