A Primal-Dual Proximal Algorithm for Sparse Template-Based Adaptive Filtering: Application to Seismic Multiple Removal

Unveiling meaningful geophysical information from seismic data requires to deal with both random and structured "noises". As their amplitude may be greater than signals of interest (primaries), additional prior information is especially important in performing efficient signal separation. We address here the problem of multiple reflections, caused by wave-field bouncing between layers. Since only approximate models of these phenomena are available, we propose a flexible framework for time-varying adaptive filtering of seismic signals, using sparse representations, based on inaccurate templates. We recast the joint estimation of adaptive filters and primaries in a new convex variational formulation. This approach allows us to incorporate plausible knowledge about noise statistics, data sparsity and slow filter variation in parsimony-promoting wavelet frames. The designed primal-dual algorithm solves a constrained minimization problem that alleviates standard regularization issues in finding hyperparameters. The approach demonstrates significantly good performance in low signal-to-noise ratio conditions, both for simulated and real field seismic data

A constrained-based optimization approach for seismic data recovery problems

Random and structured noise both affect seismic data, hiding the reflections of interest (primaries) that carry meaningful geophysical interpretation. When the structured noise is composed of multiple reflections, its adaptive cancellation is obtained through time-varying filtering, compensating inaccuracies in given approximate templates. The under-determined problem can then be formulated as a convex optimization one, providing estimates of both filters and primaries. Within this framework, the criterion to be minimized mainly consists of two parts: a data fidelity term and hard constraints modeling a priori information. This formulation may avoid, or at least facilitate, some parameter determination tasks, usually difficult to perform in inverse problems. Not only classical constraints, such as sparsity, are considered here, but also constraints expressed through hyperplanes, onto which the projection is easy to compute. The latter constraints lead to improved performance by further constraining the space of geophysically sound solutions.Comment: International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014); Special session "Seismic Signal Processing

A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth \ell_1/\ell_2 regularization term. As the mean of the noise in the power spectrum domain is dependent on its variance in the time domain, the proposed method includes a variance estimation step, which allows more robust blind deconvolution. Validation of the method on both simulated and real data, and of its performance, are compared with two well-known methods from the literature: the deconvolution approach for the mapping of acoustic sources, and sound density modeling

Euclid in a Taxicab: Sparse Blind Deconvolution with Smoothed l1/l2 Regularization

The l1/l2 ratio regularization function has shown good performance for retrieving sparse signals in a number of recent works, in the context of blind deconvolution. Indeed, it benefits from a scale invariance property much desirable in the blind context. However, the l1/l2 function raises some difficulties when solving the nonconvex and nonsmooth minimization problems resulting from the use of such a penalty term in current restoration methods. In this paper, we propose a new penalty based on a smooth approximation to the l1/l2 function. In addition, we develop a proximal-based algorithm to solve variational problems involving this function and we derive theoretical convergence results. We demonstrate the effectiveness of our method through a comparison with a recent alternating optimization strategy dealing with the exact l1/l2 term, on an application to seismic data blind deconvolution.Comment: 5 page

Filtrage de multiples sismiques par ondelettes et optimisation convexe

National audienceNous considérons le problème de filtrage adaptatif de données sismiques composées : de signaux d'intérêts ("primaires"), de perturbations structurées correspondant à des propagations d'ondes présentant des réflexions multiples ("multiples") et de bruit aléatoire. Ces signaux parasites, très énergétiques, peuvent dissimuler les réflexions primaires intéressantes, correspondant aux interfaces entre couches du sous-sol. Elles peuvent être filtrées à partir de modèles approchés qu'il faut adapter en délai, amplitude et fréquence. Ce travail permet de contraindre cette adaptation, sous forme de combinaisons de filtres glissants à réponses impulsionnelles finies, à varier lentement en fonction de la profondeur, respectant les variations géologiques attendues. Les approches antérieures pour ce problème, très important en sismique réflexion, ne semblent pas prendre en compte de contraintes sur l'adaptation, et peuvent produire des filtres très mal conditionnés, du fait notamment du caractère passe-bande des données sismiques. Cette formulation du problème permet par ailleurs d'introduire, et de résoudre par optimisation convexe, des a priori de parcimonie des signaux dans des trames d'ondelettes ainsi que de prendre en compte un bruit additif gaussien. Les multiples sont très bien estimés. La restauration des primaires réalisée permet au géophysicien de voir émerger des résidus de signal utile, même en présence de bruit fort

1 A Primal-Dual Proximal Algorithm for Sparse Template-Based Adaptive Filtering: Application to Seismic Multiple Removal

Abstract—Unveiling meaningful geophysical information from seismic data requires to deal with both random and structured “noises”. As their amplitude may be greater than signals of interest (primaries), additional prior information is especially important in performing efficient signal separation. We address here the problem of multiple reflections, caused by wave-field bouncing between layers. Since only approximate models of these phenomena are available, we propose a flexible framework for time-varying adaptive filtering of seismic signals, using sparse representations, based on inaccurate templates. We recast the joint estimation of adaptive filters and primaries in a new convex variational formulation. This approach allows us to incorporate plausible knowledge about noise statistics, data sparsity and slow filter variation in parsimony-promoting wavelet frames. The designed primal-dual algorithm solves a constrained minimization problem that alleviates standard regularization issues in finding hyperparameters. The approach demonstrates significantly good performance in low signal-to-noise ratio conditions, both for simulated and real field seismic data. Index Terms—Convex optimization, Parallel algorithms, Wavelet transforms, Adaptive filters, Geophysical signal processing, Signal restoration, Sparsity, Signal separation

Effect of Element Addition and Heat Treatment Process on the Properties of High Manganese Steel

The changing of properties of HMnS by alloy elements addition and heat treatment was presented. Studying about the hardness of HMnS were increased when the Mn contents increased. On the other hand, the Cr content has effective on the hardness and microstructure of this steel also, but with the Cr content was increased from 2% to 2,5%, the hardness of high Manganese steel was not much changed. With the research about HMnS, it was added the Cr and applied the advanced heat treatment process, the microstructure of this steel was formed the chrome carbide particles with grain fine which dispersed in the matrix with the formation of these dispersed carbide particles will contribute to increasing the alloy's abrasion resistance. With the difference in heat treatment processes, the microstructure and hardness were also changed. When the sample was heat-treated according to the model heat treating; the particle size of the sample is also significantly reduced. This explains why the hardness value of the sample increases significantly. Also, under the impact load, on the surface layer of this steel, the microstructure does not appear the martensite structure form but only see the twinning on the surface. These are new findings on the mechanism transformation of high manganese austenite steel when working under the impact of the impact force. The mechanism of transformation is quite different from the previous view of phase transformation under the impact force of high manganese austenitic steel

Isolation, screening antimicrobial activity and identification of fungi from marine sediments of the area Thanh Lan, Co To, Vietnam

Marine environment is rich in natural product resources, including marine microorganisms, especially fungi which are not only seen as a potential source of highly applicable bioactive substances but also can provide for science new chemical structures. The objective of this study is to isolate and screen fungal strains with antibacterial activity from the marine environment. Twenty five strains of fungi were isolated from marine sediments of Thanh Lan, Co To island and assessed on antibiotic activity against 7 tested microbial strains, including three Gram-negative bacteria (Escherichia coli ATCC25922, Pseudomonas aeruginosa ATCC27853, Salmonella enterica ATCC13076), three Gram-positive bacteria (Enterococcus faecalis ATCC29212, Stapphylococus aureus ATCC25923, Bacillus cereus ATCC 13245), and the yeast Candida albicans ATCC10231. The minimum inhibitory concentration (MIC) against the tested microorganisms was determined for the crude extracts obtained from the culture broths after ethyl acetate extraction and vacuum rotary evaporation. Three strains with the highest antimicrobial activity M26, M30 and M45 were capable of inhibiting 4 - 5 of the 7 tested microorganisms with MIC values from 64 to 256 μg/ml, depending on each tested strain. Morphological and phylogenetic investigations based on 18S rRNA gene sequences of the three selected strains showed that strains M26 and M30 belonged to the genus Penicillium, whereas strain M45 belonged to the genus Neurospora. The sequences of 18S rRNA gene of three strains M26, M30 and M45 were registered on GenBank database with accession numbers: MH673730, MH673731, MH673732, respectively. Research results showed that marine environment has a great potential in isolation of fungal strains for the search for antibacterial substances as well as other biologically active compounds

IDENTIFICATION AND ANTIMICROBIAL ACTIVITY OF ACTINOMYCETES STRAINS ISOLATED FROM SAMPLES COLLECTED IN THE COASTAL AREA OF HUE, DA NANG AND QUANG NAM PROVINCES, VIETNAM

Microorganisms are of particular interest because of their ability to synthesize high-value secondary compounds and provide us with novel and diverse chemical structures. The most common source of antibiotics is Actinomycetes which provide around two-third of naturally occurring antibiotics, including many of medical importance. In this study, 81 strains of actinomycetes were isolated from 145 samples including: sediments, sponges, soft corals, echinoderms and starfish collected from three sea areas of Vietnam: Hue, Da Nang and Quang Nam. The strains were fermented in A+ medium and fermentation broths were extracted 5 times with ethyl acetate. The extracts were evaporated under reduced  pressure to yield crude extracts. Quantitative assay was used to determine MIC (Minimum inhibitory concentration) of extract against 7 reference strains. From the results of screening, Seven strains of actinomycetes that have the highest biological activity (Code: G244, G246, G261, G266, G278, G280 and G290) were chosen to be identified by morphological and phylogenetic based on 16S rRNA gene sequences. The results showed that 6 strains G246, G261, G266, G278, G280 and G290 belonged to the genus Streptomyces; and the strain G244 belonged to the genus Micromonospora. In particular, strains G244, G278, G280 were resistant 5/7 strains of microorganisms test, with values  MICs from 2 µg/mL to 256 µg/mL; and three strains G261, G266, G290 showed the inhibitory effect towards 4/7 strains of microorganisms test, with respective values MICs from 2 µg/mL to 256 µg/mL. Moreover, six of the seven selected strains were highly resistant to yeast Candida albicans ATCC10231 with MIC values from 2 µg/mL to 256 µg/mL. These results indicated that marine Actinomycetes in Vietnam are also a potential source to find bioactive substances

Secondary metabolites from Micromonospora ectrinospora G017

Eight  compounds, cyclo-(Pro-Tryp) (1), N-[2-(1H-indol-3-yl)-2-oxo-ethyl] acetamide (2), cyclo-(Pro-Tyr) (3), cyclo-(Pro-Phe) (4), cyclo-trans-4-OH-(Pro-Phe) (5), cyclo-(Pro-Leu) (6), cyclo-(Pro-Val) (7), and  uracil (8) were isolated from the culture broth of the marine Micromonospora ectrinospora G017 strain. The structures of the isolated compounds were established on the basis of their spectral data, including mass spectrometry and NMR