Mosquito sound communication: are male swarms loud enough to attract females?

Given the unsurpassed sound sensitivity of mosquitoes among arthropods and the sound source power required for long-range hearing, we investigated the distance over which female mosquitoes detect species-specific cues in the sound of station-keeping mating swarms. A common misunderstanding, that mosquitoes cannot hear at long range because their hearing organs are ‘particle-velocity’ receptors, has clouded the fact that particle velocity is an intrinsic component of sound whatever the distance to the sound source. We exposed free-flying Anopheles coluzzii females to pre-recorded sounds of male An. coluzzii and An. gambiae s.s. swarms over a range of natural sound levels. Sound levels tested were related to equivalent distances between the female and the swarm for a given number of males, enabling us to infer distances over which females might hear large male swarms. We show that females do not respond to swarm sound up to 48 dB sound pressure level (SPL) and that louder SPLs are not ecologically relevant for a swarm. Considering that swarms are the only mosquito sound source that would be loud enough to be heard at long range, we conclude that inter-mosquito acoustic communication is restricted to close-range pair interactions. We also showed that the sensitivity to sound in free-flying males is much enhanced compared to that of tethered ones.     

From IP to Start-up： Building a Robust Life Science Incubator

An incubator is an organization that supports new ventures to grow and survive during the early stages. Mainly dedicated to information technology, life science may appear to be the next hot spot for incubators. Are there stabilized good practices？ Are the business models in information technology and in life science comparable when it goes to start-ups＇ incubation？ Leveraging our experience as practitioner in this field and using an inductive methodology, this paper tends to propose simple principles to help build robust incubators in life science, and to contribute to disseminate an entrepreneurial approach through an industry still dominated by blue chips.     

On the additive decomposition for polynomic maps

A polynomic operator can be represented asT= Ltauwhere τ is an imbedding of the input Hilbert resolution space into the appropriate Hilbert scale, andLis a mapping of the Hilbert resolution space that results from closing the span of the Hilbert scale with respect to a naturally defined inner product, into the output Hilbert resolution space. This paper demonstrates the relationship between the strongly causal (strongly anticausal, memoryless) components ofLandT.     

Chicory juice clarification by membrane filtration using rotating disk module

Clarification is the first step of inulin production from chicory juice, and membrane filtration as an alternative can greatly simplify this process, increase juice yield, improve product quality, and reduce the cost and waste volume. In this study, a rotating disk module (RDM) was used to investigate the clarification of chicory juice by four micro- and ultrafiltration membranes. Compared with dead end filtration, the RDM had a much higher permeate flux and product quality. High rotating speeds produced high permeate fluxes and reduced flux decline, because of the strong back transport of foulant from fouling layer to feed solution. At high rotating speeds of 1500–2000 rpm, the permeate flux increased with membrane pore size and transmembrane pressure (TMP), while at low rotating speeds (<1000 rpm), permeate flux was independent of membrane type and TMP due to a thick deposited fouling layer as a dominant filtration resistance, while carbohydrate transmission decreased at higher TMP because of denser cake layer as an additional selective membrane. The highest carbohydrate transmission (∼98%) and desirable permeate turbidity (2.4 NTU) was obtained at a TMP of 75 kPa and a rotating speed of 2000 rpm for FSM0.45PP membrane. With the RDM, the Volume Reduction Ratio (VRR) could reach 10 with a high permeate flux (106 L m⁻² h⁻¹) in the concentration test, and permeate was still rich in carbohydrate and well clarified. Chemical cleaning with 0.5% P3-ultrasil 10 detergent solution was able to recover 90% water flux of fouled membrane.     

Genetic diversity of Oenoccoccus oeni isolated from wines treated with phenolic extracts as antimicrobial agents

Molecular techniques have been applied to study the evolution of wine-associated lactic acid bacteria from red wines produced in the absence and presence of antimicrobial phenolic extracts, eucalyptus leaves and almond skins, and to genetically characterize representative Oenococcus oeni strains. Monitoring microbial populations by PCR-DGGE targeting the rpoB gene revealed that O. oeni was, as expected, the species responsible for malolactic fermentation (MLF). Representative strains from both extract-treated and not-treated wines were isolated and all were identified as O. oeni species, by 16S rRNA sequencing. Typing of isolated O. oeni strains based on the mutation of the rpoB gene suggested a more favorable adaptation of L strains (n = 63) than H strains (n = 3) to MLF. Moreover, PFGE analysis of the isolated O. oeni strains revealed 27 different genetic profiles, which indicates a rich biodiversity of indigenous O. oeni species in the winery. Finally, a higher number of genetic markers were shown in the genome of strains from control wines than strains from wines elaborated with phenolic extracts. These results provide a basis for further investigation of the molecular and evolutionary mechanisms leading to the prevalence of O. oeni in wines treated with polyphenols as inhibitor compounds.     

Iron-catalyzed oxidation of arsenic(III) by oxygen and by hydrogen peroxide: pH-dependent formation of oxidants in the Fenton reaction

The oxidation kinetics of As(III) with natural and technical oxidants is still notwell understood, despite its importance in understanding the behavior of arsenic in the environment and in arsenic removal procedures. We have studied the oxidation of 6.6 microM As(II) by dissolved oxygen and hydrogen peroxide in the presence of Fe(II,III) at pH 3.5-7.5, on a time scale of hours. As(III) was not measurably oxidized by O2, 20-100 microM H2O2, dissolved Fe(III), or iron(III) (hydr)-oxides as single oxidants, respectively. In contrast, As(III) was partially or completely oxidized in parallel to the oxidation of 20-90 microM Fe(II) by oxygen and by 20 microM H2O2 in aerated solutions. Addition of 2-propanol as an *OH-radical scavenger quenched the As(III) oxidation at low pH but had little effect at neutral pH. High bicarbonate concentrations (100 mM) lead to increased oxidation of As-(III). On the basis of these results, a reaction scheme is proposed in which H2O2 and Fe(II) form *OH radicals at low pH but a different oxidant, possibly an Fe(IV) species, at higher pH. With bicarbonate present, carbonate radicals might also be produced. The oxidant formed at neutral pH oxidizes As(III) and Fe(II) but does not react competitively with 2-propanol. Kinetic modeling of all data simultaneously explains the results quantitatively and provides estimates for reaction rate constants. The observation that As(III) is oxidized in parallel to the oxidation of Fe(II) by O2 and by H2O2 and that the As(III) oxidation is not inhibited by *OH-radical scavengers at neutral pH is significant for the understanding of arsenic redox reactions in the environment and in arsenic removal processes as well as for the understanding of Fenton reactions in general.     

Vision Based UAV Attitude Estimation: Progress and Insights

Unmanned aerial vehicles (UAVs) are increasingly replacing manned systems in situations that are dangerous, remote, or difficult for manned aircraft to access. Its control tasks are empowered by computer vision technology. Visual sensors are robustly used for stabilization as primary or at least secondary sensors. Hence, UAV stabilization by attitude estimation from visual sensors is a very active research area. Vision based techniques are proving their effectiveness and robustness in handling this problem. In this work a comprehensive review of UAV vision based attitude estimation approaches is covered, starting from horizon based methods and passing by vanishing points, optical flow, and stereoscopic based techniques. A novel segmentation approach for UAV attitude estimation based on polarization is proposed. Our future insightes for attitude estimation from uncalibrated catadioptric sensors are also discussed.     

Adversarial example detection for DNN models: a review and experimental comparison

Deep learning (DL) has shown great success in many human-related tasks, which has led to its adoption in many computer vision based applications, such as security surveillance systems, autonomous vehicles and healthcare. Such safety-critical applications have to draw their path to success deployment once they have the capability to overcome safety-critical challenges. Among these challenges are the defense against or/and the detection of the adversarial examples (AEs). Adversaries can carefully craft small, often imperceptible, noise called perturbations to be added to the clean image to generate the AE. The aim of AE is to fool the DL model which makes it a potential risk for DL applications. Many test-time evasion attacks and countermeasures, i.e., defense or detection methods, are proposed in the literature. Moreover, few reviews and surveys were published and theoretically showed the taxonomy of the threats and the countermeasure methods with little focus in AE detection methods. In this paper, we focus on image classification task and attempt to provide a survey for detection methods of test-time evasion attacks on neural network classifiers. A detailed discussion for such methods is provided with experimental results for eight state-of-the-art detectors under different scenarios on four datasets. We also provide potential challenges and future perspectives for this research direction.

     

A Newton method for the resolution of steady stochastic Navier-Stokes equations

We present a Newton method to compute the stochastic solution of the steady incompressible Navier-Stokes equations with random data (boundary conditions, forcing term, fluid properties). The method assumes a spectral discretization at the stochastic level involving a orthogonal basis of random functionals (such as Polynomial Chaos or stochastic multi-wavelets bases). The Newton method uses the unsteady equations to derive a linear equation for the stochastic Newton increments. This linear equation is subsequently solved following a matrix-free strategy, where the iterations consist in performing integrations of the linearized unsteady Navier-Stokes equations, with an appropriate time scheme to allow for a decoupled integration of the stochastic modes. Various examples are provided to demonstrate the efficiency of the method in determining stochastic steady solution, even for regimes where it is likely unstable.