Middle holocene soil and migration of climatic zones in the Guanzhong plain of China

IEECAS SKLLQG

High efficiency white organic light-emitting diodes based on double recombination zones

A multilayer white organic light-emitting diode (OLED) with high efficiency was present. The luminescent layer was composed of a red dye 4-(dicyanomethylene)-2-t-butyle-6-(1,1,7,7-tetra-methyljulolidyl-9-enyl)-4H-pyran (DCJTB) doped into NN-bis-(1-naphthyl)-N,N-diphenyl-1,1-biphenyl-4-4-diamine (NPB) layer and a blue-emitting 9,10-bis-(beta-naphthyl)-anthrene (DNA) layer. Red and blue emission, respectively, from DCJTB:NPB and DNA can be obtained by effectively controlling the thicknesses of DCJTB:NPB and DNA layers, thus a stable white light emission was achieved. The device turned on at 3.5 V, and the maximum luminance reached 16000 cd/m(2) at 21 V. The maximum current efficiency and power efficiency were 13.6 cd/A and 5.5 lm/W, respectively.

Talc-bearing serpentinized peridotites from the southern Mariana forearc: implications for aseismic character within subduction zones

The serpentinized peridotites overlying the subducted zones in the Izu-Bonin-Mariana (IBM) arc system have been interpret as the cause of the low-velocity layer identified beneath the IBM froearc, in turn few earthquakes occurred along the plate boundary. Chrysotile, which is a low temperature and highly hydrated phase of serpentine with low frictional strength, has been suggested as the low velocity material in the serpentinized peridotites, besides, brucite is inferred to be likely conducive to stable sliding. However, such idea encounters challenging in our serpentinized peridotites from the southern Mariana forearc, which absent both the above minerals. The presence of talc, which characterized by its weak, low-friction and inherently stable sliding behavior, provides new clue. Here we report the occurrence of talc in serpentinized peridotites collected from the landward trench slope of the southern Mariana forearc. We infer that talc is mainly forming as a result of the reaction of serpentine minerals with silica-saturated fluids released from the subducting slab, and talc also occurs as talc veins sometimes. Due to its unique physical properties, talc may therefore play a significant role in aseismic slip in the IBM subduction zone.

Alloy elements' effect on anti-corrosion performance of low alloy steels in different sea zones

The corrosion rate of low alloy steel in different sea zones has close correlation with the content of the alloy element. From the field data of steel corrosion rates in atmospheric zone, splash zone and immersion zone, regression analysis was used to study the correlation between the corrosion rate of steels and the amount of added alloy elements. Three regression equations were obtained in different sea zones. Based on the equations, the anti-corrosion performance of the alloy elements can be deduced which can be used to screen out low alloy steel with good anti-corrosion performance. (C) 2007 Elsevier B.V. All rights reserved.

Methane emissions from different vegetation zones in a Qinghai-Tibetan Plateau wetland

We measured methane (CH4) emissions in the Luanhaizi wetland, a typical alpine wetland on the Qinghai-Tibetan Plateau, China, during the plant growth season (early July to mid-September) in 2002. Our aim was to quantify the spatial and temporal variation of CH4 flux and to elucidate key factors in this variation. Static chamber measurements of CH4 flux were made in four vegetation zones along a gradient of water depth. There were three emergent-plant zones (Hippuris-dominated; Scirpus-dominated; and Carex-dominated) and one submerged-plant zone (Potamogeton-dominated). The smallest CH4 flux (seasonal mean = 33.1 mg CH4 m(-2) d(-1)) was, observed in the Potamogeton-dominated zone, which occupied about 74% of the total area of the wetland. The greatest CH4 flux (seasonal mean = 214 mg CH4 m(-2) d(-1)) was observed in the Hippuris-dominated zone, in the second-deepest water area. CH4 flux from three zones (excluding the Carex-dominated zone) showed a marked diurnal change and decreased dramatically under dark conditions. Light intensity had a major influence on the temporal variation in CH4 flux, at least in three of the zones. Methane fluxes from all zones increased during the growing season with increasing aboveground biomass. CH4 flux from the Scirpus-dominated zone was significantly lower than in the other emergent-plant zones despite the large biomass, because the root and rhizome intake ports for CH4 transport in the dominant species were distributed in shallower and more oxidative soil than occupied in the other zones. Spatial and temporal variation in CH4 flux from the alpine wetland was determined by the vegetation zone. Among the dominant species in each zone, there were variations in the density and biomass of shoots, gas-transport system, and root-rhizome architecture. The CH4 flux from a typical alpine wetland on the Qinghai-Tibetan Plateau was as high as those of other boreal and alpine wetlands. (C) 2004 Elsevier Ltd. All rights reserved.

Activity Zones for Context-Aware Computing

Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or Euclidean distance various landmarks. A user?s concept of location, however, is often defined in terms of regions in which common activities occur. We show how to partition a space into such regions based on patterns of observed user location and motion. These regions, which we call activity zones, represent regions of similar user activity, and can be used to trigger application actions, retrieve information based on previous context, and present information to users. We suggest that context-aware applications can benefit from a location representation learned from observing users. We describe an implementation of our system and present two example applications whose behavior is controlled by users? entry, exit, and presence in the zones.

The divine enterprise of missions a series of lectures

http://www.archive.org/details/divineenterprise00pieruoft

Upon the earth; the mission of God and the missionary enterprise of the churches.

http://www.archive.org/details/upontheearththem013276mbp

The contribution of enterprise systems to core capabilities: the case of asset lifecycle management in the utilities sector

The desire to obtain competitive advantage is a motivator for implementing Enterprise Resource Planning (ERP) Systems (Adam & O’Doherty, 2000). However, while it is accepted that Information Technology (IT) in general may contribute to the improvement of organisational performance (Melville, Kraemer, & Gurbaxani, 2004), the nature and extent of that contribution is poorly understood (Jacobs & Bendoly, 2003; Ravichandran & Lertwongsatien, 2005). Accordingly, Henderson and Venkatraman (1993) assert that it is the application of business and IT capabilities to develop and leverage a firm’s IT resources for organisational transformation, rather than the acquired technological functionality, that secures competitive advantage for firms. Application of the Resource Based View of the firm (Wernerfelt, 1984) and Dynamic Capabilities Theory (DCT) (Teece and Pisano (1998) in particular) may yield insights into whether or not the use of Enterprise Systems enhances organisations’ core capabilities and thereby obtains competitive advantage, sustainable or otherwise (Melville et al., 2004). An operational definition of Core Capabilities that is independent of the construct of Sustained Competitive Advantage is formulated. This Study proposes and utilises an applied Dynamic Capabilities framework to facilitate the investigation of the role of Enterprise Systems. The objective of this research study is to investigate the role of Enterprise Systems in the Core Dynamic Capabilities of Asset Lifecycle Management. The Study explores the activities of Asset Lifecycle Management, the Core Dynamic Capabilities inherent in Asset Lifecycle Management and the footprint of Enterprise Systems on those Dynamic Capabilities. Additionally, the study explains the mechanisms by which Enterprise Systems sustain the Exploitability and the Renewability of those Core Dynamic Capabilities. The study finds that Enterprise Systems contribute directly to the Value, Exploitability and Renewability of Core Dynamic Capabilities and indirectly to their Inimitability and Non-substitutability. The study concludes by presenting an applied Dynamic Capabilities framework, which integrates Alter (1992)’s definition of Information Systems with Teece and Pisano (1998)’s model of Dynamic Capabilities to provide a robust diagnostic for determining the sustained value generating contributions of Enterprise Systems. These frameworks are used in the conclusions to frame the findings of the study. The conclusions go on to assert that these frameworks are free - standing and analytically generalisable, per Siggelkow (2007) and Yin (2003).

Design principles for an enterprise systems chartering method

Our research follows a design science approach to develop a method that supports the initialization of ES implementation projects – the chartering phase. This project phase is highly relevant for implementation success, but is understudied in IS research. In this paper, we derive design principles for a chartering method based on a systematic review of ES implementation literature and semi-structured expert interviews. Our analysis identifies differences in the importance of certain success factors depending on the system type. The proposed design principles are built on these factors and are linked to chartering key activities. We specifically consider system-type-specific chartering aspects for process-centric Business Intelligence & Analytics (BI&A) systems, which are an emerging class of systems at the intersection of BI&A and business process management. In summary, this paper proposes design principles for a chartering method – considering specifics of process-centric BI&A.

Nutrient enrichment effects on mangrove sediments from differing tree height zones in Bocas del Toro, Panama

Red mangrove (Rhizophora mangle L.) forests have distinct tree-height zones, with tall trees fringing the ocean and shorter trees in interior stands. A long-term nitrogen (N) and phosphorus (P) fertilization experiment in Almirante Bay, Bocas del Toro Province, Panama has shown that tree-height zonation is primarily related to nutrient limitation. This experiment was used to test the effects of in-situ nutrient additions and tree zonation on mangrove sediments. The sediments underlying the experimental R. mangle trees were sampled and N₂ fixation, ¹⁵N, chlorophyll a, percent N and P, and percent organic biomass were quantified. Both N and P additions significantly affected almost every parameter measured in both zones within this experiment. These results are likely to have implications for management since N and P inputs are predicted to increase throughout the tropics and subtropics worldwide.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.