A portable load cell for in-situ ore impact breakage testing

This paper discusses the design and characterisation of a short, and hence portable impact load cell for in-situ quantification of ore breakage properties under impact loading conditions. Much literature has been published in the past two decades about impact load cells for ore breakage testing. It has been conclusively shown that such machines yield significant quantitative energy-fragmentation information about industrial ores. However, documented load cells are all laboratory systems that are not adapted for in-situ testing due to their dimensions and operating requirements. The authors report on a new portable impact load cell designed specifically for in-situ testing. The load cell is 1.5 m in height and weighs 30 kg. Its physical and operating characteristics are detailed in the paper. This includes physical dimensions, calibration and signal deconvolution. Emphasis is placed on the deconvolution issue, which is significant for such a short load cell. Finally, it is conclusively shown that the short load cell is quantitatively as accurate as its larger laboratory analogues. (C) 2062 Elsevier Science B.V. All rights reserved.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

Cyclosporin monitoring in Australasia: 2002 update of consensus guidelines

Therapeutic drug monitoring of cyclosporin (CsA) has been established as part of the routine clinical treatment of patients following organ transplantation for more than 20 years, and based on contemporary knowledge, many consensus guidelines have been published to assist clinics and laboratories attain optimal strategies for patient care. This article addresses the newer directions in CsA monitoring, with particular reference to the Australasian situation that has evolved since the 1993 Australasian guideline (1). These changes have included the introduction of alternative assay methodologies, changed CsA formulation from Sandimmun to Neoral throughout Australasia, and alternatives to trough concentration (C0) monitoring, especially 2-hour concentration (C2) monitoring and associated validated dilution protocols to accurately quantitate the higher whole blood CsA concentrations. The revision was prepared following a recent survey of all Australasian CsA-monitoring laboratories (2) where discordant practices were evident.

Monitoring and isolation of blood dendritic cells from apheresis products in healthy individuals: a platform for cancer immunotherapy

The fundamental role of dendritic cells (DC in initiating and directing the primary immune response is well established. Furthermore, it is now accepted that DC may be useful in new vaccination strategies for preventing certain malignant and infectious diseases. As blood DC (BDC physiology differs from that of the DC homologues generated in vitro from monocyte precursors, it is becoming more relevant to consider BDC for therapeutic interventions. Until recently, protocols for the isolation of BDC were laborious and inefficient; therefore, their use for investigative cancer immunotherapy is not widespread. In this study, we carefully documented BDC counts, yields and subsets during apheresis (Cobe Spectra), the initial and essential procedure in creating a BDC isolation platform for cancer immunotherapy. We established that an automated software package (Version 6,0 AutoPBPC) provides an operator-independent reliable source of motionuclear cells (MNC for BDC preparation. Further, we observed that BDC might be recovered in high yields, often greater than 100% relative to the number of circulating BDC predicted by blood volume. An average of 66 million (range, 17-179) BDC per 10-1 procedure were obtained, largely satisfying the needs for immunization. Higher yields were possible on total processed blood volumes of 151. BDC were not activated by the isolation procedure and, more importantly, both BDC subsets (CD11c(+)CD123(low) and CD11c(-)CD123(high)) were equally represented. Finally, we established that the apheresis product could be used for antibody-based BDC immunoselection and demonstrated that fully functional BDC can be obtained by this procedure. (C) 2002 Published by Elsevier Science B.V.

Simulation of the load-unload response ratio and critical sensitivity in the lattice solid model

The Load-Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It involves calculating the ratio of a specified energy release measure during loading and unloading where loading and unloading periods are determined from the earth tide induced perturbations in the Coulomb Failure Stress on optimally oriented faults. In the lead-up to large earthquakes, high LURR values are frequently observed a few months or years prior to the event. These signals may have a similar origin to the observed accelerating seismic moment release (AMR) prior to many large earthquakes or may be due to critical sensitivity of the crust when a large earthquake is imminent. As a first step towards studying the underlying physical mechanism for the LURR observations, numerical studies are conducted using the particle based lattice solid model (LSM) to determine whether LURR observations can be reproduced. The model is initialized as a heterogeneous 2-D block made up of random-sized particles bonded by elastic-brittle links. The system is subjected to uniaxial compression from rigid driving plates on the upper and lower edges of the model. Experiments are conducted using both strain and stress control to load the plates. A sinusoidal stress perturbation is added to the gradual compressional loading to simulate loading and unloading cycles and LURR is calculated. The results reproduce signals similar to those observed in earthquake prediction practice with a high LURR value followed by a sudden drop prior to macroscopic failure of the sample. The results suggest that LURR provides a good predictor for catastrophic failure in elastic-brittle systems and motivate further research to study the underlying physical mechanisms and statistical properties of high LURR values. The results provide encouragement for earthquake prediction research and the use of advanced simulation models to probe the physics of earthquakes.

Load-unload response ratio and accelerating moment/energy release critical region scaling and earthquake prediction

The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.

Promiscuous CTL recognition of viral epitopes on multiple human leukocyte antigens: Biological validation of the proposed HLA A24 supertype

Multiple HLA class I alleles can bind peptides with common sequence motifs due to structural similarities in the peptide binding cleft, and these groups of alleles have been classified into supertypes. Nine major HLA supertypes have been proposed, including an A24 supertype that includes A*2301, A*2402, and A*3001. Evidence for this A24 supertype is limited to HLA sequence homology and/or similarity in peptide binding motifs for the alleles. To investigate the immunological relevance of this proposed supertype, we have examined two viral epitopes (from EBV and CMV) initially defined as HLA-A*2301-binding peptides. The data clearly demonstrate that each peptide could be recognized by CTL clones in the context of A*2301 or A*2402; thus validating the inclusion of these three alleles within an A24 supertype. Furthermore, CTL responses to the EBV epitope were detectable in both A*2301(+) and A*2402(+) individuals who had been previously exposed to this virus. These data substantiate the biological relevance of the A24 supertype, and the identification of viral epitopes with the capacity to bind promiscuously across this supertype could aid efforts to develop CTL-based vaccines or immunotherapy. The degeneracy in HLA restriction displayed by some T cells in this study also suggests that the dogma of self-MHC restriction needs some refinement to accommodate foreign peptide recognition in the context of multiple supertype alleles.

Proteasomal targeting of a viral oncogene abrogates oncogenic phenotype and enhances immunogenicity

The ability of viral or mutated cellular oncogenes to initiate neoplastic events and their poor immunogenicity have considerably undermined their potential use as immunotherapeutic tools for the treatment of human cancers. Using an EpsteinBarr virus-encoded oncogene, latent membrane protein 1 (LMP1), as a model, we report a novel strategy that both deactivates cellular signaling pathways associated with the oncogenic phenotype and reverses poor immunogenicity. We show that cotranslational ubiquitination combined with Wend rule targeting of LMP1 enhanced the intracellular degradation of LMP1 and total blockade of LMP1-mediated nuclear factor-kappaB (NF-kappaB) and signal transducer and activator of transcription (STAT) activation in human cells. In addition, although murine cells expressing LMP1 were uniformly tumorigenic, this oncogenicity was completely abrogated by covalent linkage of LMP1 with ubiquitin, while an enhanced CD8(+) T cell response to a model epitope fused to the C-terminus of LMP1 was observed following immunization with ubiquitinated LMP1. These observations suggest that proteasomal targeting of tumor-associated oncogenes could be exploited therapeutically by either gene therapy or vaccination.