pinecone/core-2020-05-10-deduplication huggingface dataset:
The MtrAB two-component system controls antibiotic production in Streptomyces coelicolor A3(2)

MtrAB is a highly conserved two-component system implicated in the regulation of cell division in the Actinobacteria. It coordinates DNA replication with cell division in the unicellular Mycobacterium tuberculosis and links antibiotic production to sporulation in the filamentous Streptomyces venezuelae. Chloramphenicol biosynthesis is directly regulated by MtrA in S. venezuelae and deletion of mtrB constitutively activates MtrA and results in constitutive over-production of chloramphenicol. Here we report that in Streptomyces coelicolor, MtrA binds to sites upstream of developmental genes and the genes encoding ActII-1, ActII-4 and RedZ, which are cluster-situated regulators of the antibiotics actinorhodin (Act) and undecylprodigiosin (Red). Consistent with this, deletion of mtrB switches on the production of Act, Red and streptorubin B, a product of the Red pathway. Thus, we propose that MtrA is a key regulator that links antibiotic production to development and can be used to upregulate antibiotic production in distantly related streptomycetes
Simulation of a model nanopore sensor: ion competition underlies device
  behavior

We study a model nanopore sensor with which a very low concentration of
analyte molecules can be detected on the basis of the selective binding of the
analyte molecules to the binding sites on the pore wall. The bound analyte ions
partially replace the current-carrier cations in a thermodynamic competition.
This competition depends both on the properties of the nanopore and the
concentrations of the competing ions (through their chemical potentials). The
output signal given by the device is the current reduction caused by the
presence of the analyte ions. The concentration of the analyte ions can be
determined through calibration curves. We model the binding site with the
square-well potential and the electrolyte as charged hard spheres in an
implicit background solvent. We study the system with a hybrid method in which
we compute the ion flux with the Nernst-Planck (NP) equation coupled with the
Local Equilibrium Monte Carlo (LEMC) simulation technique. The resulting
NP+LEMC method is able to handle both strong ionic correlations inside the pore
(including finite size of ions) and bulk concentrations as low as micromolar.
We analyze the effect of bulk ion concentrations, pore parameters, binding site
parameters, electrolyte properties, and voltage on the behavior of the device
Elaboration, characterization of Cr-N based coatings

Cr, CrN and CrAlN monolayers were synthesized by RF dual magnetron sputtering on
AISI4140 steel and silicon substrates at 200°C. Multilayers coatings based on the three mono-layers such as CrN/CrAlN and Cr/CrN/CrAlN were also synthesized only on Si. The physico-chemical and mechanical properties of the layers were determined by AFM, SEM+WDS, stress, roughness and nanoindentation measurements. The influence of the thickness on the mechanical properties of the monolayers stresses has been studied and as a consequence we compared the mono and multilayers stress state
Global and Koopman modes analysis of sound generation in mixing layers

It is now well established that linear and nonlinear instability waves play a significant role in the noise generation process for a wide variety of shear flows such as jets or mixing layers. In that context, the problem of acoustic radiation generated by spatially growing instability waves of two-dimensional subsonic and supersonic mixing layers are revisited in a global point of view, i.e., without any assumption about the base flow, in both a linear and a nonlinear framework by using global and Koopman mode decompositions. In that respect, a timestepping technique based on disturbance equations is employed to extract the most dynamically relevant coherent structures for both linear and nonlinear regimes. The present analysis proposes thus a general strategy for analysing the near-field coherent structures which are responsible for the acoustic noise in these configurations. In particular, we illustrate the failure of linear global modes to describe the noise generation mechanism associated with the vortex pairing for the subsonic regime whereas they appropriately explain the Mach wave radiation of instability waves in the supersonic regime. By contrast, the Dynamic Mode Decomposition (DMD) analysis captures both the near-field dynamics and the far-field acoustics with a few number of modes for both configurations. In addition, the combination of DMD and linear global modes analyses provides new insight about the influence on the radiated noise of nonlinear interactions and saturation of instability waves as well as their interaction with the mean flow
Numerical simulation of bubble dispersion in turbulent Taylor-Couette flow

We investigate bubble dispersion in turbulent Taylor-Couette flow. The aim of this study is to describe the main mechanisms yielding preferential bubble accumulation in near-wall structures of the flow. We first proceed to direct numerical simulation of Taylor-Couette flows for three different geometrical configurations (three radius ratios η = R 1/R 2: η = 0.5, η = 0.72, and η = 0.91 with the outer cylinder at rest) and Reynolds numbers corresponding to turbulent regime ranging from 3000 to 8000. The statistics of the flow are discussed using two different averaging procedures that permit to characterize the mean azimuthal velocity, the Taylor vortices contribution and the small-scale turbulent fluctuations. The simulations are compared and validated with experimental and numerical data from literature. The second part of this study is devoted to bubble dispersion. Bubble accumulation is analyzed by comparing the dispersion obtained with the full turbulent flow field to bubble dispersion occurring at lower Reynolds numbers in previous works. Several patterns of preferential accumulation of bubbles have been observed depending on bubble size and the effect of gravity. For the smaller size considered, bubbles disperse homogeneously throughout the gap, while for the larger size they accumulate along the inner wall for the large gap width (η = 0.5). Varying the intensity of buoyancy yields complex evolution of the bubble spatial distribution. For low gravity effect, bubble entrapment is strong leading to accumulation along the inner wall in outflow regions (streaks of low wall shear stress). When buoyancy effect dominates on vortex trapping, bubbles rise through the vortices, while spiral patterns stretched along the inner cylinder are clearly identified. Force balance is analyzed to identify dominating forces leading to this accumulation and accumulation patterns are compared with previous experiments
A multiple objective linear programming model for power generation expansion planning

The planning of new units for electrical power generation is a problem which involves different and conflicting aspects. Besides cost, security issues and environmental concerns must be explicitly incorporated into the models. In this way mathematical models become more realistic, and they enhance the decision maker's comprehension of the complex and conflicting nature of the distinct aspects of the problem. A multiple objective linear programming model for power generation expansion planning is presented. The model considers three objective functions (net present cost of the expansion plans, reliability of the supply system, and environmental impacts) and three categories of constraints (load requirements, operational restrictions and budget). Three generating technologies are considered for power system expansion: oil, nuclear and coal.http://dx.doi.org/10.1002/er.444019050
Differential roles of hydrogen peroxide and superoxide in mediating IL-1-induced NF-kappaB activation and iNOS expression in bovine articular chondrocytes

Our previous studies showed that reactive oxygen species (ROS) are required for the pro-inflammatory cytokine interleukin-1beta (IL-1) to induce the activity of the Nuclear transcription Factor-kappaB (NF-kappaB) and the expression of the inducible isoform of the nitric oxide synthase (iNOS) in bovine articular chondrocytes. This study aimed at elucidating the role of hydrogen peroxide (H2O2) and the superoxide radical, two major ROS, in mediating those IL-1-induced responses. The results obtained show that chondrocytes produce both H2O2 and superoxide radical in response to IL-1. Treatment of the chondrocyte cultures with H2O2 alone did not induce NF-kappaB activation or iNOS expression. Addition of H2O2 simultaneously with IL-1 did neither enhance nor inhibit NF-kappaB activation and iNOS expression, relatively to treatment with IL-1 alone. Accordingly, treatment with catalase did not inhibit those IL-1-induced responses. Treatment with superoxide dismutase, however, effectively prevented IL-1-induced IkappaB-alpha degradation and iNOS expression. Taken together, the results obtained indicate that superoxide mediates IL-1-induced IkappaB-alpha degradation and the consequent NF-kappaB activation and iNOS expression in chondrocytes, whereas H2O2 does not seem to participate in those IL-1-induced responses. In conclusion, the present study identifies the superoxide radical as the ROS involved in mediating the IL-1-induced signaling pathway that leads to NF-kappaB activation and to the expression of NF-kappaB-dependent genes in bovine articular chondrocytes. © 2003 Wiley-Liss, Inc.http://dx.doi.org/10.1002/jcb.1042
A predictive model for freshwater bioassessment (Mondego River, Portugal)

Abstract  We sampled macroinvertebrates at 75 locations in the Mondego river catchment, Central Portugal, and developed a predictive model for water quality assessment of this basin, based on the Reference Condition Approach. Sampling was done from June to September 2001. Fifty-five sites were identified as “Reference sites” and 20 sites were used as “Test sites” to test the model. At each site we also measured 40 habitat variables to characterize water physics and chemistry, habitat type, land use, stream hydrology and geographic location. Macroinvertebrates were generally identified to species or genus level; a total of 207 taxa were found. By Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering and analysis of species contribution to similarities percentage (SIMPER), two groups of reference sites were established. Using Discriminant Analysis (stepwise forward), four variables correctly predicted 78% of the reference sites to the appropriate group: stream order, pool quality, substrate quality and current velocity. Test sites’ environmental quality was established from their relative distance to reference sites, in MDS ordination space, using a series of bands (BEAST methodology). The model performed well at upstream sites, but at downstream sites it was compromised by the lack of reference sites. As with the English RIVPACS predictive model, the Mondego model should be continually improved with the addition of new reference sites. The adaptation of the Mondego model methodology to the Water Framework Directive is possible and would consist mainly of the integration of the WFD typology and increasing the number of ellipses that define quality bands.http://dx.doi.org/10.1007/s10750-006-0720-
When to cross Over? Cross-language linking using Wikipedia for VideoCLEF 2009

We describe Dublin City University (DCU)'s participation in the VideoCLEF 2009 Linking Task. Two approaches were implemented using the Lemur information retrieval toolkit. Both approaches rst extracted a search query from the transcriptions of the Dutch TV broadcasts. One method rst performed search on a Dutch Wikipedia archive, then followed links to corresponding pages in the English Wikipedia. The other method rst translated the extracted query using machine translation and then searched the English Wikipedia collection directly. We found that using the original Dutch transcription query for searching the\ud
Dutch Wikipedia yielded better results
Detecting feature interactions in agricultural trade data using a deep neural network

Agri-analytics is an emerging sector which uses data mining to inform decision making in the agricultural sector. Machine learning is used to accomplish data mining tasks such as prediction, known as predictive analytics in the commercial context. Similar to other domains, hidden trends and events in agri-data can be difficult to detect with traditional machine learning approaches. Deep learning uses architectures made up of many levels of non-linear operations to construct a more holistic model for learning. In this work, we use deep learning for unsupervised modelling of commodity price data in agri-datasets. Specifically, we detect how appropriate input signals contribute to, and interact in, complex deep architectures. To achieve this, we provide a novel extension to a method which determines the contribution of each input feature to shallow, supervised neural networks. Our generalisation allows us to examine deep supervised and unsupervised neural networks
A general perspective on time observables

I propose a general geometric framework in which to discuss the existence of time observables. This frameworks allows one to describe a local sense in which time observables always exist, and a global sense in which they can sometimes exist subject to a restriction on the vector fields that they generate. Pauli's prohibition on quantum time observables is derived as a corollary to this result. I will then discuss how time observables can be regained in modest extensions of quantum theory beyond its standard formulation
Implementation of a Monte Carlo method to model photon conversion for solar cells.

A physical model describing different photon conversion mechanisms is presented in the context of photovoltaic applications. To solve the resulting system of equations, a Monte Carlo ray-tracing model is implemented, which takes into account the coupling of the photon transport phenomena to the non-linear rate equations describing luminescence. It also separates the generation of rays from the two very different sources of photons involved (the sun and the luminescence centers). The Monte Carlo simulator presented in this paper is proposed as a tool to help in the evaluation of candidate materials for up- and downconversion. Some application examples are presented, exploring the range of values that the most relevant parameters describing the converter should have in order to give significant gain in photocurrent
Analysis and synthesis of the variability of irradiance and PV power time series with the wavelet transform

The irradiance fluctuations and the subsequent variability of the power output of a PV system are analysed with some mathematical tools based on the wavelet transform. It can be shown that the irradiance and power time series are nonstationary process whose behaviour resembles that of a long memory process. Besides, the long memory spectral exponent α is a useful indicator of the fluctuation level of a irradiance time series. On the other side, a time series of global irradiance on the horizontal plane can be simulated by means of the wavestrapping technique on the clearness index and the fluctuation behaviour of this simulated time series correctly resembles the original series. Moreover, a time series of global irradiance on the inclined plane can be simulated with the wavestrapping procedure applied over a signal previously detrended by a partial reconstruction with a wavelet multiresolution analysis, and, once again, the fluctuation behaviour of this simulated time series is correct. This procedure is a suitable tool for the simulation of irradiance incident over a group of distant PV plants. Finally, a wavelet variance analysis and the long memory spectral exponent show that a PV plant behaves as a low-pass filter
Opacity calculation for target physics using the ABAKO/RAPCAL code

Radiative properties of hot dense plasmas remain a subject of current interest since they play an important role in inertial confinement fusion (ICF) research, as well as in studies on stellar physics. In particular, the understanding of ICF plasmas requires emissivities and opacities for both hydro-simulations and diagnostics. Nevertheless, the accurate calculation of these properties is still an open question and continuous efforts are being made to develop new models and numerical codes that can facilitate the evaluation of such properties. In this work the set of atomic models ABAKO/RAPCAL is presented, as well as a series of results for carbon and aluminum to show its capability for modeling the population kinetics of plasmas in both LTE and NLTE regimes. Also, the spectroscopic diagnostics of a laser-produced aluminum plasma using ABAKO/RAPCAL is discussed. Additionally, as an interesting application of these codes, fitting analytical formulas for Rosseland and Planck mean opacities for carbon plasmas are reported. These formulas are useful as input data in hydrodynamic simulation of targets where the computation task is so hard that in line computation with sophisticated opacity codes is prohibitive
Measuring skin temperature before, during and after exercise: a comparison of thermocouples and infrared thermography

Measuring skin temperature (TSK) provides important information about the complex thermal control system and could be interesting when carrying out studies about thermoregulation. The most common method to record TSK involves thermocouples at specific locations; however, the use of infrared thermal imaging (IRT) has increased. The two methods use different physical processes to measure TSK, and each has advantages and disadvantages. Therefore, the objective of this study was to compare the mean skin temperature (MTSK) measurements using thermocouples and IRT in three different situations: pre-exercise, exercise and post-exercise. Analysis of the residual scores in Bland-Altman plots showed poor agreement between the MTSK obtained using thermocouples and those using IRT. The averaged error was -0.75 °C during pre-exercise, 1.22 °C during exercise and -1.16 °C during post-exercise, and the reliability between the methods was low in the pre- (ICC = 0.75 [0.12 to 0.93]), during (ICC = 0.49 [-0.80 to 0.85]) and post-exercise (ICC = 0.35 [-1.22 to 0.81] conditions. Thus, there is poor correlation between the values of MTSK measured by thermocouples and IRT pre-exercise, exercise and post-exercise, and low reliability between the two forms of measurement
Experimental and numerical study of wind flow behind windbreaks

The shelter effect of a windbreak protects aggregate piles and provides a reduction of particle emissions in harbours. RANS (Reynolds-averaged Navier–Stokes equations) simulations using three variants of k–ε (standard k–ε, RNG k–ε and realizable k–ε) turbulence closure models have been performed to analyse wind flow characteristics behind an isolated fence located on a flat surface without roughness elements. The performance of the three turbulence models has been assessed by wind tunnel experiments. Cases of fences with different porosities (φ) have been evaluated using wind tunnel experiments as well as numerical simulations. The aim is to determine an optimum porosity for sheltering effect of an isolated windbreak. A value of 0.35 was found as the optimum value among the studied porosities (φ=0, 0.1, 0.24, 0.35, 0.4, 0.5)
A survey on multi-output regression

In recent years, a plethora of approaches have been proposed to deal\ud
with the increasingly challenging task of multi-output regression. This paper\ud
provides a survey on state-of-the-art multi-output regression methods,\ud
that are categorized as problem transformation and algorithm adaptation\ud
methods. In addition, we present the mostly used performance evaluation\ud
measures, publicly available data sets for multi-output regression\ud
real-world problems, as well as open-source software frameworks
Comparison of Expected Yields for Light Radioactive Beams at SPIRAL-1 And 2

Commune avec MECA au CENBGInternational audienceLight-particles stable high-intensity beams (p, d, 3,4He...) will be available from the Linac driver accelerator of SPIRAL-2. Yields of neutron-deficient isotopes as well as of neutron-rich isotopes (by means of reactions with secondary neutrons) are compared with those presently available at the SPIRAL-1 facility. We explore, for light beams (Z< 16) asked in the 'white book' of SPIRAL-2 1, the production methods taking into account the in-target yield but also the feasibility of making such beams by the ISOL method (considering reaction, target, thermal and release properties). We discuss some of the tests needed and planned. A comparison with the present and potentially attainable yields at SPIRAL-1 is presented
Study on the possible detection of Gamma Ray Bursts with the ANTARES neutrino telescope

International audienceThe ANTARES telescope, currently in construction, is aiming to detect high energy neutrinos. Data from the first line of the detector, which became operational recently, demonstrates that the nominal time and space resolutions are achieved. Various models predict the emission of high energy neutrinos from astrophysical sources such as Supernova Remnants, Microquasars, Active Galactic Nuclei and Gamma Ray Bursts. With the custom designed data acquisition system of this detector, in combination with the existing satellite alert systems, the ANTARES telescope has an increased sensitivity for neutrinos from Gamma Ray Bursts compared to conventional time independent sources
A new approach to formulating and appraising drug policy: a multi-criterion decision analysis applied to alcohol and cannabis regulation

Background\ud
Drug policy, whether for legal or illegal substances, is a controversial field that encompasses many complex issues. Policies can have effects on a myriad of outcomes and stakeholders differ in the outcomes they consider and value, while relevant knowledge on policy effects is dispersed across multiple research disciplines making integrated judgements difficult.\ud
\ud
Methods\ud
Experts on drug harms, addiction, criminology and drug policy were invited to a decision conference to develop a multi-criterion decision analysis (MCDA) model for appraising alternative regulatory regimes. Participants collectively defined regulatory regimes and identified outcome criteria reflecting ethical and normative concerns. For cannabis and alcohol separately, participants evaluated each regulatory regime on each criterion and weighted the criteria to provide summary scores for comparing different regimes.\ud
\ud
Results\ud
Four generic regulatory regimes were defined: absolute prohibition, decriminalisation, state control and free market. Participants also identified 27 relevant criteria which were organised into seven thematically related clusters. State control was the preferred regime for both alcohol and cannabis. The ranking of the regimes was robust to variations in the criterion-specific weights.\ud
\ud
Conclusion\ud
The MCDA process allowed the participants to deconstruct complex drug policy issues into a set of simpler judgements that led to consensus about the results