Identification of Vibrio Anguillarum and Vibrio Ordalii by a Monoclonal Antibody Coagglutination Assay.

Vibrio anguillarum exhibits species-specific antigens on the protein core of the polar flagellum (H) and H-determinants which are expressed by heterologous Vibrio species. Monoclonal antibody (MAb) which reacted with flagella core protein by ELISA were affinity purified from protein A-sepharose. Staphylococcus aureus Cowan 1 cells armed with anti-H MAb coagglutinated each of the 10 V. anguillarum O-antigen serovars within 1 to 2 minutes, as well as V. ordalii isolates. These findings suggest these two vibrios express similar if not identical species-specific H-determinants. The anti-H reagent did not coagglutinate 20 heterologous Vibrio species. MAb generated against LPS, extracted from V. anguillarum serovar 01, 02 and 03, were tested for serovar-specificity by ELISA and direct slide agglutination. Anti-02 serovar-specific MAb fixed to S. aureus cells detect the 02 serovar in enrichment culture fluid 6 hours after the broth was seeded with kidney, liver, spleen and blood from diseased fish. Utilization of the anti-O serovar specific MAb coagglutination assay is rapid and applicable to the identification of V. anguillarum from diseased fish. Anti-H can be used to detect potential environmental pathogenic strains which are nontypable with available anti-O sera

Teaching Chinese through integrating songs in Task-based learning : a teacher action research project

This research focuses on the exploration of integrating songs in the Task-based Language Teaching (TBLT) approach to enhance the learnability of Chinese. The aim of this study is to develop a series of effective curriculum resources, including songs and tasks and a novel framework combining songs and tasks in language teaching. This research is also designed as an action research to improve the teacher-researcher proficiency of the researcher with his teaching experience in Pianpi High School. In this study, different types of songs were experimented with and different tasks were utilized to allow the language to be used in life-like contexts. Finally, an adjusted framework of TBLT, including the Pre-task phase, Song phase, Core task phase and Post-task phase, is developed to combine songs and tasks, and to move the learning of songs to a higher plane of practice and application

Choosing rhotacization site in Beijing Mandarin: The role of perceptual similarity

The principle of faithfulness, proposed in the Optimality Theoretic framework of phonology, has traditionally been based on binary distinctive features and discrete sound correspondences within an input–output pair. The subsequent proposal of the P-map hasinspired a different approach to faithfulness—one that allows phonological grammars to evaluate faithfulness directly using the phonetic distance between different continuous speech streams, maximally preserving the subtle phonetic difference among output candidates. This paper presents a study that aims to determine whether the distance-based approach to faithfulness can better account for gradient alternation patterns than the traditional feature-based approach can. The phenomenon this study examines is rime rhotacization in Beijing Mandarin. Results of an experiment where participants were asked to choose which rime to rhotacize in nonce disyllables reveal that speakers choose to rhotacize the rime which yields the more faithful output. The results were modeled with mixed-effects logistic regression. One model incorporated feature-based faithfulness constraints and the other distance-based ones. The models confirmed that the faithfulness of rhotacization candidates is the main deciding factor. However, two independent model comparison measures yielded contradictory results regarding which model performed better, leaving an inclusion in regard to whether distance-based faithfulness is more capable than feature-based faithfulness

Surface Networks

We study data-driven representations for three-dimensional triangle meshes, which are one of the prevalent objects used to represent 3D geometry. Recent works have developed models that exploit the intrinsic geometry of manifolds and graphs, namely the Graph Neural Networks (GNNs) and its spectral variants, which learn from the local metric tensor via the Laplacian operator. Despite offering excellent sample complexity and built-in invariances, intrinsic geometry alone is invariant to isometric deformations, making it unsuitable for many applications. To overcome this limitation, we propose several upgrades to GNNs to leverage extrinsic differential geometry properties of three-dimensional surfaces, increasing its modeling power. In particular, we propose to exploit the Dirac operator, whose spectrum detects principal curvature directions --- this is in stark contrast with the classical Laplace operator, which directly measures mean curvature. We coin the resulting models \emph{Surface Networks (SN)}. We prove that these models define shape representations that are stable to deformation and to discretization, and we demonstrate the efficiency and versatility of SNs on two challenging tasks: temporal prediction of mesh deformations under non-linear dynamics and generative models using a variational autoencoder framework with encoders/decoders given by SNs

Robust policy iteration for continuous-time stochastic H∞H_\infty control problem with unknown dynamics

In this article, we study a continuous-time stochastic $H_\infty$ control problem based on reinforcement learning (RL) techniques that can be viewed as solving a stochastic linear-quadratic two-person zero-sum differential game (LQZSG). First, we propose an RL algorithm that can iteratively solve stochastic game algebraic Riccati equation based on collected state and control data when all dynamic system information is unknown. In addition, the algorithm only needs to collect data once during the iteration process. Then, we discuss the robustness and convergence of the inner and outer loops of the policy iteration algorithm, respectively, and show that when the error of each iteration is within a certain range, the algorithm can converge to a small neighborhood of the saddle point of the stochastic LQZSG problem. Finally, we applied the proposed RL algorithm to two simulation examples to verify the effectiveness of the algorithm

Potential of Trap Crops for Integrated Management of the Tropical Armyworm, Spodoptera litura in Tobacco

The tropical armyworm, Spodoptera litura (F.) (Lepidoptera: Noctuidae), is an important pest of tobacco, Nicotiana tabacum L. (Solanales: Solanaceae), in South China that is becoming increasingly resistant to pesticides. Six potential trap crops were evaluated to control S. litura on tobacco. Castor bean, Ricinus communis L. (Malpighiales: Euphorbiaceae), and taro, Colocasia esculenta (L.) Schott (Alismatales: Araceae), hosted significantly more S. litura than peanut, Arachis hypogaea L. (Fabales: Fabaceae), sweet potato, Ipomoea batata Lam. (Solanales: Convolvulaceae) or tobacoo in a greenhouse trial, and tobacco field plots with taro rows hosted significantly fewer S. litura than those with rows of other trap crops or without trap crops, provided the taro was in a fast-growing stage. When these crops were grown along with eggplant, Solanum melongena L. (Solanales: Solanaceae), and soybean, Glycines max L. (Fabales: Fabaceae), in separate plots in a randomized matrix, tobacco plots hosted more S. litura than the other crop plots early in the season, but late in the season, taro plots hosted significantly more S. litura than tobacco, soybean, sweet potato, peanut or eggplant plots. In addition, higher rates of S. litura parasitism by Microplitis prodeniae Rao and Chandry (Hymenoptera: Bracondidae) and Campoletis chlorideae Uchida (Ichnumonidae) were observed in taro plots compared to other crop plots. Although taro was an effective trap crop for managing S. litura on tobacco, it did not attract S. litura in the seedling stage, indicating that taro should either be planted 20–30 days before tobacco, or alternative control methods should be employed during the seedling stage

Increased ventilation of Antarctic deep water during the warm mid-Pliocene

The mid-Pliocene warm period is a recent warm geological period that shares similarities with predictions of future climate. It is generally held the mid-Pliocene Atlantic Meridional Overturning Circulation must have been stronger, to explain a weak Atlantic meridional δ13C gradient and large northern high-latitude warming. However, climate models do not simulate such stronger Atlantic Meridional Overturning Circulation, when forced with mid-Pliocene boundary conditions. Proxy reconstructions allow for an alternative scenario that the weak δ13C gradient can be explained by increased ventilation and reduced stratification in the Southern Ocean. Here this alternative scenario is supported by simulations with the Norwegian Earth System Model (NorESM-L), which simulate an intensified and slightly poleward shifted wind field off Antarctica, giving enhanced ventilation and reduced stratification in the Southern Ocean. Our findings challenge the prevailing theory and show how increased Southern Ocean ventilation can reconcile existing model-data discrepancies about Atlantic Meridional Overturning Circulation while explaining fundamental ocean features.publishedVersio