Shallow-water benthic habitats of St. John, U.S. Virgin Islands

Coral reef ecosystems of the Virgin Islands Coral Reef National Monument, Virgin Islands National Park and the surrounding waters of St. John, U.S. Virgin Islands are a precious natural resource worthy of special protection and conservation. The mosaic of habitats including coral reefs, seagrasses and mangroves, are home to a diversity of marine organisms. These benthic habitats and their associated inhabitants provide many important ecosystem services to the community of St. John, such as fishing, tourism and shoreline protection. However, coral reef ecosystems throughout the U.S. Caribbean are under increasing pressure from environmental and anthropogenic stressors that threaten to destroy the natural heritage of these marine habitats. Mapping of benthic habitats is an integral component of any effective ecosystem-based management approach. Through the implementation of a multi-year interagency agreement, NOAA’s Center for Coastal Monitoring and Assessment - Biogeography Branch and the U.S. National Park Service (NPS) have completed benthic habitat mapping, field validation and accuracy assessment of maps for the nearshore marine environment of St. John. This work is an expansion of ongoing mapping and monitoring efforts conducted by NOAA and NPS in the U.S. Caribbean and replaces previous NOAA maps generated by Kendall et al. (2001) for the waters around St. John. The use of standardized protocols enables the condition of the coral reef ecosystems around St. John to be evaluated in context to the rest of the Virgin Island Territories and other U.S. coral ecosystems. The products from this effort provide an accurate assessment of the abundance and distribution of marine habitats surrounding St. John to support more effective management and conservation of ocean resources within the National Park system. This report documents the entire process of benthic habitat mapping in St. John. Chapter 1 provides a description of the benthic habitat classification scheme used to categorize the different habitats existing in the nearshore environment. Chapter 2 describes the steps required to create a benthic habitat map from visual interpretation of remotely sensed imagery. Chapter 3 details the process of accuracy assessment and reports on the thematic accuracy of the final maps. Finally, Chapter 4 is a summary of the basic map content and compares the new maps to a previous NOAA effort. Benthic habitat maps of the nearshore marine environment of St. John, U.S. Virgin Islands were created by visual interpretation of remotely sensed imagery. Overhead imagery, including color orthophotography and IKONOS satellite imagery, proved to be an excellent source from which to visually interpret the location, extent and attributes of marine habitats. NOAA scientists were able to accurately and reliably delineate the boundaries of features on digital imagery using a Geographic Information System (GIS) and fi eld investigations. The St. John habitat classification scheme defined benthic communities on the basis of four primary coral reef ecosystem attributes: 1) broad geographic zone, 2) geomorphological structure type, 3) dominant biological cover, and 4) degree of live coral cover. Every feature in the benthic habitat map was assigned a designation at each level of the scheme. The ability to apply any component of this scheme was dependent on being able to identify and delineate a given feature in remotely sensed imagery.

Moderate-depth benthic habitats of St. John, U.S. Virgin Islands

The National Oceanic and Atmospheric Administration’s (NOAA) Center for Coastal Monitoring and Assessment’s (CCMA) Biogeography Branch and the U.S. National Park Service (NPS) have completed mapping the moderate-depth marine environment south of St. John. This work is an expansion of ongoing mapping and monitoring efforts conducted by NOAA and NPS in the U.S. Caribbean. The standardized protocols used in this effort will enable scientists and managers to quantitatively compare moderate-depth coral reef ecosystems around St. John to those throughout the U.S. Territories. These protocols and products will also help support the effective management and conservation of the marine resources within the National Park system.

中鲤亚属的分支系统学分析

基于外部形态特征和内部骨骼特征对鲤科鲤属中鲤亚属进行了分支系统学分析。内群包括中鲤亚属的全部5种和鲤亚属的2种鱼类，外群采用乌原鲤。在鲤属鱼类和外群间共有48个性状存在变化。系统发育分析采用PAUP~(*)软件的Parsimony和Bootstrap两种方式的Branch-and-Bound算法。排除不能极化的特征和特有离征之后，还有28个特征可用，由这28个特征可得到唯一的系统树，树长69，一致性系数0.7246，排除无用特征的一致性系数0.6122，保留系数0.6346。由5种中鲤组成的中鲤亚属明显不构成一个单系群。结果表明：中鲤亚属是一个复系群，该类元应该被撤销。

基于逻辑"或"约束优化的实时系统设计

标准约束优化问题的等式或不等式约束之间是逻辑“与”关系，目前已经有很多高效、收敛的优化算法．但是，在实际应用中有很多更一般的约束优化问题，其等式或不等式约束之间不仅包含逻辑“与”关系，而且还包含逻辑“或”关系，现有的针对标准约束优化问题的各种算法不再适用，给出一种新的数学变换方法，把具有逻辑“或”关系的不等式约束转换为一组具有逻辑“与”关系的不等式，并应用到实时单调速率调度算法的可调度性判定充要条件中，把实时系统设计表示成混合布尔型整数规划问题，利用经典的分支定界法求解．实验部分指出了各种方法的优缺点．

土壤干旱对2个种源野生酸枣幼苗生长和生理特性的影响

以采自陕西杨陵和安塞的2个1年生酸枣幼苗为材料,采用盆栽称重控水法研究了中度和重度土壤干旱胁迫对它们生长和生理特性的影响。结果表明,不同程度的水分胁迫均使2种源酸枣新生侧枝长度受到极显著抑制,其苗高和基径也受到一定程度抑制,同时分别使叶片相对含水量和水分饱和亏有一定程度的降低和升高;2种源酸枣叶片的叶绿素a含量在各水分胁迫均极显著降低,它们的总叶绿素含量也在重度干旱下显著降低;随土壤干旱胁迫时间的延续,2种源酸枣叶片保护酶SOD、CAT、APX活性上下波动,其脯氨酸和可溶性糖含量逐渐升高,而超氧阴离子含量在较低水平下波动,丙二醛含量逐渐降低。杨陵酸枣在土壤水分较好的条件下表现良好,而安塞酸枣则具有更强的适应旱生能力。研究发现,在不同程度的土壤干旱胁迫下,2个种源酸枣的生长均受到一定程度的抑制,但它们均能调节自身的保护酶系统活性和渗透调节物质含量来减轻干旱伤害,维持植物体的正常生理代谢功能,表现出较强的抗旱耐旱能力。

小波变换和神经网络在化学中的应用

本论文分为两部分：小波变换和神经网络在化学中的应用。小波变换是新近出现的数学方法。近年来，在化学中得到广泛的应用，本论文介绍小波变换和我分辨分析的原理和方法，并将其应用到信号的压缩和滤噪。在研究中提出了常用小波变换数据压缩的三种方法，将紧支集小波和正交三次B－样条小波压缩4－苯乙基邻苯二甲酸酐的红外光谱数据进行了对比，计算表明正交三次B－样条小波变换方法效果较好，而在全部保留模糊信号及只保留锐化信号中数值较大的系数时，压缩比大而重建光谱数据与原始光谱数据间的均方差较小。应用小波变换对表面等离子体子共振（Surface Plasmon Resonance，SPR）仪的信号进行滤噪处理，利用SPR仪器信号和噪音的频率特性而将其分离，取得良好效果。本文对神经网络在化学中应用进行了较深入的研究，并对影响神经网络的诸多因素进行了探讨。在神经网络和多元回归等在化学应用中过多的变量会导致数学模型的预测结果变差，因而选择合适变量是很重要的。本文对比了传统的统计方法（前进选择法，后退剔除法，逐步回归法），Leaps-and-Bounds回归法，正交变换法，主成分分析以及最新的优化技术遗传算法，得到了一些有意义的结果。同时提出了组合算法和前进选择法的得合算法，结果表明这种算法在一定程度上避免了局部最优且减少了计算量。本论文还利用上述方法进行了一些定量结构活性相关性研究，主要内容：1）环境中有毒有害有机物（苯酚，苯胺，硝基苯）的定量结构活性相性研究。2）抗艾滋病类药物（HEPT）定量结构活性相关性研究。3）抗肿瘤类药物（氮芥子气类化合物和2－甲酸吡啶缩氨基硫脲类化合物定量结构活性相关性研究。4）苯酚和苯胺类衍生物色谱比移值预测。5）将神经网络用于茶叶的分类。

Effect of volume ratio on thermocapillary flow in liquid bridges of high-Prandtl-number fluids

In present study, the transition of thermocapillary convection from the axisymmetric stationary flow to oscillatory flow in liquid bridges of 5cst silicon oil (aspect ratio 1.0 and 1.6) is investigated in microgravity conditions by the linear instability analysis. The corresponding marginal instability boundary is closely related to the gas/liquid configuration of the liquid bridge noted as volume ratio. With the increasing volume ratio, the marginal instability boundary consists of the increasing branch and the decreasing branch. A gap region exists between the branches where the critical Marangoni number of the corresponding axisymmetric stationary flow increases drastically. Particularly, a unique axisymmetric oscillatory flow (the critical azimuthal wave number is m=0) in the gap region is reported for the liquid bridge of aspect ratio 1.6. Moreover, the energy transfer between the basic state and the disturbance fields of the thermocapillary convection is analyzed at the corresponding critical Marangoni number, which reveals different major sources of the energy transfer for the development of the disturbances in regimes of the increasing branch, the gap region and the decreasing branch, respectively.

大气CO2浓度升高对红桦碳水化合物含量和分配的影响

碳水化合物按其存在的形式可分为结构性碳水化合物和非结构性碳水化合物两种。前者主要用于植物体的形态建成；后者是参与植物生命代谢的重要物质。迄今为止，有关CO2浓度升高对植物叶片中的碳水化合物含量的研究较多，而对其它器官中碳水化合物含量以及碳水化合物在植物体内的分配响应研究较少。碳水化合物含量在植物各器官中的变化能够反映光合同化产物在叶和茎、枝和根中的转运情况；碳水化合物的分配与植物的生长模式相关，它的变化会对植物的生长情况产生影响。因此，为全面认识植物生理生化与生长过程对大气CO2浓度升高响应情况，需要对CO2浓度升高条件下植物体内碳水化合物的含量及分配变化进行深入的研究与探讨。本文应用自控、独立、封闭的生长室系统，研究了红桦幼苗根、茎、叶和枝的碳水化合物含量以及分配格局对大气CO2浓度升高(环境CO2浓度+350 µmol·mol-1) 的响应。研究结果表明：1) CO2浓度升高使红桦幼苗叶片中的非结构性碳水化合物含量显著增加。这可能会对光合作用造成反馈抑制，降低光合速率。2) CO2浓度升高使红桦幼苗根、茎和枝中的还原糖、蔗糖、总可溶性糖、淀粉和总的非结构性碳水化合物(TNC) 含量显著增加。说明CO2浓度升高促进了碳水化合物由叶片向枝、茎和根中的运输转移，支持了Finn和Brun的假设。3) 在总的非结构性碳水化合物(TNC) 中，淀粉所占比例最大。同样地，CO2浓度升高使TNC含量增加的部分中，淀粉所占的比例也最大。在叶片、枝、茎和根中淀粉含量增加部分占TNC含量增加部分的91.45%、88.23%、83.23%和82.01%。4) CO2浓度升高使红桦幼苗根、茎、叶和枝内的纤维素含量有增加的趋势，但未达到显著水平。需要进一步研究长期CO2浓度升高下，纤维素含量的响应程度。5) CO2浓度升高使碳水化合物在红桦幼苗体内的分配发生了改变。红桦幼苗体内碳水化合物分配变化的一致趋势是由地上部分向地下部分分配转移。其中，测定的所有碳水化合物均向根中分配增多。同时，CO2浓度升高使红桦幼苗的根冠比显著增大；根系干重显著增加。这些结果支持了Gorissen 和Cotrufo的假设，即碳水化合物向根中分配增多是根冠比增大的主要原因。6) CO2浓度升高使红桦幼苗体内的氮含量显著下降。氮含量的下降可能主要是由生长的加快和TNC (主要是淀粉) 含量的增加对氮的稀释造成的。Carbohydrates found in plants are frequently grouped into two different classes:structural carbohydrates and non-structural carbohydrates. The former mainlyconstruct the plant basic framework, while the latter are essential for plant growth andmetabolism. As yet there is lack of information on the effects of elevated CO2concentration on carbohydrate contents in stem, branch and root of plant, and oncarbohydrate allocation in organs of plant although there have been many reports onthe responses of carbohydrate contents to elevated CO2 concentration in plant foliages.A shift of carbohydrate contents in plant reflects a change in transporting ofphotosynthetic production from leaf to stem, branch and root of plant. The allocationof carbohydrates that is correlated to plant growth patterns affects plant growth. Thus,in order to understand the influences of elevated CO2 on biochemical process,physiological change and plant growth well, the response of carbohydrate contentsand allocation in plant to elevated CO2 should be further investigated. In our study, theeffects of elevated CO2 on carbohydrate contents and their allocation between leaf,stem, branch and root tissue of Betula albosinensis seedlings were determined. Theseedlings were grown in independent and enclosed-top chambers. Chambers werecontrolled to reproduce ambient (CK) and ambient + 350 µmol·mol-1 CO2 (EC)concentration for 1 year. The results here showed that,1) Elevated CO2 significantly increased non-structural carbohydrate contents in leafof red birch seedlings. This will reduce photosynthetic rate.2) Elevated CO2 also significantly increased non-structural carbohydrate contentsin root, stem and branch of red birch seedlings. These findings supported thehypothesis that elevated CO2 accelerated carbohydrates from leaf to branch, stem androot.3) Starch makes up the largest parts of total non-structural carbohydrate. In thesame way, the increase of starch plays a main role in the increase of totalnon-structural carbohydrate under elevated CO2. In leaf, branch, stem and root, theincrements of starch contents comprised 91.45%, 88.23%, 83.23% and 82.01% of theincrements of total non-structural carbohydrate contents.4) Under elevated CO2 the cellulose contents have an increasing tendency in redbirch seedlings. It is needed to investigate the effects of long-term elevated CO2 oncellulose contents in plant.5) There are significant CO2 effects on the allocation of carbohydrate in organs ofred birch seedlings. Under elevated CO2 more carbohydrates were allocated to root.Moreover, CO2 enrichment significantly increased the root to shoot ratio of red birchseedlings and the dry weight of roots. These results supported Gorissen and Cotrufo ‘shypothesis that increase of carbohydrate allocation to root mostly contributed to theincrease of root to shoot ratio.6) Elevated CO2 brought about a reduction in the nitrogen contents of leaf, stem,branch and root. The decline of nitrogen contents under elevated CO2 is mainlycaused by the dilution effects of increasing starch level and growth of red birchseedlings.

Applications of the method of three-dimensional projection of a molecule in quantitative structure-activity relationship of phenol derivatives

Five variables for phenol derivatives were calculated by molecular projection in three-dimensional space which were combined with eight quantum-chemical parameters and three Am indices. These variables were selected by using leaps-and-bounds regression analysis. Multiple linear regression analysis and artificial neural networks' were performed, and the results obtained by using. artificial neural networks are superior than that obtained by using multiple linear regression.

Applications of generalized torsion angles in studies on quantitative structure-activity relationship

In this article, generalized torsion angles of derivatives of 1-[(2-hydroxyethoxy)methy1]-6(phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular similarity matrix was built based on the calculated generalized torsion angles. These similarities were taken as the new variables, and the new variables were selected by using Leaps-and-Bounds regression analysis. Multiple regression analysis and neural networks were performed, and the satisfactory results were achieved by using the neural networks.

Comparison of different methods for variable selection

In chemistry for chemical analysis of a multi-component sample or quantitative structure-activity/property relationship (QSAR/QSPR) studies, variable selection is a key step. In this study, comparisons between different methods were performed. These methods include three classical methods such as forward selection, backward elimination and stepwise regression; orthogonal descriptors; leaps-and-bounds regression and genetic algorithm. Thirty-five nitrobenzenes were taken as the data set. From these structures quantum chemical parameters, topological indices and indicator variable were extracted as the descriptors for the comparisons of variable selections. The interesting results have been obtained. (C) 2001 Elsevier Science B.V. All rights reserved.

Prediction of C-13-nuclear magnetic resonance chemical shifts for aliphatic amines

Prediction of C-13-nuclear magnetic resonance chemical shifts for aliphatic amines is performed. The topological, geological and electronic descriptors are generated. To reduce the variables, the best subsets of the descriptors are obtained by using leaps-and-bounds regression analysis. The model is achieved using multiple regression with satisfactory results.

Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks

The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.

Finding optimal alternatives based on efficient comparative preference inference

Choosing the right or the best option is often a demanding and challenging task for the user (e.g., a customer in an online retailer) when there are many available alternatives. In fact, the user rarely knows which offering will provide the highest value. To reduce the complexity of the choice process, automated recommender systems generate personalized recommendations. These recommendations take into account the preferences collected from the user in an explicit (e.g., letting users express their opinion about items) or implicit (e.g., studying some behavioral features) way. Such systems are widespread; research indicates that they increase the customers' satisfaction and lead to higher sales. Preference handling is one of the core issues in the design of every recommender system. This kind of system often aims at guiding users in a personalized way to interesting or useful options in a large space of possible options. Therefore, it is important for them to catch and model the user's preferences as accurately as possible. In this thesis, we develop a comparative preference-based user model to represent the user's preferences in conversational recommender systems. This type of user model allows the recommender system to capture several preference nuances from the user's feedback. We show that, when applied to conversational recommender systems, the comparative preference-based model is able to guide the user towards the best option while the system is interacting with her. We empirically test and validate the suitability and the practical computational aspects of the comparative preference-based user model and the related preference relations by comparing them to a sum of weights-based user model and the related preference relations. Product configuration, scheduling a meeting and the construction of autonomous agents are among several artificial intelligence tasks that involve a process of constrained optimization, that is, optimization of behavior or options subject to given constraints with regards to a set of preferences. When solving a constrained optimization problem, pruning techniques, such as the branch and bound technique, point at directing the search towards the best assignments, thus allowing the bounding functions to prune more branches in the search tree. Several constrained optimization problems may exhibit dominance relations. These dominance relations can be particularly useful in constrained optimization problems as they can instigate new ways (rules) of pruning non optimal solutions. Such pruning methods can achieve dramatic reductions in the search space while looking for optimal solutions. A number of constrained optimization problems can model the user's preferences using the comparative preferences. In this thesis, we develop a set of pruning rules used in the branch and bound technique to efficiently solve this kind of optimization problem. More specifically, we show how to generate newly defined pruning rules from a dominance algorithm that refers to a set of comparative preferences. These rules include pruning approaches (and combinations of them) which can drastically prune the search space. They mainly reduce the number of (expensive) pairwise comparisons performed during the search while guiding constrained optimization algorithms to find optimal solutions. Our experimental results show that the pruning rules that we have developed and their different combinations have varying impact on the performance of the branch and bound technique.

Fifty years of scheduling: a survey of milestones

Scheduling has become a major field within operational research with several hundred publications appearing each year. This paper explores the historical development of the subject since the mid-1950s when the landmark publications started to appear. A discussion of the main topics of scheduling research for the past five decades is provided, highlighting the key contributions that helped shape the subject. The main topics covered in the respective decades are combinatorial analysis, branch and bound, computational complexity and classification, approximate solution algorithms and enhanced scheduling models.