Characterization of the Copy Number and Variants of Deformed Wing Virus (DWV) in the Pairs of Honey Bee Pupa and Infesting Varroa destructor or Tropilaelaps mercedesae

Recent honey bee colony losses, particularly during the winter, have been shown to be associated with the presence of both ectoparasitic mites and Deformed Wing Virus (DWV). Whilst the role of Varroa destructor mites as a viral vector is well established, the role of Tropilaelaps mercedesae mites in viral transmission has not been fully investigated. In this study, we tested the effects that V. destructor and T. mercedesae infestation have on fluctuation of the DWV copy number and alteration of the virus variants in honey bees by characterizing individual pupae and their infesting mites. We observed that both mite species were associated with increased viral copy number in honey bee pupae. We found a positive correlation between DWV copy number in pupae and copy number in infesting mites, and the same DWV type A variant was present in either low or high copy number in both honey bee pupae and infesting V. destructor. These data also suggest that variant diversity is similar between honey bee pupae and the mites that infest them. These results support a previously proposed hypothesis that DWV suppresses the honey bee immune system when virus copy number reaches a specific threshold, promoting greater replication

Phoneme-based speech recognition using self-organizing map.

Automatic speech recognition by machine is a challenging task for man-machine communications. Because speech waveform is nonlinear and variant, a speech recognition algorithm requires much intelligence and an ability to accommodate variations. In this thesis, a hybrid speech recognizer based on self-organizing map (SOM) and fuzzy neural network (FNN) is proposed. The SOM is used to obtain the optimal phoneme response patterns of speech signal by Viterbi search algorithm and the FNN is applied for the recognition matching of these 2D speech response patterns on the SOM to fulfill the speech recognition tasks. Experiment results show that this hybrid speech recognizer is a feasible approach and could provide meaningful recognition results for dependent speech recognition. This thesis also compares this hybrid speech recognizer with the Hidden Markov Model, analyzes two types of misclassification for independent speech recognition and provides some suggestions for future research.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .D67. Source: Masters Abstracts International, Volume: 42-01, page: 0294. Adviser: M. K. Kwan. Thesis (M.A.Sc.)--University of Windsor (Canada), 2003

A Weil-Petersson Type Metric on the Space of Fano Kaehler-Ricci Solitons

In this paper we define a Weil-Petersson type metric on the space of shrinking Kaehler-Ricci solitons and prove a necessary and sufficient condition on when it is independent of the choices of Kaehler-Ricci soliton metrics. We also show that the Weil-Petersson metric is Kaehler when it defines a metric on the Kuranishi space of small deformations of Fano Kaehler-Ricci solitons. Finally, we establish the first and second order deformation of Fano K\"ahler-Ricci solitons and show that, essentially, the first effective term in deforming Kaehler-Ricci solitons leads to the Weil-Petersson metric.Comment: 16 pages; final version available at the journal cite of JGEA (see the journal reference info below

Unstructured Mixed Grid and SIMPLE Algorithm based Model for 2D-SWE

AbstractA 2D depth-averaged flow model was developed using implicit schemes on unstructured mixed grid. The implicit time-marching algorithm is adopted to make the model much stable. To suppress the numerical oscillation, the TVD (total-variation diminishing) based second-order convection scheme is employed in the framework of finite volume method. The new model is validated using measured data and compared with YGLai model (newly developed by Lai (2010)). Results show that the new model is consistent with the measured data fairly well. The comparison with YGLai model indicates that our new model is generally better with respect to accuracy

Molecular ecological characterization of a honey bee ectoparasitic mite, Tropilaelaps mercedesae.

Tropilaelaps mercedesae (small mite) is one of two major honey bee ectoparasitic mite species responsible for the colony losses of Apis mellifera in Asia. Although T. mercedesae mites are still restricted in Asia (except Japan), they may diffuse all over the world due to the ever-increasing global trade of live honey bees (ex. Varroa destructor). Understanding the ecological characteristics of T. mercedesae at molecular level could potentially result in improving the management and control programs. However, molecular and genomic characterization of T. mercedesae remains poorly studied, and even no genes have been deposited in Genbank to date. Therefore, I conducted T. mercedesae genome and transcriptome sequencing. By comparing T. mercedesae genome with other arthropods, I have gained new insights into evolution of Parasitiformes and the evolutionary changes associated with specific habitats and life history of honey bee ectoparasitic mite that could potentially improve the control programs of T. mercedesae. Finally, characterization of T. mercedesae transient receptor potential channel, subfamily A, member 1 (TmTRPA1) would also help us to develop a novel control method for T. mercedesae

Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild

In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild. In particular, we focus on four popular obfuscation approaches: identifier renaming, string encryption, Java reflection, and packing. To obtain the meaningful statistical results, we designed efficient and lightweight detection models for each obfuscation technique and applied them to our massive APK datasets (collected from Google Play, multiple third-party markets, and malware databases). We have learned several interesting facts from the result. For example, malware authors use string encryption more frequently, and more apps on third-party markets than Google Play are packed. We are also interested in the explanation of each finding. Therefore we carry out in-depth code analysis on some Android apps after sampling. We believe our study will help developers select the most suitable obfuscation approach, and in the meantime help researchers improve code analysis systems in the right direction