Stochastically forced dislocation density distribution in plastic deformation

The dynamical evolution of dislocations in plastically deformed metals is controlled by both deterministic factors arising out of applied loads and stochastic effects appearing due to fluctuations of internal stress. Such type of stochastic dislocation processes and the associated spatially inhomogeneous modes lead to randomness in the observed deformation structure. Previous studies have analyzed the role of randomness in such textural evolution but none of these models have considered the impact of a finite decay time (all previous models assumed instantaneous relaxation which is "unphysical") of the stochastic perturbations in the overall dynamics of the system. The present article bridges this knowledge gap by introducing a colored noise in the form of an Ornstein-Uhlenbeck noise in the analysis of a class of linear and nonlinear Wiener and Ornstein-Uhlenbeck processes that these structural dislocation dynamics could be mapped on to. Based on an analysis of the relevant Fokker-Planck model, our results show that linear Wiener processes remain unaffected by the second time scale in the problem but all nonlinear processes, both Wiener type and Ornstein-Uhlenbeck type, scale as a function of the noise decay time τ. The results are expected to ramify existing experimental observations and inspire new numerical and laboratory tests to gain further insight into the competition between deterministic and random effects in modeling plastically deformed samples.

Bayesian Emulation for Sequential Modeling, Inference and Decision Analysis

The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.

Likelihood-Based Inference for Partially Observed Multi-Type Markov Branching Processes

Thesis (Ph.D.)--University of Washington, 2016-08

Synthetic portfolio for event studies: Estimating the effects of volatility call auctions

We propose a method denoted as synthetic portfolio for event studies in market microstructure that is particularly interesting to use with high frequency data and thinly traded markets. The method is based on Synthetic Control Method and provides a robust data driven method to build a counterfactual for evaluating the effects of the volatility call auctions. We find that SMC could be used if the loss function is defined as the difference between the returns of the asset and the returns of a synthetic portfolio. We apply SCM to test the performance of the volatility call auction as a circuit breaker in the context of an event study. We find that for Colombian Stock Market securities, the asynchronicity of intraday data reduces the analysis to a selected group of stocks, however it is possible to build a tracking portfolio. The realized volatility increases after the auction, indicating that the mechanism is not enhancing the price discovery process.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Motor function measure scale, steroid therapy and patients with Duchenne muscular dystrophy

Objective: To assess the evolution of motor function in patients with Duchenne muscular dystrophy (DMD) treated with steroids (prednisolone or deflazacort) through the Motor Function Measure (MFM), which evaluates three dimensions of motor performance (D1, D2, D3). Methods: Thirty-three patients with DMD (22 ambulant, 6 non-ambulant and 5 who lost the capacity to walk during the period of the study) were assessed using the MFM scale six times over a period of 18 months. Results: All the motor functions remained stable for 14 months in all patients, except D1 for those who lost their walking ability. In ambulant patients, D2 (axial and proximal motor capacities) motor functions improved during six months; an improvement in D3 (distal motor capacity) was noted during the total follow-up. D1 (standing posture and transfers) and total score were useful to predict the loss of the ability to walk. Conclusions: The use of the MFM in DMD patients confirms the benefits of the steroid treatment for slowing the progression of the disease.

A Mutant of Arp2p Causes Partial Disassembly of the Arp2/3 Complex and Loss of Cortical Actin Function in Fission Yeast

The Arp2/3 complex is an essential component of the yeast actin cytoskeleton that localizes to cortical actin patches. We have isolated and characterized a temperature-sensitive mutant of Schizosaccharomyces pombe arp2 that displays a defect in cortical actin patch distribution. The arp2+ gene encodes an essential actin-related protein that colocalizes with actin at the cortical actin patch. Sucrose gradient analysis of the Arp2/3 complex in the arp2-1 mutant indicated that the Arp2p and Arc18p subunits are specifically lost from the complex at restrictive temperature. These results are consistent with immunolocalization studies of the mutant that show that Arp2-1p is diffusely localized in the cytoplasm at restrictive temperature. Interestingly, Arp3p remains localized to the cortical actin patch under the same restrictive conditions, leading to the hypothesis that loss of Arp2p from the actin patch affects patch motility but does not severely compromise its architecture. Analysis of the mutant Arp2 protein demonstrated defects in ATP and Arp3p binding, suggesting a possible model for disruption of the complex.

Photon-hadron jet correlations in p plus p and Au plus Au collisions at s(NN)=200 GeV

We report the observation at the Relativistic Heavy Ion Collider of suppression of back-to-back correlations in the direct photon+jet channel in Au+Au relative to p+p collisions. Two-particle correlations of direct photon triggers with associated hadrons are obtained by statistical subtraction of the decay photon-hadron (gamma-h) background. The initial momentum of the away-side parton is tightly constrained, because the parton-photon pair exactly balance in momentum at leading order in perturbative quantum chromodynamics, making such correlations a powerful probe of the in-medium parton energy loss. The away-side nuclear suppression factor, I(AA), in central Au+Au collisions, is 0.32 +/- 0.12(stat)+/- 0.09(syst) for hadrons of 3 < p(T)(h)< 5 in coincidence with photons of 5 < p(T)(gamma)< 15 GeV/c. The suppression is comparable to that observed for high-p(T) single hadrons and dihadrons. The direct photon associated yields in p+p collisions scale approximately with the momentum balance, z(T)equivalent to p(T)(h)/p(T)(gamma), as expected for a measurement of the away-side parton fragmentation function. We compare to Au+Au collisions for which the momentum balance dependence of the nuclear modification should be sensitive to the path-length dependence of parton energy loss.

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

Alterations in energy properties of eucalyptus wood and bark subjected to torrefaction: The potential of mass loss as a synthetic indicator

Torrefaction is a mild pyrolysis process (usually up to 300 degrees C) that changes the chemical and physical properties of biomass. This process is a possible pre-treatment prior to further processes (transport, grinding, combustion, gasification, etc) to generate energy or biofuels. In this study, three eucalyptus wood species and bark were subjected to different torrefaction conditions to determine the alterations in their structural and energy properties. The most severe treatment (280 degrees C, 5 h) causes mass losses of more than 35%, with severe damage to anatomical structure, and an increase of about 27% in the specific energy content. Bark is more sensitive to heat than wood. Energy yields are always higher than mass yields, thereby demonstrating the benefits of torrefaction in concentrating biomass energy. The overall mass loss is proposed as a relevant parameter to synthesize the effect of torrefaction conditions (temperature and duration). Accordingly, all results are summarised by analytical expressions able to predict the energy properties as a function of the overall mass loss. These expressions are intended to be used in any optimization procedure, from production in the field to the final use. (c) 2010 Elsevier Ltd. All rights reserved.

Disruption of NaS1 sulfate transport function in mice leads to enhanced acetaminophen-induced hepatotoxicity

Sulfate is required for detoxification of xenobiotics such as acetaminophen (APAP), a leading cause of liver failure in humans. The NaS1 sulfate transporter maintains blood sulfate levels sufficiently high for sulforiation reactions to work effectively for drug detoxification. In the present study, we identified two loss-of-function polymorphisms in the human NaS1 gene and showed the Nas1-null mouse to be hypersensitive to APAP hepatotoxicity. APAP treatment led to increased liver damage and decreased hepatic glutathione levels in the hyposulfatemic Nas1-null mice compared with that in normosulfatemic wild-type mice. Analysis of urinary APAP metabolites revealed a significantly lower ratio of APAP-sulfate to APAP-glucuronide in the Nas1-null mice. These results suggest hyposulfatemia increases sensitivity to APAP-induced hepatotoxicity by decreasing the sulfonation capacity to metabolize APAP. In conclusion, the results of this study highlight the importance of plasma sulfate level as a key modulator of acetaminophen metabolism and suggest that individuals with reduced NaS1 sulfate transporter function would be more sensitive to hepatotoxic agents.

Loss-of-function mutations in the genes encoding prokineticin-2 or prokineticin receptor-2 cause autosomal recessive Kallmann syndrome

Context: Physiological activation of the prokineticin pathway has a critical role in olfactory bulb morphogenesis and GnRH secretion in mice. Objective: To investigate PROK2 and PROKR2 mutations in patients with hypogonadotropic hypogonadism (HH) associated or not with olfactory abnormalities. Design: We studied 107 Brazilian patients with HH (63 with Kallmann syndrome and 44 with normosmic HH) and 100 control individuals. The coding regions of PROK2 and PROKR2 were amplified by PCR followed by direct automatic sequencing. Results: In PROK2, two known frameshift mutations were identified. Two brothers with Kallmann syndrome harbored the homozygous p. G100fsX121 mutation, whereas one male with normosmic HH harbored the heterozygous p. I55fsX56 mutation. In PROKR2, four distinct mutations (p. R80C, p. Y140X, p. L173R, and p. R268C) were identified in five patients with Kallmann syndrome and in one patient with normosmic HH. These mutations were not found in the control group. The p. R80C, p. L173R, and p. R268C missense mutations were identified in the heterozygous state in the HH patients and in their asymptomatic first-degree relatives. In addition, nomutations of FGFR1, KAL1, GnRHR, KiSS-1, or GPR54 were identified in these patients. Notably, the new nonsense mutation (p. Y140X) was identified in the homozygous state in an anosmic boy with micropenis, bilateral cryptorchidism, and high-arched palate. His asymptomatic parents were heterozygous for this severe defect. Conclusion: We expanded the repertoire of PROK2 and PROKR2 mutations in patients with HH. In addition, we show that PROKR2 haploinsufficiency is not sufficient to cause Kallmann syndrome or normosmic HH, whereas homozygous loss-of-function mutations either in PROKR2 or PROK2 are sufficient to cause disease phenotype, in accordance with the Prokr2 and Prok2 knockout mouse models.

Identification of genes differentially expressed in a strain of the mold Aspergillus nidulans carrying a loss-of-function mutation in the palA gene

To identify genes differentially expressed in a strain of the mold Aspergillus nidulans carrying a loss-of-function mutation in palA, a gene in the pH-responsive signal transduction pathway, suppression subtractive hybridization was performed between RNA isolated from the biA1 and biA1 palA1 strains grown under limiting inorganic phosphate at pH 5.0. We have identified several genes upregulated in the biA1 palA1 mutant strain that play important roles in mitotic fidelity, stress responses, enzyme secretion, signal transduction mechanisms, development, genome stability, phosphate sensing, and transcriptional regulation among others. The upregulation of eight of these transcripts was also validated by Northern blot. Moreover, we show that a loss of function mutation in the palA gene drastically reduced the neutral sugar content of the acid phosphatase PacA secreted by the fungus A. nidulans grown at pH 5.0 compared with a control strain.

Analysis of the microbial community structure and function of a laboratory scale enhanced biological phosphorus removal reactor

A laboratory scale sequencing batch reactor (SBR) operating for enhanced biological phosphorus removal (EBPR) and fed with a mixture of volatile fatty acids (VFAs) showed stable and efficient EBPR capacity over a four-year-period. Phosphorus (P), poly-beta-hydroxyalkanoate (PHA) and glycogen cycling consistent with classical anaerobic/aerobic EBPR were demonstrated with the order of anaerobic VFA uptake being propionate, acetate then butyrate. The SBR was operated without pH control and 63.67+/-13.86 mg P l(-1) was released anaerobically. The P% of the sludge fluctuated between 6% and 10% over the operating period (average of 8.04+/-1.31%). Four main morphological types of floc-forming bacteria were observed in the sludge during one year of in-tensive microscopic observation. Two of them were mainly responsible for anaerobic/aerobic P and PHA transformations. Fluorescence in situ hybridization (FISH) and post-FISH chemical staining for intracellular polyphosphate and PHA were used to determine that 'Candidatus Accumulibacter phosphatis' was the most abundant polyphosphate accumulating organism (PAO), forming large clusters of coccobacilli (1.0-1.5 mum) and comprising 53% of the sludge bacteria. Also by these methods, large coccobacillus-shaped gammaproteobacteria (2.5-3.5 mum) from a recently described novel cluster were glycogen-accumulating organisms (GAOs) comprising 13% of the bacteria. Tetrad-forming organisms (TFOs) consistent with the 'G bacterium' morphotype were alphaproteobacteria , but not Amaricoccus spp., and comprised 25% of all bacteria. According to chemical staining, TFOs were occasionally able to store PHA anaerobically and utilize it aerobically.