At the interface of phylogenetics and population genetics, the phylogeography of Dirca occidentalis (Thymelaeaceae)

Dirca occidentalis is a rare shrub indigenous to only six counties near the San Francisco Bay in California, United States. We used intersimple sequence repeat (ISSR) markers and automated genotyping to probe 29 colonies of D. occidentalis from four geographically disjunct populations (East Bay, North Bay, Salmon Creek, and Peninsula) and used methods of phylogenetics and population genetics to model variation across the species. Results show that the four disjunct populations are genetically isolated and have undergone divergence. Phylogenetic analyses indicate that the East Bay population was the first to diverge, followed by the North Bay, then the Salmon Creek and Peninsula populations. This order of divergence suggests an intriguing natural history for D. occidentalis that is explained by the dynamic geological and climatic history of the Bay Area. Spatial genetic structure detected for the species suggests an interaction of four factors: limited seed dispersal, clonal regeneration, distances traveled by pollinators, and genetic isolation of the four populations. Genetic diversity within the North Bay and Salmon Creek populations is low, indicating poor ecological fitness and risk of decline. ISSRs resolved phylogeographic structure within D. occidentalis, results unattainable with ITS methods, and the integration of tools of phylogenetics and population biology led to an enhanced understanding of this endemic species

Time-Dependent Physicochemical Changes of Carbonate Surfaces from SmartWater (Diluted Seawater) Flooding Processes for Improved Oil Recovery.

Over the past few decades, field- and laboratory-scale studies have shown enhancements in oil recovery when reservoirs, which contain high-salinity formation water (FW), are waterflooded with modified-salinity salt water (widely referred to as the low-salinity, dilution, or SmartWater effect for improved oil recovery). In this study, we investigated the time dependence of the physicochemical processes that occur during diluted seawater (i.e., SmartWater) waterflooding processes of specific relevance to carbonate oil reservoirs. We measured the changes to oil/water/rock wettability, surface roughness, and surface chemical composition during SmartWater flooding using 10-fold-diluted seawater under mimicked oil reservoir conditions with calcite and carbonate reservoir rocks. Distinct effects due to SmartWater flooding were observed and found to occur on two different timescales: (1) a rapid (<15 min) increase in the colloidal electrostatic double-layer repulsion between the rock and oil across the SmartWater, leading to a decreased oil/water/rock adhesion energy and thus increased water wetness and (2) slower (>12 h to complete) physicochemical changes of the calcite and carbonate reservoir rock surfaces, including surface roughening via the dissolution of rock and the reprecipitation of dissolved carbonate species after exchanging key ions (Ca2+, Mg2+, CO32-, and SO42- in carbonates) with those in the flooding SmartWater. Our experiments using crude oil from a carbonate reservoir reveal that these reservoir rock surfaces are covered with organic-ionic preadsorbed films (ad-layers), which the SmartWater removes (detaches) as flakes. Removal of the organic-ionic ad-layers by SmartWater flooding enhances oil release from the surfaces, which was found to be critical to increasing the water wetness and significantly improving oil removal from carbonates. Additionally, the increase in water wetness is further enhanced by roughening of the rock surfaces, which decreases the effective contact (interaction) area between the oil and rock interfaces. Furthermore, we found that the rate of these slower physicochemical changes to the carbonate rock surfaces increases with increasing temperature (at least up to an experimental temperature of 75 °C). Our results suggest that the effectiveness of improved oil recovery from SmartWater flooding depends strongly on the formation of the organic-ionic ad-layers. In oil reservoirs where the ad-layer is fully developed and robust, injecting SmartWater would lead to significant removal of the ad-layer and improved oil recovery

A review of clinical decision-making: Models and current research

Aims and objectives: The aim of this paper was to review the current literature with respect to clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information processing model, the intuitive-humanist model and the clinical decision making model. Background: Clinical decision-making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognised from the literature; the information processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Design: Literature review Methods: Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 – November 2005