The application of early contractor involvement and its impact on project performance

Early contractor involvement is a topic that has attracted attention from construction practitioners and researchers in the UK since the 1990s. It has been adopted to introduce construction knowledge and experience to the design process, and to integrate design with construction. In contrast with the limited number of previous studies on early contractor involvement, which used case studies, a questionnaire survey was conducted in this study, to investigate the application of early contractor involvement in current practice and its impact on project performance in terms of time, cost and quality. From an analysis of the questionnaire results, early contractor involvement is found to be increasingly used in the construction industry, and to have a significant impact on cost and time performance. This research provides empirical evidence related to the practice of early contractor involvement. It demonstrates the major influence of early contractor involvement on management processes and working relationships during a project, which contribute to performance improvement and project success.

Data-driven optimal filtering for phase and frequency of noisy oscillations: Application to vortex flow metering

A method for measuring the phase of oscillations from noisy time series is proposed. To obtain the phase, the signal is filtered in such a way that the filter output has minimal relative variation in the amplitude over all filters with complex-valued impulse response. The argument of the filter output yields the phase. Implementation of the algorithm and interpretation of the result are discussed. We argue that the phase obtained by the proposed method has a low susceptibility to measurement noise and a low rate of artificial phase slips. The method is applied for the detection and classification of mode locking in vortex flow meters. A measure for the strength of mode locking is proposed.

Application of guar gum as a flocculant aid in food processing and potable water treatment

The paper deals with use of a food grade coagulant (guar gum) as a replacement for synthetic coagulants for potable water treatment.

Application of proton radiography in experiments of relevance to inertial confinement fusion

Multi-Mev proton beams generated by target normal sheath acceleration (TNSA) during the interaction of an ultra intense laser beam (Ia parts per thousand yen10(19) W/cm(2)) with a thin metallic foil (thickness of the order of a few tens of microns) are particularly suited as a particle probe for laser plasma experiments. The proton imaging technique employs a laser-driven proton beam in a point-projection imaging scheme as a diagnostic tool for the detection of electric fields in such experiments. The proton probing technique has been applied in experiments of relevance to inertial confinement fusion (ICF) such as laser heated gasbags and laser-hohlraum experiments. The data provides direct information on the onset of laser beam filamentation and on the plasma expansion in the hohlraum's interior, and confirms the suitability and usefulness of this technique as an ICF diagnostic.

Stress processes in caring for an end-of-life family member:Application of a theoretical model

Objectives: Family caregivers play a vital role in maintaining the lives of individuals with advanced illness living in the community. However, the responsibility of caregiving for an end-of-life family member can have profound consequences on the psychological, physical and financial well-being of the caregiver. While the literature has identified caregiver stress or strain as a complex process with multiple contributing factors, few comprehensive studies exist. This study examined a wide range of theory-driven variables contributing to family caregiver stress. Method: Data variables from interviews with primary family caregivers were mapped onto the factors within the Stress Process Model theoretical framework. A hierarchical multiple linear regression analysis was used to determine the strongest predictors of caregiver strain as measured by a validated composite index, the Caregiver Strain Index. Results: The study included 132 family caregivers across south-central/western Ontario, Canada. About half of these caregivers experienced high strain, the extent of which was predicted by lower perceived program accessibility, lower functional social support, greater weekly amount of time caregivers committed to the care recipient, younger caregiver age and poorer caregiver self-perceived health. Conclusion: This study examined the influence of a multitude of factors in the Stress Process Model on family caregiver strain, finding stress to be a multidimensional construct. Perceived program accessibility was the strongest predictor of caregiver strain, more so than intensity of care, highlighting the importance of the availability of community resources to support the family caregiving role.

Modelling local-scale determinants and the probability of microarthropod species occurrence in Antarctic soils

Soil fauna in the extreme conditions of Antarctica consists of a few microinvertebrate species patchily distributed at different spatial scales. Populations of the prostigmatic mite Stereotydeus belli and the collembolan Gressittacantha terranova from northern Victoria Land (Antarctica) were used as models to study the effect of soil properties on microarthropod distributions. In agreement with the general assumption that the development and distribution of life in these ecosystems is mainly controlled by abiotic factors, we found that the probability of occurrence of S. belli depends on soil moisture and texture and on the sampling period (which affects the general availability of water); surprisingly, none of the analysed variables were significantly related to the G. terranova distribution. Based on our results and literature data, we propose a theoretical model that introduces biotic interactions among the major factors driving the local distribution of collembolans in Antarctic terrestrial ecosystems. (c) 2007 Elsevier Ltd. All rights reserved.

Application of factor analysis and geostatistics to identify processes controlling the distribution and bioaccessibility of trace elements in Northern Ireland soils

Geologic and environmental factors acting over varying spatial scales can control
trace element distribution and mobility in soils. In turn, the mobility of an element in soil will affect its oral bioaccessibility. Geostatistics, kriging and principal component analysis (PCA) were used to explore factors and spatial ranges of influence over a suite of 8 element oxides, soil organic carbon (SOC), pH, and the trace elements nickel (Ni), vanadium (V) and zinc (Zn). Bioaccessibility testing was carried out previously using the Unified BARGE Method on a sub-set of 91 soil samples from the Northern Ireland Tellus1 soil archive. Initial spatial mapping of total Ni, V and Zn concentrations shows their distributions are correlated spatially with local geologic formations, and prior correlation analyses showed that statistically significant controls were exerted over trace element bioaccessibility by the 8 oxides, SOC and pH. PCA applied to the geochemistry parameters of the bioaccessibility sample set yielded three principal components accounting for 77% of cumulative variance in the data
set. Geostatistical analysis of oxide, trace element, SOC and pH distributions using 6862 sample locations also identified distinct spatial ranges of influence for these variables, concluded to arise from geologic forming processes, weathering processes, and localised soil chemistry factors. Kriging was used to conduct a spatial PCA of Ni, V and Zn distributions which identified two factors comprising the majority of distribution variance. This was spatially accounted for firstly by basalt rock types, with the second component associated with sandstone and limestone in the region. The results suggest trace element bioaccessibility and distribution is controlled by chemical and geologic processes which occur over variable spatial ranges of influence.

Mathematical modelling of quantum yield enhancements of methyl orange photooxidation in aqueous TiO2 suspensions under controlled periodic UV LED illumination

Quantum yields of the photocatalytic degradation of methyl orange under controlled periodic illumination (CPI) have been modelled using existing models. A modified Langmuir-Hinshelwood (L-H) rate equation was used to predict the degradation reaction rates of methyl orange at various duty cycles and a simple photocatalytic model was applied in modelling quantum yield enhancement of the photocatalytic process due to the CPI effect. A good agreement between the modelled and experimental data was observed for quantum yield modelling. The modified L-H model, however, did not accurately predict the photocatalytic decomposition of the dye under periodic illumination.

Compositional data-driven alternatives to single geochemical component maps

Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.