Screening and characterization of pathogenic fungi for possible control of Coptotermes formosanus

Coptotermes formosanus was used as “bait” to isolate pathogenic fungi from soil. Fifteen pathogenic fungal isolates were obtained, all either Metarhizium anisopliae (six isolates) or Beauveria bassiana (nine isolates). There were no differences in numbers of fungal isolates from the three sampling locations. However, significantly more isolates were found in woodlands (eleven) than in pastures (four). Median lethal doses (LD50s) of these fungal species to C. formosanus were interspersed, indicating that fungal isolates rather than species had the greatest effect on virulence. In vitro growth characteristics were significantly correlated with virulence against termites, suggesting that fungal virulence might be predicted in vitro rather than by bioassay. Conidial production on termite cadavers increased significantly over 11 days post-death. Effects of isolates of M. anisopliae and B. bassiana on in vivo sporulation were significant. B. bassiana isolates could be categorized into a group with high total sporulation (day 11) and low quick sporulation (on days 2 and 3), while M. anisopliae isolates fell into another group with high quick sporulation and low total sporulation. Conidial production was significantly higher in vitro than in vivo. Correlation between in vivo and in vitro conidial production was positive and significant. This may allow preliminary in vitro screening of a large number of isolates for high in vivo sporulation. Fungal species and isolate significantly affected disease prevalence in termite populations. Sporulation of M. anisopliae played a more important role than virulence in producing epizootics in termites, but this was not the case for B. bassiana. Isolates characterized by quick sporulation (day 2 after death) did not produce better epizootics in termites than those with high total sporulation (day 11 after death) in either fungal species. An isolate of M. anisopliae ranked highly in all three categories (virulence, quick sporulation, total sporulation) produced better epizootics than an isolate that was inferior in all three characteristics. High temperature (35ºC) significantly reduced fungal germination rates, leading to significant reduction of epizootics. Thus, fungal characteristics other than virulence must be taken into account for the seasonal colonization approach to termite microbial control

Efficient Subgraph Matching on Billion Node Graphs

The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query processing. Typically, most indices require either super-linear indexing time or super-linear indexing space. Unfortunately, for very large graphs, super-linear approaches are almost always infeasible. In this paper, we study the problem of subgraph matching on billion-node graphs. We present a novel algorithm that supports efficient subgraph matching for graphs deployed on a distributed memory store. Instead of relying on super-linear indices, we use efficient graph exploration and massive parallel computing for query processing. Our experimental results demonstrate the feasibility of performing subgraph matching on web-scale graph data.Comment: VLDB201

Reverse Nearest Neighbor Heat Maps: A Tool for Influence Exploration

We study the problem of constructing a reverse nearest neighbor (RNN) heat map by finding the RNN set of every point in a two-dimensional space. Based on the RNN set of a point, we obtain a quantitative influence (i.e., heat) for the point. The heat map provides a global view on the influence distribution in the space, and hence supports exploratory analyses in many applications such as marketing and resource management. To construct such a heat map, we first reduce it to a problem called Region Coloring (RC), which divides the space into disjoint regions within which all the points have the same RNN set. We then propose a novel algorithm named CREST that efficiently solves the RC problem by labeling each region with the heat value of its containing points. In CREST, we propose innovative techniques to avoid processing expensive RNN queries and greatly reduce the number of region labeling operations. We perform detailed analyses on the complexity of CREST and lower bounds of the RC problem, and prove that CREST is asymptotically optimal in the worst case. Extensive experiments with both real and synthetic data sets demonstrate that CREST outperforms alternative algorithms by several orders of magnitude.Comment: Accepted to appear in ICDE 201

Long term water integration in interconnected ramets of stoloniferous grass, buffalograss

Buffalograss (Buchloë dactyloides) is known for its drought resistant character. Natural resources are patchily distributed and resource sharing between interconnected ramets can enhance the performance of the whole genet. In order to examine whether there exists long term water integration between interconnected ramets of buffalograss, a greenhouse experiment was conducted. Interconnected ramet pairs of stoloniferous buffalograss were planted in two partitioned similar-sized containers and subjected to homogeneous (20 ml pot-1 d-1 or 100 - 150 ml pot-1 d-1) or heterogeneous (20 ml pot-1 d-1 vs. 100-150 ml pot-1 d-1) water supply; the whole experiment lasted for 91 days. In heterogeneous treatment, water translocation was equally effective in acropetal and basipetal directions. Elder ramet was more efficient in water use, but rooted ramet of elder ramet in moist condition experienced significant cost when it was connected to younger ramet in dry condition; whereas, no cost was found in any fragment of younger donor ramet. Ramet in dry condition produced more biomass than its connected ramet in moist condition and developed larger leaves. This “oversharing” phenomenon indicated that no net cost was involved in water integration, and water might not be the only resources transported within stolon xylem. Overall, long term water integration is an important strategy for buffalograss to cope with adverse natural drought conditions.Keywords: Water integration, interconnected ramets, heterogeneous treatment, Buchloë dactyloides, oversharingAfrican Journal of Biotechnology Vol. 9(34), pp. 5503-5510, 23 August, 201

Assessment of multi-air emissions: case of particulate matter (dust), SO2, NOx and CO2 from iron and steel industry of China

Industrial activities are generally energy and air emissions intensive, requiring bulky inputs of raw materials and fossil fuels and emitting huge waste gases including particulate matter (PM, or dust), sulphur dioxide (SO2), nitrogen oxides (NOx), carbon dioxide (CO2), and other substances, which are severely damaging the environment. Many studies have been carried out on the quantification of the concentrations of these air emissions. Although there are studies published on the co-effect of multi-air emissions, a more fair and comprehensive method for assessing the environmental impact of multi-air emissions is still lacking, which can simultaneously consider the flow rate of waste gases, the availability of emitting sources and the concentrations of all emission substances. In this work, a Total Environmental Impact Score (TEIS) approach is proposed to assess the environmental impact of the main industrial processes of an integrated iron and steel site located in the northeast of China. Besides the concentration of each air emission substance, this TEIS approach also combines the flow rate of waste gases and the availability of emitting sources. It is shown that the processes in descending order by the values of TEIS are sintering, ironmaking, steelmaking, thermal power, steel rolling, and coking, with the values of 17.57, 16.68, 10.86, 10.43, 9.60 and 9.27, respectively. In addition, a sensitivity analysis was conducted, indicating that the TEIS order is almost the same with the variation of 10% in the permissible CO2 concentration limit and the weight of each air emission substance. The effects of emitting source availability and waste gas flow rate on the TEIS cannot be neglected in the environmental impact assessment

MALA: Cross-Domain Dialogue Generation with Action Learning

Response generation for task-oriented dialogues involves two basic components: dialogue planning and surface realization. These two components, however, have a discrepancy in their objectives, i.e., task completion and language quality. To deal with such discrepancy, conditioned response generation has been introduced where the generation process is factorized into action decision and language generation via explicit action representations. To obtain action representations, recent studies learn latent actions in an unsupervised manner based on the utterance lexical similarity. Such an action learning approach is prone to diversities of language surfaces, which may impinge task completion and language quality. To address this issue, we propose multi-stage adaptive latent action learning (MALA) that learns semantic latent actions by distinguishing the effects of utterances on dialogue progress. We model the utterance effect using the transition of dialogue states caused by the utterance and develop a semantic similarity measurement that estimates whether utterances have similar effects. For learning semantic actions on domains without dialogue states, MsALA extends the semantic similarity measurement across domains progressively, i.e., from aligning shared actions to learning domain-specific actions. Experiments using multi-domain datasets, SMD and MultiWOZ, show that our proposed model achieves consistent improvements over the baselines models in terms of both task completion and language quality.Comment: 9 pages, 3 figure

Material and energy flows of the iron and steel industry: status quo, challenges and perspectives

Integrated analysis and optimization of material and energy flows in the iron and steel industry have drawn considerable interest from steelmakers, energy engineers, policymakers, financial firms, and academic researchers. Numerous publications in this area have identified their great potential to bring significant benefits and innovation. Although much technical work has been done to analyze and optimize material and energy flows, there is a lack of overview of material and energy flows of the iron and steel industry. To fill this gap, this work first provides an overview of different steel production routes. Next, the modelling, scheduling and interrelation regarding material and energy flows in the iron and steel industry are presented by thoroughly reviewing the existing literature. This study selects eighty publications on the material and energy flows of steelworks, from which a map of the potential of integrating material and energy flows for iron and steel sites is constructed. The paper discusses the challenges to be overcome and the future directions of material and energy flow research in the iron and steel industry, including the fundamental understandings of flow mechanisms, the dynamic material and energy flow scheduling and optimization, the synergy between material and energy flows, flexible production processes and flexible energy systems, smart steel manufacturing and smart energy systems, and revolutionary steelmaking routes and technologies