Sum-of-squares of polynomials approach to nonlinear stability of fluid flows: an example of application

With the goal of providing the first example of application of a recently proposed method, thus demonstrating its ability to give results in principle, global stability of a version of the rotating Couette flow is examined. The flow depends on the Reynolds number and a parameter characterising the magnitude of the Coriolis force. By converting the original Navier-Stokes equations to a finite-dimensional uncertain dynamical system using a partial Galerkin expansion, high-degree polynomial Lyapunov functionals were found by sum-of-squares-of-polynomials optimization. It is demonstrated that the proposed method allows obtaining the exact global stability limit for this flow in a range of values of the parameter characterising the Coriolis force. Outside this range a lower bound for the global stability limit was obtained, which is still better than the energy stability limit. In the course of the study several results meaningful in the context of the method used were also obtained. Overall, the results obtained demonstrate the applicability of the recently proposed approach to global stability of the fluid flows. To the best of our knowledge, it is the first case in which global stability of a fluid flow has been proved by a generic method for the value of a Reynolds number greater than that which could be achieved with the energy stability approach

Hybrid Model For Word Prediction Using Naive Bayes and Latent Information

Historically, the Natural Language Processing area has been given too much attention by many researchers. One of the main motivation beyond this interest is related to the word prediction problem, which states that given a set words in a sentence, one can recommend the next word. In literature, this problem is solved by methods based on syntactic or semantic analysis. Solely, each of these analysis cannot achieve practical results for end-user applications. For instance, the Latent Semantic Analysis can handle semantic features of text, but cannot suggest words considering syntactical rules. On the other hand, there are models that treat both methods together and achieve state-of-the-art results, e.g. Deep Learning. These models can demand high computational effort, which can make the model infeasible for certain types of applications. With the advance of the technology and mathematical models, it is possible to develop faster systems with more accuracy. This work proposes a hybrid word suggestion model, based on Naive Bayes and Latent Semantic Analysis, considering neighbouring words around unfilled gaps. Results show that this model could achieve 44.2% of accuracy in the MSR Sentence Completion Challenge

Turbulent separation upstream of a forward-facing step

The turbulent flow over a forward-facing step is studied using two-dimensional time-resolved particle image velocimetry. The structure and behaviour of the separation region in front of the step is investigated using conditional averages based on the area of reverse flow present. The relation between the position of the upstream separation and the two-dimensional shape of the separation region is presented. It is shown that when of ‘closed' form, the separation region can become unstable resulting in the ejection of fluid over the corner of the step. The separation region is shown to grow simultaneously in both the wall-normal and streamwise directions, to a point where the maximum extent of the upstream position of separation is limited by the accompanying transfer of mass over the step corner. The conditional averages are traced backwards in time to identify the average behaviour of the boundary-layer displacement thickness leading up to such events. It is shown that these ejections are preceded by the convection of low-velocity regions from upstream, resulting in a three-dimensional interaction within the separation region. The size of the low-velocity regions, and the time scale at which the separation region fluctuates, is shown to be consistent with the large boundary layer structures observed in the literature. Instances of a highly suppressed separation region are accompanied by a steady increase in velocity in the upstream boundary laye

Neurobehavioral Evaluation of Mice Dosed With Water Hemlock Green Seeds and Tubers

Water hemlock are plants of the genus Cicuta and are toxic to animals and humans. The primary toxin is cicutoxin, which is abundant in the tubers, but less abundant in other parts of the plant. Other cicutoxin-like compounds, such as cicutols, which may also contribute to the toxicity of water hemlock, are more abundant in non-tuber plant parts. The objective of this study was to determine the toxicity of different parts of water hemlock and characterize their effects on motor function/coordination in mice. An aqueous extract of green seeds, dry seeds, tubers, flowers and stems of water hemlock was dosed orally to mice to determine their acute toxicity. The results indicated that only the green seeds and tubers were sufficiently toxic to animals to induce seizures and death. The LD50 for tubers and green seeds was 17 mg/kg and 1320 mg/kg, respectively. Several tests were used to evaluate motor function and behavior in treated mice including rotarod, tremor monitor, and open field. The animals were evaluated before dosing and 30, 90, 120, 150, 180, 240, and 300 min after dosing. Water hemlock affected muscle function of mice, including their balance and motility on a rotarod, motor activity, and exploratory and anxiety-related (i.e., thigmotaxis) behaviors in an open field. Seizures interspersed with central nervous system (CNS) motor depression were observed in animals poisoned by water hemlock. Extracts from tubers were especially potent in causing a decrease in motor activity and resultant depression, while periodically provoking seizures. Further research is needed to identify, quantitate, and purify cicutoxin and the other polyacetylene compounds from the various water hemlock plant parts to evaluate their toxicity and effects on motor function

Designing antibiotic cycling strategies by determining and understanding local adaptive landscapes

The evolution of antibiotic resistance among bacteria threatens our continued ability to treat infectious diseases. The need for sustainable strategies to cure bacterial infections has never been greater. So far, all attempts to restore susceptibility after resistance has arisen have been unsuccessful, including restrictions on prescribing [1] and antibiotic cycling [2,3]. Part of the problem may be that those efforts have implemented different classes of unrelated antibiotics, and relied on removal of resistance by random loss of resistance genes from bacterial populations (drift). Here, we show that alternating structurally similar antibiotics can restore susceptibility to antibiotics after resistance has evolved. We found that the resistance phenotypes conferred by variant alleles of the resistance gene encoding the TEM {\beta}-lactamase (blaTEM) varied greatly among 15 different {\beta}-lactam antibiotics. We captured those differences by characterizing complete adaptive landscapes for the resistance alleles blaTEM-50 and blaTEM-85, each of which differs from its ancestor blaTEM-1 by four mutations. We identified pathways through those landscapes where selection for increased resistance moved in a repeating cycle among a limited set of alleles as antibiotics were alternated. Our results showed that susceptibility to antibiotics can be sustainably renewed by cycling structurally similar antibiotics. We anticipate that these results may provide a conceptual framework for managing antibiotic resistance. This approach may also guide sustainable cycling of the drugs used to treat malaria and HIV

Magnetite and its transformation to hematite in a soil derived from steatite.

O presente trabalho objetivou caracterizar o mineral magnetico e identificar suas rotas pedogeneticas de transformacao em um solo formado sobre esteatito, de Minas Gerais, Brasil. O oxido de ferro isoestrutural ao espinelio foi identificado e caracterizado por analises quimicas, difracao de raios X, espectroscopia Mossbauer e medidas de magnetizacao de saturacao. Na rocha fresca, foi encontrada magnetita estequiometrica e bem cristalizada, com parametro da rede cubica, ao = 0.8407(5) nm. Nas fracoes areia e silte, foram detectadas magnetita parcialmente alterada e hematita estequiometrica e bem cristalizada, com parametros de rede hexagonal, a = 0.5036(3) nm e c = 1.375(4)nm. A ocorrencia dessas hematitas deveu-se principalmente a oxidacao do Fe2+ a Fe3+, no sitio octaedrico de magnetita, durante a pedogenese. Esse processo foi caracterizado pelo aparecimento de pequena quantidade de Fe3+ eletronicamente desacoplada, encontrada nas magnetitas parcialmente oxidadas, cujas formulas para as diferentes estequiometrias foram propostas. Verificou-se tambem pequena quantidade de ilmenita nas amostras de rocha e de solo

Early pneumococcal clearance in mice induced by systemic immunization with recombinant BCG PspA-PdT prime and protein boost correlates with cellular and humoral immune response in bronchoalveolar fluids (BALF)

© 2019 The Author(s) An effective immunological response in the lungs during a pneumococcal infection is a key factor to the bacteria clearance and prevention of sepsis. In order to develop broad-range pneumococcal vaccines several pneumococcal proteins and strong adjuvants have been investigated. Previously, we constructed a recombinant BCG (rBCG) strain expressing a fragment of PspA (Pneumococcal surface protein A) fused to PdT (detoxified form of pneumolysin). Immunization of mice with a priming dose of rBCG PspA-PdT followed by a booster dose of rPspA-PdT fused protein induced a high antibody response in the serum and protected mice against lethal challenge. Here, we investigated the humoral and cellular immune response in the Bronchoalveolar lavage fluid (BALF). Immunization of mice with rBCG PspA-PdT / rPspA-PdT induced rapid clearance of bacteria after challenge, an early control of the cellular influx and reduced inflammatory cytokine levels in the BALF. In addition, rBCG PspA-PdT / rPspA-PdT induced higher lymphocyte recruitment to the lungs at 48 h, showing an increased percentage of CD4+ T cells. Furthermore, BALF samples from mice immunized with rBCG PspA-PdT / PspA-PdT showed high binding of IgG2c and enhanced complement deposition on the pneumococcal surface; antibody binding was specific to PspA as no binding was observed to a PspA-knockout strain. Taken together, our results show that the immunization with rBCG PspA-PdT / rPspA-PdT induces humoral and cellular immune responses in the lungs, promotes an early clearance of pneumococci and protects against the systemic dissemination of pneumococci

Optimal mode decomposition for unsteady flows

A new method, herein referred to as optimal mode decomposition (OMD), of finding a linear model to describe the evolution of a fluid flow is presented. The method estimates the linear dynamics of a high-dimensional system which is first projected onto a subspace of a user-defined fixed rank. An iterative procedure is used to find the optimal combination of linear model and subspace that minimizes the system residual error. The OMD method is shown to be a generalization of dynamic mode decomposition (DMD), in which the subspace is not optimized but rather fixed to be the proper orthogonal decomposition (POD) modes. Furthermore, OMD is shown to provide an approximation to the Koopman modes and eigenvalues of the underlying system. A comparison between OMD and DMD is made using both a synthetic waveform and an experimental data set. The OMD technique is shown to have lower residual errors than DMD and is shown on a synthetic waveform to provide more accurate estimates of the system eigenvalues. This new method can be used with experimental and numerical data to calculate the ‘optimal' low-order model with a user-defined rank that best captures the system dynamics of unsteady and turbulent flow