The role of operations management in public sector policy and practice alignment: a local government analysis

In responding to the demand for change and improvement, local government has applied a plethora of operations management-based methods, tools and techniques. This article explores how these methods, specifically in the form of performance management models, are used to improve alignment between central government policy and local government practice, an area which has thus far been neglected in the literature. Using multiple case studies from Environmental Waste Management Services, this research reports that models derived in the private sector are often directly ‘implanted’ into the public sector. This has challenged the efficacy of all performance management models. However, those organisations which used models most effectively did so by embedding (contextualisation) and extending (reconceptualisation) them beyond their original scope. Moreover, success with these models created a cumulative effect whereby other operations management approaches were probed, adapted and used.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

Local delivery of chlorhexidine using a tooth-bonded delivery system

Films containing 20% w/w chlorhexidine base (particle size 63-125 mu m) in poly(epsilon-caprolactone), MW 35 000-45 000, were prepared by solvent evaporation and sections attached to the mesio-lingual and mesio-buccal surfaces of the lower first molar in healthy volunteers. Saliva (

Gemini observations of Wolf-Rayet stars in the Local Group starburst galaxy IC 10

We present Gemini-N GMOS and CFHT MOS spectroscopy of Wolf-Rayet candidates in the Local Group dwarf galaxy IC 10 that were previously identified by Massey et al. and Royer et al. From the present spectroscopic survey, the WC/WN ratio for IC 10 remains unusually high, given its low metallicity, although none of the WC9 stars suspected from narrow-band imaging are confirmed. Our spectroscopy confirms 9 newly discovered Wolf-Rayet candidates from Royer et al., whilst spectral types of 14 Wolf-Rayet stars previously observed by Massey & Armandroff are refined here. In total, there are 26 spectroscopically confirmed Wolf-Rayet stars in IC 10. All but one of the fourteen WC stars are WC4-6 stars, the exception being # 10 from Massey et al., a broad-lined, apparently single WC7 star. There are a total of eleven WN stars, which are predominantly early WN3-4 stars, but include a rare WN10 star, # 8 from Royer et al. # 5 from Massey et al. is newly identified as a transition WN/C star. Consequently, the WC/WN ratio for IC10 is 14/11similar to1.3, unusually high for a metal-poor galaxy. Re-evaluating recent photometric data of Massey & Holmes, we suggest that the true WC/WN ratio may not be as low as similar to0.3. Finally, we present ground-based finding charts for all confirmed WR stars, plus HST/WFPC2 charts for twelve cases.

VLT FORS spectra of blue supergiants in the Local Group galaxy NGC 6822

Half hour exposures using the ESO VLT/FORS1 combination at Paranal in Chile have allowed us to obtain spectra for three B supergiants in the dwarf irregular galaxy NGC 6822. The spectra have been analysed using non-LTE techniques and temperatures, gravities, helium content and abundances have been obtained. Overall the metallicity of NGC 6822 is found to lie between that of the LMC and of the SMC, in agreement with previous observations of H II regions and in contrast to the earlier findings of Massey et al. (1995). The analysis of H-alpha yields estimates of the mass-loss rates and wind momenta. These results demonstrate that significantly longer exposures with the same instruments will allow us to perform quantitative spectroscopy of blue supergiants in galaxies far beyond the Local Group.

Local DNA damage by proton microbeam irradiation induces poly(ADP-ribose) synthesis in mammalian cells

Cellular recovery from ionizing radiation (IR)-induced damage involves poly(ADP-ribose) polymerase (PARP-1 and PARP-2) activity, resulting in the induction of a signalling network responsible for the maintenance of genomic integrity. In the present work, a charged particle microbeam delivering 3.2 MeV protons from a Van de Graaff accelerator has been used to locally irradiate mammalian cells. We show the immediate response of PARPs to local irradiation, concomitant with the recruitment of ATM and Rad51 at sites of DNA damage, both proteins being involved in DNA strand break repair. We found a co-localization but no connection between two DNA damage-dependent post-translational modifications, namely poly(ADP-ribosyl)ation of nuclear proteins and phosphorylation of histone H2AX. Both of them, however, should be considered and used as bona fide immediate sensitive markers of IR damage in living cells. This technique thus provides a powerful approach aimed at understanding the interactions between the signals originating from sites of DNA damage and the subsequent activation of DNA strand break repair mechanisms.

A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.