An impinger-based sampling method was designed and evaluated for the collection of airborne cellulose nanocrystals (CNC). Plastic impingers were purchased and a custom nozzle was designed and 3D printed. Collection efficiency by particle size was compared to commercially available impingers. Collection efficiency (CE) was then adjusted theoretically for an impactor that would be used in a field setting to remove particles larger than 300 nm. Adjusted CE was compared to the nanoparticulate matter (NPM) criterion model, which mimics nanoparticle deposition in the human respiratory system. The impinger method was then used to collect rhodamine-tagged CNC to determine if it could collect a concentration of CNC that agreed with the known aerosolized concentration when analyzed with spectroscopy/spectrophotometry. The plastic impinger method had a greater collection efficiency for relevant particle sizes than the commercially available impingers tested. After adjusting for the impactor, the impinger method agreed with the NPM curve for particles ranging from 45-600 nm (R2=0.94). Concentrations of rhodamine-tagged CNC collected with the impinger method did not agree with the concentrations measured by the reference instrument, however this was likely due to issues with the batch of CNC used. The impinger method can be used to collect other nanoparticles, but analysis methods that do not rely on using tagged CNC must be developed to mate the preferred analysis method with sampling.

Characterizing airborne influenza virus exposure is important for infection prevention and exposure control in health care and public settings. Detecting airborne influenza virus is important in assessing infection risk. The virus must also be protected from deterioration during aerosol sampling and long term storage. RNA preservation buffers (RNAPBs) may stabilize influenza virus after sampling and during storage. Bioaerosol samplers are used to collect airborne influenza virus, and many different types of samplers are available. The objectives of this experiment were to: 1) compare influenza virus concentrations across bioaerosol samplers; 2) compare the efficacy of RNAPB over Hanks Balanced Salt Solution (HBSS) as a sample collection media; and 3) determine whether RNAPB stabilizes viral particles stored over time. In this experiment we aerosolized active influenza virus (H1N1) in a bioaerosol chamber and compared sampling efficiencies using two different samplers: the SKC Biosampler and NIOSH Biosampler, and two different medias: Hanks Balanced Salt Solution (HBSS) and an RNAPB. Ten 15-minute experimental trials were completed. We also compared HBSS and RNAPB in terms of the maintenance of virus RNA integrity during storage at room temperatures. Samples were stored at room temperature for 1, 4, 7, and 14 days. Virus concentrations were measured and compared at each time point. Significant differences were found between sampler and media type - the SKC Biosampler collected a higher concentration of virus than the NIOSH Biosampler, and HBSS collected a higher concentration of virus than RNAPB. In storage at room temperature conditions, RNAPB maintained virus in concentrations significantly greater than in HBSS. The results of this experiment indicates that the SKC Biosampler should be used to characterize airborne influenza and that RNAPB should not be used as a sampling media but can be used to preserve samples if needed.

Electrostatic Dust Collectors (EDCs) are a passive sampling method that has not yet been fully validated. Our first study investigated the effect of EDC mailing and EDC deployment in front of and away from heated ventilation on endotoxin concentrations. Endotoxin sampling efficiency of heated and unheated EDC cloths was evaluated. EDCs express mailed cross-country yielded no significant changes in endotoxin concentrations when dust-only samples were compared to high quality control (QC) spiked-EDCs (p=0.21) and low QC spiked-EDCs (p=0.16). EDCs were deployed in 20 apartments with one EDC placed in front of the univent heater and another EDC placed on a built-in bookshelf. Endotoxin concentrations were significantly different (p=0.049) indicating that EDC placement impacts endotoxin sampling. Heated and unheated EDCs were deployed for 7 days in farm homes. There was a significant difference between endotoxin concentrations (p=0.027). The electrostatic charge of 12 heated and 12 unheated EDC cloths were significantly different (p=0.009). These studies suggest that heating cloths may diminish their electrostatic charge and endotoxin sampling capabilities. The EDC sampling time needed to achieve detectable and reproducible loading for bioaerosols has not been systematically evaluated. In our second study, EDCs were deployed in 15 Iowa farm homes for 7-, 14-, and 28-day sampling periods to determine if endotoxin and allergens could be quantified and if loading rates were uniform (i.e. doubling from 7 to 14 days and 14 to 28 days and quadrupling from 7 to 28 days). Loadings between left and right paired EDC cloths were not significantly different and were highly correlated for endotoxin, total protein, and cat (Fel d1), dog (Can f1) and mouse (Mus m1) allergens (p<0.001). EDC endotoxin sampling had close agreement between paired samples (Pearson p=0.96, p<0.001). EDC endotoxin loading doubled from 7 to 14-day deployments but the loading rate decreased from 14 to 28 days of sampling with only a 1.38 fold increase. Allergen exposure assessment using EDCs was less satisfactory. Paired EDCs and daily Button aerosol samplers (BS) were used in our third study to concurrently sample endotoxin in 10 farm homes during 7 day periods in summer and winter. Winter sampling included an optical particle counter (OPC) for particulate size and number concentration data. OPC particulate matter (PM) data were divided into PM2.5 and PM10-2.5. Summer sampling yielded geometric mean and geometric standard deviation values of 0.82 EU/m3 (2.7) for inhalable aerosol BS and 737 EU/m2 (1.9) for EDCs. Winter values were 0.52 EU/m3 (3.1) for BS and 538 EU/m2 (3.0) for EDCs. Seven day endotoxin values of EDCs were significantly and highly correlated with the 7-day BS sampling averages (p=0.70; p<0.001). An Analysis of Variance indicated a 2.37-fold increase in EDC endotoxin concentrations for each unit increase of the ratio of PM2.5 to PM10-2.5. A 10-fold increase in BS endotoxin concentrations was associated with a 12.2-fold increase in EDC endotoxin concentrations. Our fourth study established QC protocols use of EDCs in large field studies. QCs were developed for endotoxin, peptidoglycan, and glucan for analysis alongside the Agricultural Lung Health study EDC samples. The coefficient of variation percentage (CV) for each QC was used to determine variability. For each QC, 20 EDC cloths were analyzed to establish an acceptable range (mean ± 3 standard deviations). Two QCs were established for endotoxin analysis. The high QCs were dust-spiked EDCs with a CV of 29.7%. The low QCs were spiked with E. coli standard and had a CV of 15.6%. One QC was established for peptidoglycan analysis using dust-spiked EDC extracts. Two glucan QCs were established using dust-spiked EDCs with a high CV (51.7%) and yeast-spiked EDCs with a CV of 26.0%. Endotoxin and glucan concentrations of AGLH EDC samples were found to be significantly correlated (p=0.71; p<0.0001). In conclusion, EDCs are an effective passive sampling method for endotoxin exposure assessment in farm homes.

This thesis presents a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher order temporal correlations due to feedback. Switching activity, one of the key components in dynamic power dissipation, is dependent on input streams and exhibits spatio-temporal correlation amongst the signals. One can handle dependency modeling of switching activity in a combinational circuit by Bayesian Networks [2] that encapsulates the underlying joint probability distribution function exactly. We present the underlying switching model of a sequential circuit as the time coupled logic induced directed acyclic graph (TC-LiDAG), that can be constructed from the logic structure and prove it to be a dynamic Bayesian Network. Dynamic Bayesian Networks over n time slices are also minimal representation of the dependency model where nodes denote the random variable and edges either denote direct dependency between variables at one time instant or denote dependencies between the random variables at different time instants. Dynamic Bayesian Networks are extremely powerful in modeling higher order temporal as well as spatial correlations; it is an exact model for the underlying conditional independencies. The attractive feature of this graphical representation of the joint probability function is that not only does it make the dependency relationships amongst the nodes explicit but it also serves as a computational mechanism for probabilistic inference. We use stochastic inference engines for dynamic Bayesian Networks which provides any-time estimates and scales well with respect to size We observe that less than a thousand samples usually converge to the correct estimates and that three time slices are sufficient for the ISCAS benchmark circuits. The average errors in switching probability of 0.006, with errors tightly distributed around the mean error values, on ISCAS'89 benchmark circuits involving up to 10000 signals are reported.

Power optimization is a crucial issue at all levels of abstractions in VLSI Design. Power estimation has to be performed repeatedly to explore the design space throughout the design process at all levels. Dynamic Power Dissipation due to Switching Activity has been one of the major concerns in Power Estimation. While many Simulation and Statistical Simulation based methods exist to estimate Switching Activity, these methods are input pattern sensitive, hence would require a large input vector set to accurately estimate Power. Probabilistic estimation of switching activity under Zero-Delay conditions, seriously undermines the accuracy of the estimation process, since it fails to account for the spurious transitions due to difference in input signal arrival times. In this work, we propose a comprehensive probabilistic switching model that characterizes the circuit's underlying switching profile, an essential component for estimating data-dependent dynamic and static power. Probabilistic estimation of Switching under Real Delay conditions has been a traditionally difficult problem, since it involves modeling the higher order temporal, spatio-temporal and spatial dependencies in the circuit. In this work we have proposed a switching model under Real Delay conditions, using Bayesian Networks. This model accurately captures the spurious transitions, due to different signal input arrival times, by explicitly modeling the higher order temporal, spatio-temporal and spatial dependencies. The proposed model, using Bayesian Networks, also serves as a knowledge base, from which information such as cross-talk noise due to simulataneous switching at input nodes can be inferred.

Doctor of Philosophy(PhD), / Airborne fungi are ubiquitous in the environment and human exposure is inevitable. Such fungi differ greatly in their taxonomic, physical, ecological and pathogenic characteristics. Currently, 69 000 species have been taxonomically classified and more than 80 of these are recognised to be aeroallergen sources. Many strategies have evolved to sample, identify and interpret fungal exposure to these species, however no strategy serves all purposes as exposure is a complex and dynamic process confounded by spatial, temporal and geographic variations in airborne counts, in addition to the inadequacies of the immunodiagnostic techniques available. To date, the interpretation of personal exposure and sensitisation to fungal allergens has been restricted to a few select species and the contribution of other genera, airborne hyphae and fragmented conidia to allergic disease are all poorly understood. The aim of the thesis was to utilize the Halogen Immunoassay (HIA) to diagnose fungal allergic sensitisation, to investigate the distribution and factors influencing allergens of fungi in the air and to understand what is actually inhaled in exposure settings. The novelty of the HIA derives from its unique ability to provide allergen sources that are actively secreted by the collected fungal spores and hyphae, which are bound to protein binding membranes (PBM) and then immunoprobed. In Chapter 2, the HIA was compared to the commercial in vitro Pharmacia UniCap assay (CAP) and the in vivo skin prick test (SPT), using 30 sera from subjects SPT positive to Aspergillus fumigatus and/or Alternaria alternata and 30 who were SPT negative to these fungi but sensitised to non-fungal allergens. Sera were analysed by CAP and the HIA against A. alternata, A. fumigatus, Cladosporium herbarum and Epicoccum purpurascens and compared statistically. Between 3% and 7% of SPT negative sera were identified to have specific IgE towards A. fumigatus and A. iv alternata, respectively. For the SPT positive sera, significant associations were found between the HIA and CAP scores for all fungal species tested (P<0.0001). Correlations between the HIA and SPT however, were weakly correlated for A. alternata (rs = 0.44, P<0.05) but not for A. fumigatus. In Chapter 3, personal exposure to indoor fungal aerosols was examined using the HIA to identify the fungal components that people were allergic to. Personal air sampling pumps (PASs) collected airborne fungal propagules onto PBMs for 2.5 hours indoors (n=21). Collected fungi were incubated overnight in a humid chamber to promote the germination of conidia. The membranes were then immunostained with pooled human Alternaria species-positive sera. All air samples contained fungal hyphae that expressed soluble allergens and were significantly higher in concentration than counts of conidia of individual well-characterised allergenic genera. Approximately 25% of all hyphae expressed detectable allergen compared to non-stained hyphae (P<0.05) and the resultant localisation of immunostaining was heterogeneous among hyphae. Fungal conidia of ten genera that were previously uncharacterised as allergen sources accounted for 8% of the total conidia that demonstrated IgE binding. In Chapter 4, the number and identity of fungi inhaled by 34 adults in an outdoor community setting was measured over 2 hour periods by people wearing Intra-nasal air samplers (INASs) and compared to fungal counts made with a Burkard spore trap and filter air samplers worn on the lapel. Using INAS, the most prevalent fungi inhaled belonged to soil borne spores of Alternaria, Arthrinium, Bipolaris, Cladosporium, Curvularia, Epicoccum, Exserohilum, Fusarium, Pithomyces, Spegazzinia, Tetraploa and Xylariaceae species, in addition to hyphal fragments. These results showed that inhaled exposure in most people varied in a 2-fold range with 10-fold outliers. In addition, the INAS and personal air filters agreed more with each other than with Burkard spore trap counts. The analysis was further confounded by different sampling efficiencies, locations of devices and ability to visualise and count fungal propagules. In Chapter 5, a double immunostaining technique based on the HIA was developed and applied to the conidia, hyphae and fungal fragments of A. alternata, A. fumigatus and Penicillium chrysogenum to discriminate between sources of allergens, v using IgE and to identify the fungi, using a fungal-specific antibody. The localisation of immunostaining was heterogeneous between both conidia and the state of germination with greater concentrations of double immunostaining detected following germination for each fungal species (P<0.0001). Fragmented A. alternata hyphae and morphologically indiscernible fragments could be identified for the first time using this technique. In Chapter 6, the factors affecting the release of allergen from the spores of eleven different species were studied. For nine of eleven species, between 5.7% and 92% of spores released allergen before germination. Ungerminated spores of P. chrysogenum and Trichoderma viride did not release detectable allergen. After germination, all spores that germinated eluted allergen from their hyphae. Upon germination there was a significant increase in the percentage of spores eluting detectable allergen (P<0.0001) and the localisation of allergen along the hyphae varied between species. Increased elution of allergen post germination might be a common feature of many species of allergenic fungi following inhalation. Additionally, Chapter 6 explored the extent to which inhaled spores or hyphae germinate after deposition in the nasal cavity and thus cause exposure to allergens. Twenty subjects had their noses lavaged at three separate intervals, (1) at the beginning of the experiment, (2) after one hour indoors and (3) after one hour outdoors. The recovery of spores and hyphal fragments from the nasal cavity varied between individuals and was significantly greater after outdoor exposures. Germinated fungal spores were recovered often in high concentrations for Aspergillus-Penicillium species, however the proportion between ungerminated and germinated spores were much lower for other genera recovered. Conclusions: Our analysis of cultured and wild-type fungi presents a new paradigm of natural fungal exposure, which in addition to commonly recognized species, implicates airborne hyphae, fragmented conidia and the conidia of a much more diverse range of genera as airborne allergens. Exposure is heterogeneous between individuals in the same geographic locality and the spectrum of fungal genera inhaled differs with the method of analysis. Many of the spores inhaled are likely to be allergenic, however upon germination there is an increased elution of allergen and this might be a common vi feature of many fungal species following inhalation. This project also provides novel techniques to diagnose fungal allergy by immunostaining wild-type fungi to which a patient is exposed with the patient’s own serum. Such an immunoassay combines environmental with serological monitoring on a patient specific basis and potentially avoids many problems associated with extract variability, based on the performance of current diagnostic techniques for fungal allergy.

This thesis is about the dynamics of eastern grey kangaroo (Macropus giganteus) populations and their food supplies in temperate grasslands of south-eastern Australia. It is based on the study of three populations of eastern grey kangaroos inhabiting �warm dry�, �cold dry�, and �warm wet� sites within the Southern Tablelands climatic region. After a pilot survey and methods trial in early 2001, the main period of study was from August 2001 to July 2003. The study populations were found to have the highest densities of any kangaroo populations, 450 to 510 km-2. Their density was the same at the end of the two year study period as at the beginning, in spite of a strong decline in herbage availability due to drought. The eastern grey kangaroo populations were limited according to the predation-sensitive food hypothesis. Fecundity, as the observed proportion of females with late pouch young in spring, was high, in spite of the high kangaroo density and restricted food availability. Age-specific fecundity of a kangaroo sample shot on one of the sites in 1997 to avert starvation was the highest reported for kangaroos. Thus, limitation acted through mortality rather than fecundity. Population growth rate was most sensitive to adult survival but the demographic rate that had the greatest effect in practice was mortality of juveniles, most likely sub-adults. The combination of high fecundity with high mortality of immatures would provide resilience to low levels of imposed mortality and to fertility control. The normal pattern of spring pasture growth was not observed in the drought conditions and few of the recorded increments of growth were of the magnitude considered typical for sites on the southern and central tablelands. Temperature was necessary to predict pasture growth, as well as rainfall, over the previous two months. The best model of pasture growth (lowest AICc) included negative terms for herbage mass, rainfall over the previous two months, and temperature, and a positive term for the interaction between rainfall and temperature. It accounted for 13% more of the variation in the data than did the simpler model of the type used by Robertson (1987a), Caughley (1987) and Choquenot et al. (1998). However this was only 63% of total variation. Re-evaluation of the model based on measurements of pasture growth in more typical (non-drought) conditions is recommended. Grazing had a powerful influence on the biomass of pasture due to the high density of kangaroos. This is a marked difference to many other studies of the type which have been conducted in semi-arid environments where rainfall dominates. The offtake of pasture by kangaroos, as estimated on the research sites by the cage method, was linear on herbage mass. It was of greater magnitude than the more exact estimate of the (curved) functional response from grazedowns in high�quality and low�quality pastures. The widespread recognition of three forms of functional response is inadequate. Both the theoretical basis, and supporting data, have been published for domed, inaccessible residue, and power forms as well (Holling 1966; Noy-Meir 1975; Hassell et al. 1976, 1977; Short 1986; Sabelis 1992). Eastern grey kangaroos had approximately the same Type 2 functional response when consuming either a high quality artificial pasture (Phalaris aquatica), or dry native pasture (Themeda australis) in autumn. Their functional response rose more gradually than those published for red kangaroos and western grey kangaroos in the semi-arid rangelands, and did not satiate at the levels of pasture available. This gradual behaviour of the functional response contributes to continuous stability of the consumer-resource system, as opposed to discontinuous stability. The numerical response was estimated using the ratio equation, assuming an intrinsic rate of increase for eastern grey kangaroos in temperate grasslands of 0.55. There is indirect evidence of effects of predation in the dynamics of the kangaroo populations. This is demonstrated by the positive relationship between r and kangaroo density. Such a relationship can be generated by predation. A desirable future task is to compile estimates of population growth rate and simultaneous estimates of pasture, in the absence of predation, where kangaroo population density is changing, so that the numerical response can be estimated empirically. The management implications arising from this study are numerous and a full account would require a separate report. As one example, kangaroos in these temperate grasslands are on average smaller, eat less, are more numerous, and are more fecund, than would be predicted from other studies (e.g. Caughley et al. 1987). Thus the benefit of shooting each kangaroo, in terms of grass production, is less, or, in other words, more kangaroos have to be shot to achieve a certain level of impact reduction, and the population will recover more quickly, than would have been predicted prior to this study. Secondly, of much importance to managers, the interactive model which can readily be assembled from the products of Chapters 4, 5 and 8, can be used to test a range of management options, and the effect of variation in weather conditions, such as increased or decreased rainfall. For example, the model indicates that commercial harvesting (currently under trial in the region), at the maximum level allowed, results in a sustainable harvest of kangaroos, but does not increase the herbage mass, and only slightly reduces the frequency of crashes when herbage mass falls to low levels. (To demonstrate this with an ecological experiment would require an extremely large investment of research effort.) However, an alternative �national park damage mitigation� formula, which holds kangaroo density to about 1 ha-1, is predicted to increase herbage mass considerably and to reduce the frequency of crashes in herbage mass, but these effects would be achieved at the cost of having to shoot large numbers of kangaroos. Thus, aside from many specific details of kangaroo ecology, the knowledge gained in this study appears to have useful potential to illustrate to managers the dynamic properties of a resource-consumer system, the probabilistic nature of management outcomes, and the consequences of particular kangaroo management proposals.

Public view removed at the authors request. 16/07/2006 / The daily experience of anorexia nervosa sufferers has not previously been studied and yet it is fundamental to understanding anorexia nervosa. This study examined and compared the daily experiences of anorexia nervosa patients and control participants in terms of sense of self, mood states and flow states. Flow is characterised by undivided concentration and interest in an activity for intrinsic benefits. Flow is not always desirable, as some ways of experiencing it may be harmful to the individual and society. Anorexia nervosa participants were recruited from hospitals and private practices of clinicians specialising in the treatment of anorexia nervosa. Exclusion criteria included male gender, chronic anorexia nervosa, drug abuse, and current participation in an inpatient program. Anorexia nervosa participants completed a series of questionnaires at baseline, 3-6 month follow-up and 7-12 month follow-up (stage one, two and three respectively). The questionnaires were designed to measure the severity of their eating disorder. Anorexia nervosa and control group participants completed Experience Sampling Forms (ESF) and a Repertory Grid at baseline and 3-6 months. The ESFs were completed each time a pager was activated. The pager was activated seven times a day, for four days at random times between 8.00am and 10.00pm. The pager signals were a minimum of two hours apart. The Repertory Grid consisted of 23 constructs and 13 elements provided to the participant. Thirty-one anorexia nervosa sufferers and thirty-two control participants completed stage one and eighteen anorexia nervosa sufferers and twenty-seven control group participants completed stage two of the study. Eighteen anorexia nervosa sufferers completed stage three of the study. Control participants were not required to participate in stage three. There was no difference in the severity of anorexia nervosa between completers and drop-outs The analysis of the ESFs at stage one indicated that the anorexia nervosa group participants did not spend more time alone at home or more time alone in any situation than the control group. For both groups, being alone had a negative influence on mood state, but had no effect on sense of self. The anorexia nervosa group felt lonelier and less sociable than the control group. The mood state and sense of self for the anorexia nervosa group was significantly lower over all the ESFs when compared to the control group. They were also more self-critical, experienced higher levels of guilt, were less able to live up to their own expectations, and were less satisfied with their performance in the activity they were doing. The anorexia nervosa group experienced less flow states than the control group at stage one. There was an improvement in mood state, sense of self and self-criticism for the anorexia nervosa group when they were in a flow state compared to when they were not in a flow state. There was an improvement in mood state, sense of self, guilt and self-criticism for the control group when they experienced flow, however these differences were not significant. The anorexia nervosa group had a more positive mood state and sense of self at stage two when compared to stage one. Correspondingly, there was a trend towards a reduced severity of the disorder indicated by a significant improvement on some of the psychological tests (EAT, REDS, BDI, DT). There was also a significant improvement in BMI. However, there was a significant decline in the amount of flow of anorexia nervosa participants experienced at stage two when compared to stage one. This result may be attributed to the significant decline in the response rate on ESFs in the second stage of the study for both the anorexia nervosa and control groups. Anorexia nervosa non-responders at stage two reported more severe symptoms of anorexia nervosa than anorexia nervosa responders, although this was a trend and reached significance only on minor indicators of eating disorder severity. The identification of a factor that predicted severity over a six-month period was not possible. The repertory grid analysis showed that the construct system of the anorexia nervosa participants was tighter and less complex than that of the control group. The anorexia nervosa group construed themselves as dissimilar from the way they would like to be in any context. The control group construed themselves as similar to the way they would like to be when they were alone, but as dissimilar from the way they would like to be when they were with other people. While the most salient element for both the anorexia nervosa and control groups was 'alone at home', it appears that the controls use this time for goal-directed activities. In contrast, this time was dominated by fear of losing control for the anorexia nervosa group. Although there was a trend towards a decrease in the amount of variance accounted for by the first component for the anorexia nervosa group at stage two compared to stage one, the interpretation of this result was complicated by mixed result of the control group. The anorexia nervosa groups' daily experience of life was bleak when compared to the daily experience of the control group, except for periods when the anorexia nervosa participants experienced a flow state. DeVries (1992) has documented the success of therapeutic interventions that involve the identification and replication of activities that resulted in a flow state. This investigation suggests that a similar result may be possible in the treatment of anorexia nervosa.

Graduation date: 2000

This thesis is on quantum algorithms. It has three main themes: (1) quantum walk based search algorithms, (2) quantum rejection sampling, and (3) the Boolean function hidden shift problem. The first two parts deal with generic techniques for constructing quantum algorithms, and the last part is on quantum algorithms for a specific algebraic problem. In the first part of this thesis we show how certain types of random walk search algorithms can be transformed into quantum algorithms that search quadratically faster. More formally, given a random walk on a graph with an unknown set of marked vertices, we construct a quantum walk that finds a marked vertex in a number of steps that is quadratically smaller than the hitting time of the random walk. The main idea of our approach is to interpolate the random walk from one that does not stop when a marked vertex is found to one that stops. The quantum equivalent of this procedure drives the initial superposition over all vertices to a superposition over marked vertices. We present an adiabatic as well as a circuit version of our algorithm, and apply it to the spatial search problem on the 2D grid. In the second part we study a quantum version of the problem of resampling one probability distribution to another. More formally, given query access to a black box that produces a coherent superposition of unknown quantum states with given amplitudes, the problem is to prepare a coherent superposition of the same states with different specified amplitudes. Our main result is a tight characterization of the number of queries needed for this transformation. By utilizing the symmetries of the problem, we prove a lower bound using a hybrid argument and semidefinite programming. For the matching upper bound we construct a quantum algorithm that generalizes the rejection sampling method first formalized by von~Neumann in~1951. We describe quantum algorithms for the linear equations problem and quantum Metropolis sampling as applications of quantum rejection sampling. In the third part we consider a hidden shift problem for Boolean functions: given oracle access to f(x+s), where f(x) is a known Boolean function, determine the hidden shift s. We construct quantum algorithms for this problem using the "pretty good measurement" and quantum rejection sampling. Both algorithms use the Fourier transform and their complexity can be expressed in terms of the Fourier spectrum of f (in particular, in the second case it relates to "water-filling" of the spectrum). We also construct algorithms for variations of this problem where the task is to verify a given shift or extract only a single bit of information about it.