Resource allocation analysis of the stochastic diffusion search

The Stochastic Diffusion Search (SDS) was developed as a solution to the best-fit search problem. Thus, as a special case it is capable of solving the transform invariant pattern recognition problem. SDS is efficient and, although inherently probabilistic, produces very reliable solutions in widely ranging search conditions. However, to date a systematic formal investigation of its properties has not been carried out. This thesis addresses this problem. The thesis reports results pertaining to the global convergence of SDS as well as characterising its time complexity. However, the main emphasis of the work, reports on the resource allocation aspect of the Stochastic Diffusion Search operations. The thesis introduces a novel model of the algorithm, generalising an Ehrenfest Urn Model from statistical physics. This approach makes it possible to obtain a thorough characterisation of the response of the algorithm in terms of the parameters describing the search conditions in case of a unique best-fit pattern in the search space. This model is further generalised in order to account for different search conditions: two solutions in the search space and search for a unique solution in a noisy search space. Also an approximate solution in the case of two alternative solutions is proposed and compared with predictions of the extended Ehrenfest Urn model. The analysis performed enabled a quantitative characterisation of the Stochastic Diffusion Search in terms of exploration and exploitation of the search space. It appeared that SDS is biased towards the latter mode of operation. This novel perspective on the Stochastic Diffusion Search lead to an investigation of extensions of the standard SDS, which would strike a different balance between these two modes of search space processing. Thus, two novel algorithms were derived from the standard Stochastic Diffusion Search, ‘context-free’ and ‘context-sensitive’ SDS, and their properties were analysed with respect to resource allocation. It appeared that they shared some of the desired features of their predecessor but also possessed some properties not present in the classic SDS. The theory developed in the thesis was illustrated throughout with carefully chosen simulations of a best-fit search for a string pattern, a simple but representative domain, enabling careful control of search conditions.

Impact of age and menopausal status on the postprandial triacylglycerol response in healthy women

Objective: To examine the impact of age and the natural menopause on the postprandial triacylglycerol (TAG) response in healthy women. Methods and results: Thirty-seven premenopausal and sixty-one postmenopausal women underwent a sequential meal postprandial investigation, in which blood samples were taken at regular intervals after a test breakfast and lunch given at 0 and 330 min respectively. Lipids and glucose were measured in the fasting sample, with TAG analysed in the postprandial samples. Postmenopausal women were shown to have higher fasting total cholesterol, low density lipoprotein cholesterol (LDL-C) and glucose (P < 0.02). Marked differences in the postprandial TAG response were evident between the groups, with a greater incremental area under the curve (IAUC) and maximum TAG concentration in the postmenopausal women (P < 0.04). Multivariate regression analysis revealed both age and fasting TAG to be independently associated with the summary measures of the postprandial TAG response in the premenopausal women only. Interestingly, sub-division of the women into both younger and older pre- and postmenopausal subgroups, showed the most marked difference in TAG-IAUC to be between the younger and the older premenopausal women, whereas differences in fasting LDL-C were most evident between the older premenopausal and the younger postmenopausal women. Conclusions: Our results suggest a divergence in the relationship of age and menopausal status with fasting LDL-C and postprandial TAG which may reflect differences in the metabolic effects of age and the menopause on these lipid risk markers or a greater impact of early oestrogen decline on pathways of TAG rather than LDL metabolism.

Contribution of apolipoprotein E genotype and docosahexaenoic acid to the LDL-cholesterol response to fish oil

Objectives: To investigate the impact of apolipoprotein E (apoE) genotype on the response of the plasma lipoprotein profile to eicosapentaenoic acid (EPA) versus docosahexaenoic acid (DHA) intervention in humans. Methods and results: 38 healthy normolipidaemic males, prospectively recruited on the basis of apoE genotype (n = 20 E3/E3 and n = 18 E3/E4), completed a double-blind placebo-controlled cross-over trial, consisting of 3 × 4 week intervention arms of either control oil, EPA-rich oil (ERO, 3.3 g EPA/day) or DHA-rich oil (DRO, 3.7 g DHA/day) in random order, separated by 10 week wash-out periods. A significant genotype-independent 28% and 19% reduction in plasma triglycerides in response to ERO and DRO was observed. For total cholesterol (TC), no significant treatment effects were evident; however a significant genotype by treatment interaction emerged (P = 0.045), with a differential response to ERO and DRO in E4 carriers. Although the genotype × treatment interaction for LDL-cholesterol (P = 0.089) did not reach significance, within DRO treatment analysis indicated a 10% increase in LDL (P = 0.029) in E4 carriers with a non-significant 4% reduction in E3/E3 individuals. A genotype-independent increase in LDL mass was observed following DRO intervention (P = 0.018). Competitive uptake studies in HepG2 cells using plasma very low density lipoproteins (VLDL) from the human trial, indicated that following DRO treatment, VLDL2 fractions obtained from E3/E4 individuals resulted in a significant 32% (P = 0.002) reduction in LDL uptake relative to the control. Conclusions: High dose DHA supplementation is associated with increases in total cholesterol in E4 carriers, which appears to be due to an increase in LDL-C and may in part negate the cardioprotective action of DHA in this population subgroup.

Performance analysis of the unconstrained FxLMS algorithm for active noise control

The paper analyzes the performance of the unconstrained filtered-x LMS (FxLMS) algorithm for active noise control (ANC), where we remove the constraints on the controller that it must be causal and has finite impulse response. It is shown that the unconstrained FxLMS algorithm always converges to, if stable, the true optimum filter, even if the estimation of the secondary path is not perfect, and its final mean square error is independent of the secondary path. Moreover, we show that the sufficient and necessary stability condition for the feedforward unconstrained FxLMS is that the maximum phase error of the secondary path estimation must be within 90°, which is the only necessary condition for the feedback unconstrained FxLMS. The significance of the analysis on a practical system is also discussed. Finally we show how the obtained results can guide us to design a robust feedback ANC headset.

Maternal adipose tissue response to nicotine administration in the pregnant rat: effects on fetal body fat and cellularity

1. Nicotine has been implicated as a causative factor in the intrauterine growth retardation associated with smoking in pregnancy. A study was set up to ascertain the effect of nicotine on fetal growth and whether this could be related to the actions of this drug on maternal adipose tissue metabolism. 2. Sprague-Dawley rats were mated and assigned to control and nicotine groups, the latter receiving nicotine in the drinking-water throughout pregnancy. Animals were weighed at regular intervals and killed on day 20 of pregnancy. Rates of maternal adipose tissue lipolysis and lipogenesis were measured. Fetal and placental weights were recorded and analysis of fetal body water, fat, protein and DNA carried out. 3. Weight gains of mothers in the nicotine group were less in the 1st and 2nd weeks of pregnancy, but similar to controls in the 3rd week. Fetal body-weights, DNA, protein and percentage water contents were similar in both groups. Mean fetal body fat (g/kg) was significantly higher in the nicotine group (96.2 (SE 5.1)) compared with controls (72.0 (SE 2.9)). Rates of maternal lipolysis were also higher in the nicotine group. 4. The cause of these differences and their effects on maternal and fetal well-being is discussed.

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues.

The structure and evolution of the stratospheric vortex in response to natural forcings

The structure and evolution of the Arctic stratospheric polar vortex is assessed during opposing phases of, primarily, the El Niño–Southern Oscillation (ENSO) and the Quasi-Biennial Oscillation (QBO), but the 11 year solar cycle and winters following large volcanic eruptions are also examined. The analysis is performed by taking 2-D moments of vortex potential vorticity (PV) fields which allow the area and centroid of the vortex to be calculated throughout the ERA-40 reanalysis data set (1958–2002). Composites of these diagnostics for the different phases of the natural forcings are then considered. Statistically significant results are found regarding the structure and evolution of the vortex during, in particular, the ENSO and QBO phases. When compared with the more traditional zonal mean zonal wind diagnostic at 60°N, the moment-based diagnostics are far more robust and contain more information regarding the state of the vortex. The study details, for the first time, a comprehensive sequence of events which map the evolution of the vortex during each of the forcings throughout an extended winter period.

Analysis of time-related metabolic fluctuations induced by ethionine in the rat

The time-course of metabolic events following response to a model hepatotoxin ethionine (800 mg/kg) was investigated over a 7 day period in rats using high-resolution (1)H NMR spectroscopic analysis of urine and multivariate statistics. Complementary information was obtained by multivariate analysis of (1)H MAS NMR spectra of intact liver and by conventional histopathology and clinical chemistry of blood plasma. (1)H MAS NMR spectra of liver showed toxin-induced lipidosis 24 h postdose consistent with the steatosis observed by histopathology, while hypertaurinuria was suggestive of liver injury. Early biochemical changes in urine included elevation of guanidinoacetate, suggesting impaired methylation reactions. Urinary increases in 5-oxoproline and glycine suggested disruption of the gamma-glutamyl cycle. Signs of ATP depletion together with impairment of the energy metabolism were given from the decreased levels in tricarboxylic acid cycle intermediates, the appearance of ketone bodies in urine, the depletion of hepatic glucose and glycogen, and also hypoglycemia. The observed increase in nicotinuric acid in urine could be an indication of an increase in NAD catabolism, a possible consequence of ATP depletion. Effects on the gut microbiota were suggested by the observed urinary reductions in the microbial metabolites 3-/4-hydroxyphenyl propionic acid, dimethylamine, and tryptamine. At later stages of toxicity, there was evidence of kidney damage, as indicated by the tubular damage observed by histopathology, supported by increased urinary excretion of lactic acid, amino acids, and glucose. These studies have given new insights into mechanisms of ethionine-induced toxicity and show the value of multisystem level data integration in the understanding of experimental models of toxicity or disease.

Integrated cytokine and metabolic analysis of pathological responses to parasite exposure in rodents

Parasitic infections cause a myriad of responses in their mammalian hosts, on immune as well as on metabolic level. A multiplex panel of cytokines and metabolites derived from four parasite-rodent models, namely, Plasmodium berghei-mouse, Trypanosoma brucei brucei-mouse, Schistosoma mansoni-mouse, and Fasciola hepatica-rat were statistically coanalyzed. 1H NMR spectroscopy and multivariate statistical analysis were used to characterize the urine and plasma metabolite profiles in infected and noninfected animals. Each parasite generated a unique metabolic signature in the host. Plasma cytokine concentrations were obtained using the ‘Meso Scale Discovery’ multi cytokine assay platform. Multivariate data integration methods were subsequently used to elucidate the component of the metabolic signature which is associated with inflammation and to determine specific metabolic correlates with parasite-induced changes in plasma cytokine levels. For example, the relative levels of acetyl glycoproteins extracted from the plasma metabolite profile in the P. berghei-infected mice were statistically correlated with IFN-γ, whereas the same cytokine was anticorrelated with glucose levels. Both the metabolic and the cytokine data showed a similar spatial distribution in principal component analysis scores plots constructed for the combined murine data, with samples from all infected animals clustering according to the parasite species and whereby the protozoan infections (P. berghei and T. b. brucei) grouped separately from the helminth infection (S. mansoni). For S. mansoni, the main infection-responsive cytokines were IL-4 and IL-5, which covaried with lactate, choline, and D-3-hydroxybutyrate. This study demonstrates that the inherently differential immune response to single and multicellular parasites not only manifests in the cytokine expression, but also consequently imprints on the metabolic signature, and calls for in-depth analysis to further explore direct links between immune features and biochemical pathways.

The primary somatosensory cortex largely contributes to the early part of the cortical response elicited by nociceptive stimuli.

Research on the cortical sources of nociceptive laser-evoked brain potentials (LEPs) began almost two decades ago (Tarkka and Treede, 1993). Whereas there is a large consensus on the sources of the late part of the LEP waveform (N2 and P2 waves), the relative contribution of the primary somatosensory cortex (S1) to the early part of the LEP waveform (N1 wave) is still debated. To address this issue we recorded LEPs elicited by the stimulation of four limbs in a large population (n=35). Early LEP generators were estimated both at single-subject and group level, using three different approaches: distributed source analysis, dipolar source modeling, and probabilistic independent component analysis (ICA). We show that the scalp distribution of the earliest LEP response to hand stimulation was maximal over the central-parietal electrodes contralateral to the stimulated side, while that of the earliest LEP response to foot stimulation was maximal over the central-parietal midline electrodes. Crucially, all three approaches indicated hand and foot S1 areas as generators of the earliest LEP response. Altogether, these findings indicate that the earliest part of the scalp response elicited by a selective nociceptive stimulus is largely explained by activity in the contralateral S1, with negligible contribution from the secondary somatosensory cortex (S2).

Response theory for equilibrium and non-equilibrium statistical mechanics: causality and generalized Kramers-Kronig relations

We consider the general response theory recently proposed by Ruelle for describing the impact of small perturbations to the non-equilibrium steady states resulting from Axiom A dynamical systems. We show that the causality of the response functions entails the possibility of writing a set of Kramers-Kronig (K-K) relations for the corresponding susceptibilities at all orders of nonlinearity. Nonetheless, only a special class of directly observable susceptibilities obey K-K relations. Specific results are provided for the case of arbitrary order harmonic response, which allows for a very comprehensive K-K analysis and the establishment of sum rules connecting the asymptotic behavior of the harmonic generation susceptibility to the short-time response of the perturbed system. These results set in a more general theoretical framework previous findings obtained for optical systems and simple mechanical models, and shed light on the very general impact of considering the principle of causality for testing self-consistency: the described dispersion relations constitute unavoidable benchmarks that any experimental and model generated dataset must obey. The theory exposed in the present paper is dual to the time-dependent theory of perturbations to equilibrium states and to non-equilibrium steady states, and has in principle similar range of applicability and limitations. In order to connect the equilibrium and the non equilibrium steady state case, we show how to rewrite the classical response theory by Kubo so that response functions formally identical to those proposed by Ruelle, apart from the measure involved in the phase space integration, are obtained. These results, taking into account the chaotic hypothesis by Gallavotti and Cohen, might be relevant in several fields, including climate research. In particular, whereas the fluctuation-dissipation theorem does not work for non-equilibrium systems, because of the non-equivalence between internal and external fluctuations, K-K relations might be robust tools for the definition of a self-consistent theory of climate change.

An inverse method for determining source characteristics for emergency response applications

Following a malicious or accidental atmospheric release in an outdoor environment it is essential for first responders to ensure safety by identifying areas where human life may be in danger. For this to happen quickly, reliable information is needed on the source strength and location, and the type of chemical agent released. We present here an inverse modelling technique that estimates the source strength and location of such a release, together with the uncertainty in those estimates, using a limited number of measurements of concentration from a network of chemical sensors considering a single, steady, ground-level source. The technique is evaluated using data from a set of dispersion experiments conducted in a meteorological wind tunnel, where simultaneous measurements of concentration time series were obtained in the plume from a ground-level point-source emission of a passive tracer. In particular, we analyze the response to the number of sensors deployed and their arrangement, and to sampling and model errors. We find that the inverse algorithm can generate acceptable estimates of the source characteristics with as few as four sensors, providing these are well-placed and that the sampling error is controlled. Configurations with at least three sensors in a profile across the plume were found to be superior to other arrangements examined. Analysis of the influence of sampling error due to the use of short averaging times showed that the uncertainty in the source estimates grew as the sampling time decreased. This demonstrated that averaging times greater than about 5min (full scale time) lead to acceptable accuracy.

Asymmetric response of demand-supply mismatch to investor's sentiment

We look through both the demand and supply side information to understand dynamics of price determination in the real estate market and examine how accurately investors’ attitudes predict the market returns and thereby flagging off extent of any demand-supply mismatch. Our hypothesis is based on the possibility that investors’ call for action in terms of their buy/sell decision and adjustment in reservation/offer prices may indicate impending demand-supply imbalances in the market. In the process, we study several real estate sectors to inform our analysis. The timeframe of our analysis (1995-2010) allows us to observe market dynamics over several economic cycles and in various stages of those cycles. Additionally, we also seek to understand how investors’ attitude or the sentiment affects the market activity over the cycles through asymmetric responses. We test our hypothesis variously using a number of measures of market activity and attitude indicators within several model specifications. The empirical models are estimated using Vector Error Correction framework. Our analysis suggests that investors’ attitude exert strong and statistically significant feedback effects in price determination. Moreover, these effects do reveal heterogeneous responses across the real estate sectors. Interestingly, our results indicate the asymmetric responses during boom, normal and recessionary periods. These results are consistent with the theoretical underpinnings.

Analysis of growth physiology and phytochemical content of Eruca and Diplotaxis Cultivars under different light and temperature regimes

Rocket is a leafy brassicaceous salad crop that encompasses two major genera (Diplotaxis and Eruca) and many different cultivars. Rocket is a rich source of antioxidants and glucosinolates, many of which are produced as secondary products by the plant in response to stress. In this paper we examined the impact of temperature and light stress on several different cultivars of wild and salad rocket. Growth habit of the plants varied in response to stress and with different genotypes, reflecting the wide geographical distribution of the plant and the different environments to which the genera have naturally adapted. Preharvest environmental stress and genotype also had an impact on how well the cultivar was able to resist postharvest senescence, indicating that breeding or selection of senescence-resistant genotypes will be possible in the future. The abundance of key phytonutrients such as carotenoids and glucosinolates are also under genetic control. As genetic resources improve for rocket it will therefore be possible to develop a molecular breeding programme specifically targeted at improving stress resistance and nutritional levels of plant secondary products. Concomitantly, it has been shown in this paper that controlled levels of abiotic stress can potentially improve the levels of chlorophyll, carotenoids and antioxidant activity in this leafy vegetable.

Constrained principal component analysis reveals functionally connected load-dependent networks involved in multiple stages of working memory

Constrained principal component analysis (CPCA) with a finite impulse response (FIR) basis set was used to reveal functionally connected networks and their temporal progression over a multistage verbal working memory trial in which memory load was varied. Four components were extracted, and all showed statistically significant sensitivity to the memory load manipulation. Additionally, two of the four components sustained this peak activity, both for approximately 3 s (Components 1 and 4). The functional networks that showed sustained activity were characterized by increased activations in the dorsal anterior cingulate cortex, right dorsolateral prefrontal cortex, and left supramarginal gyrus, and decreased activations in the primary auditory cortex and "default network" regions. The functional networks that did not show sustained activity were instead dominated by increased activation in occipital cortex, dorsal anterior cingulate cortex, sensori-motor cortical regions, and superior parietal cortex. The response shapes suggest that although all four components appear to be invoked at encoding, the two sustained-peak components are likely to be additionally involved in the delay period. Our investigation provides a unique view of the contributions made by a network of brain regions over the course of a multiple-stage working memory trial.