255 research outputs found
Exposure, telomere length, and cancer risk
Telomeres are tandem repeats of TTAGGG at the end of eukaryotic chromosomes. Telomeres play a key role in chromosome stability and regulation of the cellular lifespan. Telomeres are shortened during cell division, and probably, by not yet well characterised factors in the environment. Short telomeres in peripheral blood have repeatedly been associated with increased risk of various types of cancer, as well as with cardiovascular diseases, diabetes, and lung diseases. The aim of this thesis was to explore the effect of exposures on telomere length in different occupational or environmental settings, and also to investigate the association between telomere length and chromosomal aberrations in blood, a biomarker for cancer risk. Different study populations were recruited to elucidate specific hypothesises: In the first study 157 workers in rubber industry were recruited to investigate the effect of exposure to rubber fumes on telomere length; in the second study 101 welders, 34 diesel-exposed workers and 127 controls were examined to elucidate the effect of exposure to particles on telomere length; in the third study 202 women exposed to arsenic via drinking water were analysed for effects of arsenic exposure on telomere length; and finally, in the fourth study 364 male adults were recruited to study the association between telomere length and chromosomal instability. Associations between exposures and telomere length were found: N-nitrosamines were related to shorter telomeres, whereas welding fumes and diesel exhaust showed no significant impact on telomere length. Arsenic in drinking water was related to longer telomeres and the association between arsenic and telomere length was modified by polymorphisms in the main arsenic-metabolizing gene. Although telomere length was associated with chromosome instability, no significant association was found between telomere length and cancer risk in our study, probably due to the limited number of cancer cases. We also found effects of exposure on methylation of DNA, and in turn with chromosome instability, reflecting interactions of the environment with epigenetic processes. The findings of the thesis provide evidence that some exposures, at workplaces or in the general environment, influence the average telomere length in peripheral blood. Since telomeres are key components for genomic stability and often altered during malignant transformation, it is likely that the effect of the exposures on telomeres found here reflect a mechanism of carcinogenesis for the compounds studied
Discrete element modelling of two-layered ballast in a box test
It has been recently reported that ballast comprising differently graded layers helps to reduce track settlement. The main goal of this paper is to provide micro mechanical insight about how the differently layered ballasts reduce the settlement by employing DEM and thus propose an optimum design for two-layered ballast. The DEM simulations provide sufficient evidence that the two-layered ballast works by preventing particles from moving laterally through interlocking of the particles at the interface of the different layers in a similar way to geogrid. By plotting the lateral force acting on the side boundary as a function of the distance to the base, it is found that the walls in the region of 60-180 mm above the base alway support the largest lateral forces and therefore this region might be the best location for an interface layer. However, considering the weak improvement in performance by increasing the thickness of the layer of scaled (small) ballast from 100 mm to 200 mm, it is suggested that it is best to use the sample comprising 100 mm scaled ballast on top of 200 mm standard ballast as the most cost effective solution
Discrete element method (DEM) modelling of rock flow and breakage within a cone crusher
A cone crusher is a crushing machine which is widely used in the mining, construction and recycling industries. Previous research studies have proposed empirical mathematical models to simulate the operational performance of a cone crusher. These models attempt to match the size distributions of the feed and product streams. The flow of the rock and its breakage within the cone crusher chamber are not explicitly modelled by these methods. Moreover, the ability to investigate the changes in crusher performance affected by changes to the crusher design geometry and/or operating variables (including cavity profile, closed size setting and eccentric speed) are not easily achieved. Improvements to system design and performance are normally achieved by the combination of iterative modifications made to the design and manufacture of a series of prototype machines, and from a subsequent analysis of the results obtained from expensive and time consuming rock testing programs. The discrete element method (DEM) has in recent years proved to be a powerful tool in the execution of fundamental research to investigate the behaviour of granular material flow and rock breakage. Consequently, DEM models may provide the computational means to simulate the flow and breakage of rock as it passes through a cone crusher chamber. Thus, the development of field validated models may provide a cost effective tool to predict the changes in crusher performance that may be produced by incremental changes made to the dimensions or power delivered to the crusher chamber. To obtain an improved understanding of the fundamental mechanisms that take place within a cone crusher chamber, the two processes of rock flow and rock breakage may be decoupled. Consequently, this study firstly characterised the flow behaviour of broken rock through a static crusher chamber by conducting a series of experiments to investigate the flow of regular river pebbles down an inclined chute. A parallel computational study constructed and solved a series of DEM models to replicate the results of these experimental studies. An analysis of the results of these studies concluded that an accurate model replication of the shape of the pebbles and the method used to load the pebbles into the inclined chute were important to ensure that the DEM models successfully reproduced the observed particle flow behaviour. These studies also established relationships between the chute geometry and the time taken for the loaded pebble streams to clear the chute.
To investigate the rock breakage behaviour observed within a cone crusher chamber, thirty quasi-spherical particles of Glensanda ballast aggregate were diametrically crushed in the laboratory using a Zwick crushing machine. The crushed rock particles used were of three sieve size fractions: 14-28mm, 30-37.5mm and 40-60mm. The effects that either a variation in the particle size or strength has on and the number and size distribution of the progeny rock fragments produced on breakage were studied. Subsequently, a series of DEM simulation models were constructed and solved to replicate the experimental results obtained from these crushing tests. The aggregate particles were represented by agglomerates consisting of a number of smaller diameter bonded micro-spheres. A new method was proposed to generate a dense, isotropic agglomerate with negligible initial overlap between the micro-spheres by inserting particles to fill the voids in the agglomerate. In addition, the effects that a variation in the particle packing configurations had on the simulated strength and breakage patterns experienced by the model agglomerate rock particles were investigated. The results from these DEM model studies were validated against the experimental data obtained from the ballast rock breakage tests. A comparative analysis of the experimental and modelling studies concluded that once the bond strengths between the constituent micro-spheres matched the values determined from the rock breakage tests, then the numerical models were able to replicate the measured variations in the aggregate particle strengths.
Finally, the individual validated DEM aggregate particle flow and breakage modes were combined to construct a preliminary coupled prototype DErvl model to simulate the flow and breakage of an aggregate feed through a cone crusher chamber. The author employed two modelling approaches: the population balance model (PBM) and bonded particle model (BPM) to simulate the observed particle breakage characteristics. The application of the PBM model was successfully validated against historical experimental data available in the literature. However, the potential wider use of the BPM model was deemed impractical due to the high computation time. From a comparative analysis of the particle size distributions of the feed and computed product streams by the two modelling approaches, it is concluded that the simpler PBM produces more practical computationally efficient numerical solutions
Discrete element method (DEM) modelling of rock flow and breakage within a cone crusher
A cone crusher is a crushing machine which is widely used in the mining, construction and recycling industries. Previous research studies have proposed empirical mathematical models to simulate the operational performance of a cone crusher. These models attempt to match the size distributions of the feed and product streams. The flow of the rock and its breakage within the cone crusher chamber are not explicitly modelled by these methods. Moreover, the ability to investigate the changes in crusher performance affected by changes to the crusher design geometry and/or operating variables (including cavity profile, closed size setting and eccentric speed) are not easily achieved. Improvements to system design and performance are normally achieved by the combination of iterative modifications made to the design and manufacture of a series of prototype machines, and from a subsequent analysis of the results obtained from expensive and time consuming rock testing programs. The discrete element method (DEM) has in recent years proved to be a powerful tool in the execution of fundamental research to investigate the behaviour of granular material flow and rock breakage. Consequently, DEM models may provide the computational means to simulate the flow and breakage of rock as it passes through a cone crusher chamber. Thus, the development of field validated models may provide a cost effective tool to predict the changes in crusher performance that may be produced by incremental changes made to the dimensions or power delivered to the crusher chamber. To obtain an improved understanding of the fundamental mechanisms that take place within a cone crusher chamber, the two processes of rock flow and rock breakage may be decoupled. Consequently, this study firstly characterised the flow behaviour of broken rock through a static crusher chamber by conducting a series of experiments to investigate the flow of regular river pebbles down an inclined chute. A parallel computational study constructed and solved a series of DEM models to replicate the results of these experimental studies. An analysis of the results of these studies concluded that an accurate model replication of the shape of the pebbles and the method used to load the pebbles into the inclined chute were important to ensure that the DEM models successfully reproduced the observed particle flow behaviour. These studies also established relationships between the chute geometry and the time taken for the loaded pebble streams to clear the chute.
To investigate the rock breakage behaviour observed within a cone crusher chamber, thirty quasi-spherical particles of Glensanda ballast aggregate were diametrically crushed in the laboratory using a Zwick crushing machine. The crushed rock particles used were of three sieve size fractions: 14-28mm, 30-37.5mm and 40-60mm. The effects that either a variation in the particle size or strength has on and the number and size distribution of the progeny rock fragments produced on breakage were studied. Subsequently, a series of DEM simulation models were constructed and solved to replicate the experimental results obtained from these crushing tests. The aggregate particles were represented by agglomerates consisting of a number of smaller diameter bonded micro-spheres. A new method was proposed to generate a dense, isotropic agglomerate with negligible initial overlap between the micro-spheres by inserting particles to fill the voids in the agglomerate. In addition, the effects that a variation in the particle packing configurations had on the simulated strength and breakage patterns experienced by the model agglomerate rock particles were investigated. The results from these DEM model studies were validated against the experimental data obtained from the ballast rock breakage tests. A comparative analysis of the experimental and modelling studies concluded that once the bond strengths between the constituent micro-spheres matched the values determined from the rock breakage tests, then the numerical models were able to replicate the measured variations in the aggregate particle strengths.
Finally, the individual validated DEM aggregate particle flow and breakage modes were combined to construct a preliminary coupled prototype DErvl model to simulate the flow and breakage of an aggregate feed through a cone crusher chamber. The author employed two modelling approaches: the population balance model (PBM) and bonded particle model (BPM) to simulate the observed particle breakage characteristics. The application of the PBM model was successfully validated against historical experimental data available in the literature. However, the potential wider use of the BPM model was deemed impractical due to the high computation time. From a comparative analysis of the particle size distributions of the feed and computed product streams by the two modelling approaches, it is concluded that the simpler PBM produces more practical computationally efficient numerical solutions
Boundary detection of optic disk by a modiÿed ASM method
Abstract A new algorithm to automatically detect the boundary of optic disk in color fundus images is proposed. The optic disk is located by principal component analysis (PCA) based model, which is employed to initialize active shape model (ASM) to detect the disk boundary. ASM is modiÿed with two aspects: one is the self-adjusting weight in the transformation from shape space to image space; the other is exclusion of outlying points in obtaining shape parameters. The modiÿcations make the proposed algorithm more robust and converge faster than the original ASM method, especially in the case where the edge of optic disk is weak or occluded by blood vessels.
Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models
This paper aims to show that the inference logic of a deep model can be
faithfully approximated as a sparse, symbolic causal graph. Such a causal graph
potentially bridges the gap between connectionism and symbolism. To this end,
the faithfulness of the causal graph is theoretically guaranteed, because we
show that the causal graph can well mimic the model's output on an exponential
number of different masked samples. Besides, such a causal graph can be further
simplified and re-written as an And-Or graph (AOG), which explains the logical
relationship between interactive concepts encoded by the deep model, without
losing much explanation accuracy
ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction
Most advanced unsupervised anomaly detection (UAD) methods rely on modeling
feature representations of frozen encoder networks pre-trained on large-scale
datasets, e.g. ImageNet. However, the features extracted from the encoders that
are borrowed from natural image domains coincide little with the features
required in the target UAD domain, such as industrial inspection and medical
imaging. In this paper, we propose a novel epistemic UAD method, namely
ReContrast, which optimizes the entire network to reduce biases towards the
pre-trained image domain and orients the network in the target domain. We start
with a feature reconstruction approach that detects anomalies from errors.
Essentially, the elements of contrastive learning are elegantly embedded in
feature reconstruction to prevent the network from training instability,
pattern collapse, and identical shortcut, while simultaneously optimizing both
the encoder and decoder on the target domain. To demonstrate our transfer
ability on various image domains, we conduct extensive experiments across two
popular industrial defect detection benchmarks and three medical image UAD
tasks, which shows our superiority over current state-of-the-art methods.Comment: NeurIPS 2023 Poste
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