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Minimal Data (minimal + data)
Selected AbstractsForensic nursing in secure environmentsJOURNAL OF FORENSIC NURSING, Issue 3 2009Deborah Shelton PhD Abstract There are few well-designed studies of corrections or prison nursing roles. This study seeks to describe the corrections or prison role of forensic nurses in the United States who provide care in secure environments. National data detailing the scope of practice in secure environments are limited. This pencil and paper survey describes the roles of 180 forensic nurses from 14 states who work in secure environments. Descriptive statistics are utilized. A repeated measures ANOVA with post hoc analyses was implemented. These nurses were older than average in age, but had 10 years or less experience in forensic nursing practice. Two significant roles emerged to "promote and implement principles that underpin effective quality and practice" and to "assess, develop, implement, and improve programs of care for individuals." Significant roles varied based upon the security classification of the unit or institution in which the nurses were employed. Access to information about these nurses and their nursing practice was difficult in these closed systems. Minimal data are available nationally, indicating a need for collection of additional data over time to examine changes in role. It is through such developments that forensic nursing provided in secure environments will define its specialization and attract the attention it deserves. [source] Hydrological and erosional response to natural rainfall in a semi-arid area of south-east SpainHYDROLOGICAL PROCESSES, Issue 4 2001M. Martinez-Mena Abstract A better knowledge of soil erosion by water is essential for planning effective soil and water conservation practices in semi-arid Mediterranean environments. The special climatic and hydrological characteristics of these areas, however, make accurate soil loss predictions difficult, particularly in the absence of minimal data. Two zero-order experimental microcatchments (328,759 m2), representative of an extensive semi-arid watershed with a high potential erosion risk in the south-east of Spain, were selected and monitored for 3 years (1991,93) in order to provide information on the hydrological and erosional response. A pluviogram and hydrograph recorded data at 1-min intervals during each storm, after which the soil loss was collected and the particle size of the sediment was analysed. Runoff coefficients of about 9% and soil losses of between 84·83 and 298·9 g m,2 year,1 were observed in the area. Rapid response times (geometric mean values lower than 2 h) and low runoff thresholds (mean values between 3·5 to 5·9 mm) were the norm in the experimental areas. A rain intensity of over 15 mm h,1 was considered as ,erosive rainfall' in these areas because of the total soil loss and the transport capacity of the overland flow. Differences in pore-size distribution explained the different hydrological responses observed between areas. The erosional response was more complex and basically seemed to be determined by soil aggregate stability and topographical properties. A greater proportion of finer particles in the eroded material than in the soil matrix indicated selective erosion and the transport of finer material. Copyright © 2001 John Wiley & Sons, Ltd. [source] Quantifying allowable harm in species at risk: application to the Laurentian black redhorse (Moxostoma duquesnei)AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 6 2009Luis A. Vélez-Espino Abstract 1.When a species is identified for conservation, often the only way to effect recovery is to reduce the harm imposed by stressors threatening the survival of the species. Ideally all threats would be removed; however, this is often not feasible or practical. Within this context, a demographic approach is presented to assess how much human-induced harm could be allowed without impairing the persistence of the species. Harm is defined as a negative perturbation that can target one or more vital rates and life stages simultaneously. 2.Allowable harm, defined as a level of harm that will not jeopardize survival or recovery, will be a function of the vital rates affected by human actions, the sensitivity of population growth to changes in these vital rates (their elasticities), the population growth rate prevailing before harm occurs, and the set of demographic parameters considered safe for long-term persistence. This life-history based approach requires minimal data, can link demography with habitat-explicit information, is flexible enough to encompass complex life histories, and follows a precautionary approach. 3.Quantification of allowable harm could be applied to any species at risk. This approach is introduced by applying it to a Canadian population of a freshwater fish, the black redhorse (Moxostoma duquesnei), demonstrating that in the absence of habitat constraints population dynamics of this species are most sensitive to the survival of young adults, but population fitness is particularly sensitive to the loss of habitat used by young-of-the-year fish under current levels of habitat supply. Copyright © 2009 John Wiley & Sons, Ltd. [source] Prediction of metabolic function from limited data: Lumped hybrid cybernetic modeling (L-HCM)BIOTECHNOLOGY & BIOENGINEERING, Issue 2 2010Hyun-Seob Song Abstract Motivated by the need for a quick quantitative assessment of metabolic function without extensive data, we present an adaptation of the cybernetic framework, denoted as the lumped hybrid cybernetic model (L-HCM), which combines the attributes of the classical lumped cybernetic model (LCM) and the recently developed HCM. The basic tenet of L-HCM and HCM is the same, that is, they both view the uptake flux as being split among diverse pathways in an optimal way as a result of cellular regulation such that some chosen metabolic objective is realized. The L-HCM, however, portrays this flux distribution to occur in a hierarchical way, that is, first among lumped pathways, and next among individual elementary modes (EM) in each lumped pathway. Both splits are described by the cybernetic control laws using operational and structural return-on-investments, respectively. That is, the distribution of uptake flux at the first split is dynamically regulated according to environmental conditions, while the subsequent split is based purely on the stoichiometry of EMs. The resulting model is conveniently represented in terms of lumped pathways which are fully identified with respect to yield coefficients of all products unlike classical LCMs based on instinctive lumping. These characteristics enable the model to account for the complete set of EMs for arbitrarily large metabolic networks despite containing only a small number of parameters which can be identified using minimal data. However, the inherent conflict of questing for quantification of larger networks with smaller number of parameters cannot be resolved without a mechanism for parameter tuning of an empirical nature. In this work, this is accomplished by manipulating the relative importance of EMs by tuning the cybernetic control of mode-averaged enzyme activity with an empirical parameter. In a case study involving aerobic batch growth of Saccharomyces cerevisiae, L-HCM is compared with LCM. The former provides a much more satisfactory prediction than the latter when parameters are identified from a few primary metabolites. On the other hand, the classical model is more accurate than L-HCM when sufficient datasets are involved in parameter identification. In applying the two models to a chemostat scenario, L-HCM shows a reasonable prediction on metabolic shift from respiration to fermentation due to the Crabtree effect, which LCM predicts unsatisfactorily. While L-HCM appears amenable to expeditious estimates of metabolic function with minimal data, the more detailed dynamic models [such as HCM or those of Young et al. (Young et al., Biotechnol Bioeng, 2008; 100: 542,559)] are best suited for accurate treatment of metabolism when the potential of modern omic technology is fully realized. However, in view of the monumental effort surrounding the development of detailed models from extensive omic measurements, the preliminary insight into the behavior of a genotype and metabolic engineering directives that can come from L-HCM is indeed valuable. Biotechnol. Bioeng. 2010;106: 271,284. © 2010 Wiley Periodicals, Inc. [source] | ||||||||||