Relationship between environmental and vegetational parameters for understory and open-area communities

Ten individuals from each of four tree species were selected, and their associated understory and adjacent open-area communities were sampled for both environmental and vegetational parameters, including light intensity, pH, litter depth, soil depth, and percentages of exposed rock, litter cover, living cover, shrubs, forbs, grasses, and annuals. The four tree species were ponderosa pine, Rocky Mountain juniper, Gambel oak, and snowbrush ceanothus. The study site was in the lower Uinta Mountains about 10 miles east of Kamas, Utah. Correlations among the various biotic and abiotic parameters were examined. The interplay of these factors in differentiating the understory and open-area communities is discussed.       

Toward interoperable bioscience data

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.     

On Selecting a Power Transformation in Time-Series Analysis

The primary aim of this paper is to select an appropriate power transformation when we use ARMA models for a given time series. We propose a Bayesian procedure for estimating the power transformation as well as other parameters in time series models. The posterior distributions of interest are obtained utilizing the Gibbs sampler, a Markov Chain Monte Carlo (MCMC) method. The proposed methodology is illustrated with two real data sets. The performance of the proposed procedure is compared with other competing procedures. © 1997 John Wiley & Sons, Ltd.     

Primary structure and expression of a product from cut, a locus involved in specifying sensory organ identity in Drosophila

In the absence of cut gene activity in Drosophila, external sensory organs are transformed into chordotonal organs. Here we show that the cut locus encodes a large protein containing a homoeodomain and is expressed in nuclei of cells in external sensory organs but not in cells within chordotonal organs.     

Ecological differences of C 3 and C 4 plant species from central Utah in habitats and mineral composition

Six study sites were established in each of three community life form types (grass, forb, and shrub) containing as dominants or subdominants either C 3 and/or C 4 plants. Soil and vegetation samples were analyzed for total nitrogen, phosphorus, magnesium, calcium, potassium, sodium, zinc, iron, copper, and manganese. Discriminant analysis and analysis of variance statistics were used to evaluate differences in mineral content of soils and plant tissues. C 4 plants in all study sites assimilated higher concentrations of potassium, iron, and calcium than did C 3 plants. Forbs in all sites contained the highest concentrations of minerals, followed by shrubs and grasses.     

军队服装订货和供应系统的计算机仿真

美军服装订货和供应系统采用传统的经济订货量法和分发中心供货。由于生产厂不能预测订货周期和数量，很难计划生产；而维护分发中心也增加了开销。讨论了现行系统模型，并提出一个新的系统方案。新方案采用正常，的固定的订货量，不但直接有利于生产厂安排生产，产能减少库存。     

Utilizing Statistical Semantic Similarity Techniques for Ontology Mapping——with Applications to AEC Standard Models

The objective of this paper is to introduce three semi-automated approaches for ontology mapping using relatedness analysis techniques. In the architecture, engineering, and construction (AEC) industry, there exist a number of ontological standards to describe the semantics of building models. Although the standards share similar scopes of interest, the task of comparing and mapping concepts among standards is challenging due to their differences in terminologies and perspectives. Ontology mapping is therefore necessary to achieve information interoperability, which allows two or more information sources to exchange data and to re-use the data for further purposes. The attribute-based approach, corpus-based approach, and name-based approach presented in this paper adopt the statistical relatedness analysis techniques to discover related concepts from heterogeneous ontologies. A pilot study is conducted on IFC and CIS/2 ontologies to evaluate the approaches. Preliminary results show that the attribute-based approach outperforms the other two approaches in terms of precision and F-measure.