Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

A Bayesian decision approach for sample size determination in phase II trials

Stallard (1998, Biometrics 54, 279-294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics 50, 337-349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or total gain for a fixed length of time because the rate of gain depends on the proportion: of treatments forwarding to the phase III study. We suggest maximizing the rate of gain, and the resulting optimal one-stage design becomes twice as efficient as Stallard's one-stage design. Furthermore, the new design has a probability of only 0.12 of passing an ineffective treatment to phase III study.

Alkaline hydrothermal treatment of titanate nanostructures

Since its initial proposal in 1998, alkaline hydrothermal processing has rapidly become an established technology for the production of titanate nanostructures. This simple, highly reproducible process has gained a strong research following since its conception. However, complete understanding and elucidation of nanostructure phase and formation have not yet been achieved. Without fully understanding phase, formation, and other important competing effects of the synthesis parameters on the final structure, the maximum potential of these nanostructures cannot be obtained. Therefore this study examined the influence of synthesis parameters on the formation of titanate nanostructures produced by alkaline hydrothermal treatment. The parameters included alkaline concentration, hydrothermal temperature, the precursor material‘s crystallite size and also the phase of the titanium dioxide precursor (TiO2, or titania). The nanostructure‘s phase and morphology was analysed using X-ray diffraction (XRD), Raman spectroscopy and transmission electron microscopy. X-ray photoelectron spectroscopy (XPS), dynamic light scattering (non-invasive backscattering), nitrogen sorption, and Rietveld analysis were used to determine phase, for particle sizing, surface area determinations, and establishing phase concentrations, respectively. This project rigorously examined the effect of alkaline concentration and hydrothermal temperature on three commercially sourced and two self-prepared TiO2 powders. These precursors consisted of both pure- or mixed-phase anatase and rutile polymorphs, and were selected to cover a range of phase concentrations and crystallite sizes. Typically, these precursors were treated with 5–10 M sodium hydroxide (NaOH) solutions at temperatures between 100–220 °C. Both nanotube and nanoribbon morphologies could be produced depending on the combination of these hydrothermal conditions. Both titania and titanate phases are comprised of TiO6 units which are assembled in different combinations. The arrangement of these atoms affects the binding energy between the Ti–O bonds. Raman spectroscopy and XPS were therefore employed in a preliminary study of phase determination for these materials. The change in binding energy from a titania to a titanate binding energy was investigated in this study, and the transformation of titania precursor into nanotubes and titanate nanoribbons was directly observed by these methods. Evaluation of the Raman and XPS results indicated a strengthening in the binding energies of both the Ti (2p3/2) and O (1s) bands which correlated to an increase in strength and decrease in resolution of the characteristic nanotube doublet observed between 320 and 220 cm.1 in the Raman spectra of these products. The effect of phase and crystallite size on nanotube formation was examined over a series of temperatures (100.200 �‹C in 20 �‹C increments) at a set alkaline concentration (7.5 M NaOH). These parameters were investigated by employing both pure- and mixed- phase precursors of anatase and rutile. This study indicated that both the crystallite size and phase affect nanotube formation, with rutile requiring a greater driving force (essentially �\harsher. hydrothermal conditions) than anatase to form nanotubes, where larger crystallites forms of the precursor also appeared to impede nanotube formation slightly. These parameters were further examined in later studies. The influence of alkaline concentration and hydrothermal temperature were systematically examined for the transformation of Degussa P25 into nanotubes and nanoribbons, and exact conditions for nanostructure synthesis were determined. Correlation of these data sets resulted in the construction of a morphological phase diagram, which is an effective reference for nanostructure formation. This morphological phase diagram effectively provides a .recipe book�e for the formation of titanate nanostructures. Morphological phase diagrams were also constructed for larger, near phase-pure anatase and rutile precursors, to further investigate the influence of hydrothermal reaction parameters on the formation of titanate nanotubes and nanoribbons. The effects of alkaline concentration, hydrothermal temperature, crystallite phase and size are observed when the three morphological phase diagrams are compared. Through the analysis of these results it was determined that alkaline concentration and hydrothermal temperature affect nanotube and nanoribbon formation independently through a complex relationship, where nanotubes are primarily affected by temperature, whilst nanoribbons are strongly influenced by alkaline concentration. Crystallite size and phase also affected the nanostructure formation. Smaller precursor crystallites formed nanostructures at reduced hydrothermal temperature, and rutile displayed a slower rate of precursor consumption compared to anatase, with incomplete conversion observed for most hydrothermal conditions. The incomplete conversion of rutile into nanotubes was examined in detail in the final study. This study selectively examined the kinetics of precursor dissolution in order to understand why rutile incompletely converted. This was achieved by selecting a single hydrothermal condition (9 M NaOH, 160 °C) where nanotubes are known to form from both anatase and rutile, where the synthesis was quenched after 2, 4, 8, 16 and 32 hours. The influence of precursor phase on nanostructure formation was explicitly determined to be due to different dissolution kinetics; where anatase exhibited zero-order dissolution and rutile second-order. This difference in kinetic order cannot be simply explained by the variation in crystallite size, as the inherent surface areas of the two precursors were determined to have first-order relationships with time. Therefore, the crystallite size (and inherent surface area) does not affect the overall kinetic order of dissolution; rather, it determines the rate of reaction. Finally, nanostructure formation was found to be controlled by the availability of dissolved titanium (Ti4+) species in solution, which is mediated by the dissolution kinetics of the precursor.

The ageing of alumina hydrolysates synthesized from sec-butoxyaluminium(III)

A combination of X-ray diffraction, thermal analysis and Raman spectroscopy was employed to characterise the ageing of alumina hydrolysates synthesised from the hydrolysis of anhydrous tri-sec-butoxyaluminium(III). X-Ray diffraction showed that the alumino-oxy(hydroxy) hydrolysates were pseudoboehmite. For boehmite the lamellar spacings are in the b direction and multiple d(020) peaks are observed for the un-aged hydrolysate. After 4 h of ageing, a single d(020) peak is observed at 6.53 Å. Thermal analysis showed five endotherms at 70, 140, 238, 351 and 445°C. These endotherms are attributed to the dehydration and dehydroxylation of the boehmite-like hydrolysate. Raman spectroscopy shows the presence of bands for the washed hydrolysates at 333, 355, 414, 455, 475, 495, 530 and 675 cm–1. These bands are attributed to pseudoboehmite. Ageing of the hydrolysates results in an increase in the crystallite size of the pseudoboehmite.

Mechanochemical treatment of kaolinite

Kaolinite surfaces were modified by mechanochemical treatment for periods of time up to 10 h. X-ray diffraction shows a steady decrease in intensity of the d(001) spacing with mechanochemical treatment, resulting in the delamination of the kaolinite and a subsequent decrease in crystallite size with grinding time. Thermogravimetric analyses show the dehydroxylation patterns of kaolinite are significantly modified. Changes in the molecular structure of the kaolinite surface hydroxyls were followed by infrared spectroscopy. Hydroxyls were lost after 10 h of grinding as evidenced by a decrease in intensity of the OH stretching vibrations at 3695 and 3619 cm−1 and the deformation modes at 937 and 915 cm−1. Concomitantly an increase in the hydroxyl stretching vibrations of water is found. The water-bending mode was observed at 1650 cm−1, indicating that water is coordinating to the modified kaolinite surface. Changes in the surface structure of the OSiO units were reflected in the SiO stretching and OSiO bending vibrations. The decrease in intensity of the 1056 and 1034 cm−1 bands attributed to kaolinite SiO stretching vibrations were concomitantly matched by the increase in intensity of additional bands at 1113 and 520 cm−1 ascribed to the new mechanically synthesized kaolinite surface. Mechanochemical treatment of the kaolinite results in a new surface structure.

Implications of precursor chemistry on the alkaline hydrothermal synthesis of titania/titanate nanostructures

A systematic study of four parameters within the alkaline hydrothermal treatment of three commercial titania powders—anatase, rutile, and Degussa P25—was made. These powders were treated with 5, 7.5, 9, and 10 M NaOH between 100 and 220 °C for 20 h. The effects of alkaline concentration, hydrothermal temperature, and precursor phase and crystallite size on the resultant nanostructure formation have been studied through X-ray diffraction, Raman spectroscopy, transmission electron microscopy, and nitrogen adsorption. Through the correlation of these data, morphological phase diagrams were constructed for each commercial powder. Interpretation of the resultant morphological phase diagrams indicates that alkaline concentration and hydrothermal temperature affect nanostructure formation independently, where nanoribbon formation is significantly influenced by temperature for initial formation. The phase and crystallite size of the precursor also significantly influenced nanostructure formation, with rutile displaying a slower rate of precursor consumption compared with anatase. Small crystallite titania precursors formed nanostructures at reduced hydrothermal temperatures.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Nanostructured metal hydrides for hydrogen storage studied by in situ synchrotron and neutron diffraction

This work was focused on studies of the metal hydride materials having a potential in building hydrogen storage systems with high gravimetric and volumetric efficiencies of H storage and formed / decomposed with high rates of hydrogen exchange. In situ diffraction studies of the metal-hydrogen systems were explored as a valuable tool in probing both the mechanism of the phase-structural transformations and their kinetics. Two complementary techniques, namely Neutron Powder Diffraction (NPD) and Synchrotron X-ray diffraction (SR XRD) were utilised. High pressure in situ NPD studies were performed at D2 pressures reaching 1000 bar at the D1B diffractometer accommodated at Institute Laue Langevin, Grenoble. The data of the time resolved in situ SR XRD were collected at the Swiss Norwegian Beam Lines, ESRF, Grenoble in the pressure range up to 50 bar H2 at temperatures 20-400°C. The systems studied by NPD at high pressures included deuterated Al-modified Laves-type C15 ZrFe2-xAlx intermetallics with x = 0.02; 0.04 and 0.20 and the CeNi5-D2 system. D content, hysteresis of H uptake and release, unit cell expansion and stability of the hydrides systematically change with Al content. Deuteration exhibited a very fast kinetics; it resulted in increase of the unit cells volumes reaching 23.5 % for ZrFe1.98Al0.02D2.9(1) and associated with exclusive occupancy of the Zr2(Fe,Al)2 tetrahedra. For CeNi5 deuteration yielded a hexahydride CeNi5D6.2 (20°C, 776 bar D2) and was accompanied by a nearly isotropic volume expansion reaching 30.1% (∆a/a=10.0%; ∆c/c=7.5%). Deuterium atoms fill three different interstitial sites including Ce2Ni2, Ce2Ni3 and Ni4. Significant hysteresis was observed on the first absorption-desorption cycle. This hysteresis decreased on the absorption-desorption cycling. A different approach to the development of H storage systems is based on the hydrides of light elements, first of all the Mg-based ones. These systems were studied by SR XRD. Reactive ball milling in hydrogen (HRBM) allowed synthesis of the nanostructured Mg-based hydrides. The experimental parameters (PH2, T, energy of milling, ball / sample ratio and balls size), significantly influence rate of hydrogenation. The studies confirmed (a) a completeness of hydrogenation of Mg into MgH2; (b) indicated a partial transformation of the originally formed -MgH2 into a metastable -MgH2 (a ratio / was 3/1); (c) yielded the crystallite size for the main hydrogenation product, -MgH2, as close to 10 nm. Influence of the additives to Mg on the structure and hydrogen absorption/desorption properties and cycle behaviour of the composites was established and will be discussed in the paper.

Si quantum dots embedded in an amorphous SiC matrix : nanophase control by non-equilibrium plasma hydrogenation

Nanophase nc-Si/a-SiC films that contain Si quantum dots (QDs) embedded in an amorphous SiC matrix were deposited on single-crystal silicon substrates using inductively coupled plasma-assisted chemical vapor deposition from the reactive silane and methane precursor gases diluted with hydrogen at a substrate temperature of 200 °C. The effect of the hydrogen dilution ratio X (X is defined as the flow rate ratio of hydrogen-to-silane plus methane gases), ranging from 0 to 10.0, on the morphological, structural, and compositional properties of the deposited films, is extensively and systematically studied by scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, Raman spectroscopy, Fourier-transform infrared absorption spectroscopy, and X-ray photoelectron spectroscopy. Effective nanophase segregation at a low hydrogen dilution ratio of 4.0 leads to the formation of highly uniform Si QDs embedded in the amorphous SiC matrix. It is also shown that with the increase of X, the crystallinity degree and the crystallite size increase while the carbon content and the growth rate decrease. The obtained experimental results are explained in terms of the effect of hydrogen dilution on the nucleation and growth processes of the Si QDs in the high-density plasmas. These results are highly relevant to the development of next-generation photovoltaic solar cells, light-emitting diodes, thin-film transistors, and other applications.

Reconstruction of a multi-vent kimberlite eruption from deposit and host rock characteristics: Jericho kimberlite, Nunavut, Canada

The Jericho kimberlite (173.1. ±. 1.3. Ma) is a small (~. 130. ×. 70. m), multi-vent system that preserves products from deep (>. 1. km?) portions of kimberlite vents. Pit mapping, drill core examination, petrographic study, image analysis of olivine crystals (grain size distributions and shape studies), and compositional and mineralogical studies, are used to reconstruct processes from near-surface magma ascent to kimberlite emplacement and alteration. The Jericho kimberlite formed by multiple eruptions through an Archean granodiorite batholith that was overlain by mid-Devonian limestones ~. 1. km in thickness. Kimberlite magma ascended through granodiorite basement by dyke propagation but ascended through limestone, at least in part, by locally brecciating the host rocks. After the first explosive breakthrough to surface, vent deepening and widening occurred by the erosive forces of the waxing phase of the eruption, by gravitationally induced failures as portions of the vent margins slid into the vent and, in the deeper portions of the vent (>. 1. km), by scaling, as thin slabs burst from the walls into the vent. At currently exposed levels, coherent kimberlite (CK) dykes (<. 40. cm thick) are found to the north and south of the vent complex and represent the earliest preserved in-situ products of Jericho magmatism. Timing of CK emplacement on the eastern side of the vent complex is unclear; some thick CK (15-20. m) may have been emplaced after the central vent was formed. Explosive eruptive products are preserved in four partially overlapping vents that are roughly aligned along strike with the coherent kimberlite dyke. The volcaniclastic kimberlite (VK) facies are massive and poorly sorted, with matrix- to clast-supported textures. The VK facies fragmented by dry, volatile-driven processes and were emplaced by eruption column collapse back into the volcanic vents. The first explosive products, poorly preserved because of partial destruction by later eruptions, are found in the central-east vent and were formed by eruption column collapse after the vent was largely cleared of country rock debris. The next active vent was either the north or south vent. Collapse of the eruption column, linked to a vent widening episode, resulted in coeval avalanching of pipe margin walls into the north vent, forming interstratified lenses of country rock-rich boulder breccias in finer-grained volcaniclastic kimberlite. South vent kimberlite has similar characteristics to kimberlite of the north vent and likely formed by similar processes. The final eruptive phase formed olivine-rich and moderately sorted deposits of the central vent. Better sorting is attributed to recycling of kimberlite debris by multiple eruptions through the unconsolidated volcaniclastic pile and associated collapse events. Post-emplacement alteration varies in intensity, but in all cases, has overprinted the primary groundmass and matrix, in CK and VK, respectively. Erosion has since removed all limestone cover.

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.

Asphalt concrete surfaces macrotexture determination from still images

Road surface macrotexture is identified as one of the factors contributing to the surface's skid resistance. Existing methods of quantifying the surface macrotexture, such as the sand patch test and the laser profilometer test, are either expensive or intrusive, requiring traffic control. High-resolution cameras have made it possible to acquire good quality images from roads for the automated analysis of texture depth. In this paper, a granulometric method based on image processing is proposed to estimate road surface texture coarseness distribution from their edge profiles. More than 1300 images were acquired from two different sites, extending to a total of 2.96 km. The images were acquired using camera orientations of 60 and 90 degrees. The road surface is modeled as a texture of particles, and the size distribution of these particles is obtained from chord lengths across edge boundaries. The mean size from each distribution is compared with the sensor measured texture depth obtained using a laser profilometer. By tuning the edge detector parameters, a coefficient of determination of up to R2 = 0.94 between the proposed method and the laser profilometer method was obtained. The high correlation is also confirmed by robust calibration parameters that enable the method to be used for unseen data after the method has been calibrated over road surface data with similar surface characteristics and under similar imaging conditions.