Cost-effective flexibilisation of an 80 MWe retrofitted biomass power plants : improved combustion control dynamics using virtual air flow sensors

As they deliver dispatchable renewable energy, biomass power plants are expected to play a key role in the stability of the future electricity grids dominated by intermittent renewables. Large-scale, biomass-fired power plants are often retrofitted from coal-fired plants. Such a fuel modi-fication combined with decreasing pollutant emission limits and higher requirements in terms load flexibility can lead to a decrease of the maximum power delivered by the unit. The limiting factors are partly related to the control systems of those plants. In this paper, we present the results of the upgrading of an 80 MWe, retrofitted biomass power plant that was achieved improving the dynamic control of the combustion process. Thanks to the addition of virtual air flow sensors in the control system and the re-design of the combustion control loops, the unde-sired effects of a recent 10% power increase on NOx emissions were more than compensated. The accurate control of the local NOx production in the furnace resulted in a decrease of these emissions by 15% with an increased stability. This study will help increasing the cost-effectiveness of such conversions, and facilitate the development of dispatchable, renewable power units able to contribute to the grid stability

Polytopic Cryptanalysis

Standard differential cryptanalysis uses statistical dependencies between the difference of two plaintexts and the difference of the respective two ciphertexts to attack a cipher. Here we introduce polytopic cryptanalysis which considers interdependencies between larger sets of texts as they traverse through the cipher. We prove that the methodology of standard differential cryptanalysis can unambiguously be extended and transferred to the polytopic case including impossible differentials. We show that impossible polytopic transitions have generic advantages over impossible differentials. To demonstrate the practical relevance of the generalization, we present new low-data attacks on round-reduced DES and AES using impossible polytopic transitions that are able to compete with existing attacks, partially outperforming these

Susceptibility testing and reporting of new antibiotics with a focus on tedizolid: an international working group report

Inappropriate use and overuse of antibiotics are among the most important factors in resistance development, and effective antibiotic stewardship measures are needed to optimize outcomes. Selection of appropriate antimicrobials relies on accurate and timely antimicrobial susceptibility testing. However, the availability of clinical breakpoints and in vitro susceptibility testing often lags behind regulatory approval by several years for new antimicrobials. A Working Group of clinical/medical microbiologists from Brazil, Canada, Mexico, Saudi Arabia, Russia and the UK recently examined issues surrounding antimicrobial susceptibility testing for novel antibiotics. While commercially available tests are being developed, potential surrogate antibiotics may be used as marker of susceptibility. Using tedizolid as an example of a new antibiotic, this special report makes recommendations to optimize routine susceptibility reporting

Universality of Level Spacing Distributions in Classical Chaos

We suggest that random matrix theory applied to a classical action matrix can be used in classical physics to distinguish chaotic from non-chaotic behavior. We consider the 2-D stadium billiard system as well as the 2-D anharmonic and harmonic oscillator. By unfolding of the spectrum of such matrix we compute the level spacing distribution, the spectral auto-correlation and spectral rigidity. We observe Poissonian behavior in the integrable case and Wignerian behavior in the chaotic case. We present numerical evidence that the action matrix of the stadium billiard displays GOE behavior and give an explanation for it. The findings present evidence for universality of level fluctuations - known from quantum chaos - also to hold in classical physics

Universal scaling of the logarithmic negativity in massive quantum field theory

We consider the logarithmic negativity, a measure of bipartite entanglement, in a general unitary 1 + 1-dimensional massive quantum field theory, not necessarily integrable. We compute the negativity between a finite region of length r and an adjacent semi-infinite region, and that between two semi-infinite regions separated by a distance r. We show that the former saturates to a finite value, and that the latter tends to zero, as r -> ∞. We show that in both cases, the leading corrections are exponential decays in r (described by modified Bessel functions) that are solely controlled by the mass spectrum of the model, independently of its scattering matrix. This implies that, like the entanglement entropy (EE), the logarithmic negativity displays a very high level of universality, allowing one to extract information about the mass spectrum. Further, a study of sub-leading terms shows that, unlike the EE, a large-r analysis of the negativity allows for the detection of bound states

Primary cardiac sarcoma presenting as acute left-sided heart failure

Primary cardiac sarcomas are rare malignant tumors of the heart. Clinical features depend on the site of tumor and vary from symptoms of congestive heart failure to thromboembolism and arrhythmias. Echocardiography is helpful but definitive diagnosis is established by histopathology. Surgical resection is the mainstay of treatment, and the role of chemotherapy and radiotherapy is unclear. We report a case of primary cardiac sarcoma which presented with signs and symptoms of acute left-sided heart failure

Stochastic Resonance of Ensemble Neurons for Transient Spike Trains: A Wavelet Analysis

By using the wavelet transformation (WT), we have analyzed the response of an ensemble of $N$ (=1, 10, 100 and 500) Hodgkin-Huxley (HH) neurons to {\it transient} $M$-pulse spike trains ($M=1-3$) with independent Gaussian noises. The cross-correlation between the input and output signals is expressed in terms of the WT expansion coefficients. The signal-to-noise ratio (SNR) is evaluated by using the {\it denoising} method within the WT, by which the noise contribution is extracted from output signals. Although the response of a single (N=1) neuron to sub-threshold transient signals with noises is quite unreliable, the transmission fidelity assessed by the cross-correlation and SNR is shown to be much improved by increasing the value of $N$: a population of neurons play an indispensable role in the stochastic resonance (SR) for transient spike inputs. It is also shown that in a large-scale ensemble, the transmission fidelity for supra-threshold transient spikes is not significantly degraded by a weak noise which is responsible to SR for sub-threshold inputs.Comment: 20 pages, 4 figure