A new root-knot nematode, Meloidogyne moensi n. sp. (Nematoda : Meloidogynidae), parasitizing Robusta coffee from Western Highlands, Vietnam

A new root-knot nematode, parasitizing Robusta coffee in Dak Lak Province, Western Highlands of Vietnam, is described as Meloidogyne moensi n. sp. Morphological and molecular analyses demonstrated that this species differs clearly from other previously described root-knot nematodes. Morphologically, the new species is characterized by a swollen body of females with a small posterior protuberance that elongated from ovoid to saccate; perineal patterns with smooth striae, continuous and low dorsal arch; lateral lines marked as a faint space or linear depression at junction of the dorsal and ventral striate; distinct phasmids; perivulval region free of striae; visible and wide tail terminus surrounding by concentric circles of striae; medial lips of females in dumbbell-shaped and slightly raised above lateral lips; female stylet is normally straight with posteriorly sloping stylet knobs; lip region of second stage juvenile (J2) is not annulated; medial lips and labial disc of J2 formed dumbbell shape; lateral lips are large and triangular; tail of J2 is conoid with rounded unstriated tail tip; distinct phasmids and hyaline; dilated rectum. Meloidogyne moensi n. sp. is most similar to M. africana, M. ottersoni by prominent posterior protuberance. Results of molecular analysis of rDNA sequences including the D2-D3 expansion regions of 28S rDNA, COI, and partial COII/16S rRNA of mitochondrial DNA support for the new species status

Excitation properties of the divacancy in 4H-SiC

We investigate the quenching of the photoluminescence (PL) from the divacancy defect in 4H-SiC consisting of a nearest-neighbour silicon and carbon vacancies. The quenching occurs only when the PL is excited below certain photon energies (thresholds), which differ for the four different inequivalent divacancy configurations in 4H-SiC. Refined theoretical ab initio calculation for the charge-transfer levels of the divacancy show very good agreement between the position of the (0/-) level with respect to the conduction band for each divacancy configurations and the corresponding experimentally observed threshold, allowing us to associate the PL decay with conversion of the divacancy from neutral to negative charge state due to capture of electrons photoionized from other defects (traps) by the excitation. Electron paramagnetic resonance measurements are conducted in dark and under excitation similar to that used in the PL experiments and shed light on the possible origin of traps in the different samples. A simple model built on this concept agrees well with the experimentally-observed decay curves.Comment: 28 pages, 6 figure

Stability of singular jump-linear systems with a large state space : a two-time-scale approach

This paper considers singular systems that involve both continuous dynamics and discrete events with the coefficients being modulated by a continuous-time Markov chain. The underlying systems have two distinct characteristics. First, the systems are singular, that is, characterized by a singular coefficient matrix. Second, the Markov chain of the modulating force has a large state space. We focus on stability of such hybrid singular systems. To carry out the analysis, we use a two-time-scale formulation, which is based on the rationale that, in a large-scale system, not all components or subsystems change at the same speed. To highlight the different rates of variation, we introduce a small parameter ε>0. Under suitable conditions, the system has a limit. We then use a perturbed Lyapunov function argument to show that if the limit system is stable then so is the original system in a suitable sense for ε small enough. This result presents a perspective on reduction of complexity from a stability point of view

Data-driven structural health monitoring using feature fusion and hybrid deep learning

Smart structural health monitoring (SHM) for large-scale infrastructures is an intriguing subject for engineering communities thanks to its significant advantages such as timely damage detection, optimal maintenance strategy, and reduced resource requirement. Yet, it is a challenging topic as it requires handling a large amount of collected sensors data continuously, which is inevitably contaminated by random noises. Therefore, this study developed a practical end-to-end framework that makes use of physical features embedded in raw data and an elaborated hybrid deep learning model, namely 1DCNN-LSTM, featuring two algorithms - Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM). In order to extract relevant features from sensory data, the method combines various signal processing techniques such as the autoregressive model, discrete wavelet transform, and empirical mode decomposition. The hybrid deep learning 1DCNN-LSTM is designed based on the CNN’s capacity of capturing local information and the LSTM network’s prominent ability to learn long-term dependencies. Through three case studies involving both experimental and synthetic datasets, it is demonstrated that the proposed approach achieves highly accurate damage detection, as accurate as the powerful two-dimensional CNN, but with a lower time and memory complexity, making it suitable for real-time SHM

Heterologous expression of a recombinant lactobacillal -galactosidase in Lactobacillus plantarum: effect of different parameters on the sakacin P-based expression system

Background: Two overlapping genes lacL and lacM (lacLM) encoding for heterodimeric -galactosidase from Lactobacillus reuteri were previously cloned and over-expressed in the food-grade host strain Lactobacillus plantarum WCFS1, using the inducible lactobacillal pSIP expression system. In this study, we analyzed different factors that affect the production of recombinant L. reuteri -galactosidase. Results: Various factors related to the cultivation, i.e. culture pH, growth temperature, glucose concentration, as well as the induction conditions, including cell concentration at induction point and inducer concentration, were tested. Under optimal fermentation conditions, the maximum -galactosidase levels obtained were 130 U/mg protein and 3540 U/ml of fermentation broth corresponding to the formation of approximately 200 mg of recombinant protein per litre of fermentation medium. As calculated from the specific activity of the purified enzyme (190 U/mg), -galactosidase yield amounted to roughly 70% of the total soluble intracellular protein of the host organism. It was observed that pH and substrate (glucose) concentration are the most prominent factors affecting the production of recombinant -galactosidase. Conclusions: The over-expression of recombinant L. reuteri -galactosidase in a food-grade host strain was optimized, which is of interest for applications of this enzyme in the food industry. The results provide more detailed insight into these lactobacillal expression systems and confirm the potential of the pSIP system for efficient, tightly controlled expression of enzymes and proteins in lactobacilli.(VLID)90704

Resistance to experimental infections with Haemonchus contortus in Romanov sheep

International audienc

Multiple Sublineages of Influenza A Virus (H5N1), Vietnam, 2005−2007

Clade 2.3.4 viruses that are dominant in southern China have now spread to northern Vietnam

Quantum properties of dichroic silicon vacancies in silicon carbide

The controlled generation and manipulation of atom-like defects in solids has a wide range of applications in quantum technology. Although various defect centres have displayed promise as either quantum sensors, single photon emitters or light-matter interfaces, the search for an ideal defect with multi-functional ability remains open. In this spirit, we investigate here the optical and spin properties of the V1 defect centre, one of the silicon vacancy defects in the 4H polytype of silicon carbide (SiC). The V1 centre in 4H-SiC features two well-distinguishable sharp optical transitions and a unique S=3/2 electronic spin, which holds promise to implement a robust spin-photon interface. Here, we investigate the V1 defect at low temperatures using optical excitation and magnetic resonance techniques. The measurements, which are performed on ensemble, as well as on single centres, prove that this centre combines coherent optical emission, with up to 40% of the radiation emitted into the zero-phonon line (ZPL), a strong optical spin signal and long spin coherence time. These results single out the V1 defect in SiC as a promising system for spin-based quantum technologies

Morphological Filter Detector for Image Forensics Applications

Mathematical morphology provides a large set of powerful non-linear image operators, widely used for feature extraction, noise removal or image enhancement. Although morphological filters might be used to remove artifacts produced by image manipulations, both on binary and graylevel documents, little effort has been spent towards their forensic identification. In this paper we propose a non-trivial extension of a deterministic approach originally detecting erosion and dilation of binary images. The proposed approach operates on grayscale images and is robust to image compression and other typical attacks. When the image is attacked the method looses its deterministic nature and uses a properly trained SVM classifier, using the original detector as a feature extractor. Extensive tests demonstrate that the proposed method guarantees very high accuracy in filtering detection, providing 100% accuracy in discriminating the presence and the type of morphological filter in raw images of three different datasets. The achieved accuracy is also good after JPEG compression, equal or above 76.8% on all datasets for quality factors above 80. The proposed approach is also able to determine the adopted structuring element for moderate compression factors. Finally, it is robust against noise addition and it can distinguish morphological filter from other filters

Co-infection of human parvovirus B19 with Plasmodium falciparum contributes to malaria disease severity in Gabonese patients

Background: High seroprevalence of parvovirus B19 (B19V) coinfection with Plasmodium falciparum has been previously reported. However, the impact of B19V-infection on the clinical course of malaria is still elusive. In this study, we investigated the prevalence and clinical significance of B19V co-infection in Gabonese children with malaria. Methods: B19V prevalence was analyzed in serum samples of 197 Gabonese children with P. falciparum malaria and 85 healthy controls using polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and direct DNA-sequencing. Results: B19V was detected in 29/282 (10.28%) of Gabonese children. B19V was observed more frequently in P. falciparum malaria patients (14.21%) in comparison to healthy individuals (1.17%) (