Development of Detailed Clinical Models for Nursing Assessments and Nursing Interventions

Objectives: The aim of this study was to develop and validate Detailed Clinical Models (DCMs) for nursing assessments and interventions. Methods: First, we identified the nursing assessment and nursing intervention entities. Second, we identified the attributes and the attribute values in order to describe the entities in more detail. The data type and optionality of the attributes were then defined. Third, the entities, attributes and value sets in the DCMs were mapped to the International Classification for Nursing Practice Version 2 concepts. Finally, the DCMs were validated by domain experts and applied to case reports. Results: In total 481 DCMs, 429 DCMs for nursing assessments and 52 DCMs for nursing interventions, were developed and validated. The DCMs developed in this study were found to be sufficiently comprehensive in representing the clinical concepts of nursing assessments and interventions. Conclusions: The DCMs developed in this study can be used in electronic nursing records. These DCMs can be used to ensure the semantic interoperability of the nursing information documented in electronic nursing records

Applicability of the ISO Reference Terminology Model for Nursing to the Detailed Clinical Models of Perinatal Care Nursing Assessments

Objectives: The purpose of this study was to examine the applicability of the International Organization for Standardization (ISO) reference terminology model for nursing to describe the terminological value domain content regarding the entities and attributes of the detailed clinical models (DCMs) used for nursing assessments. Methods: The first author mapped 52 DCM entities and 45 DCM attributes used for perinatal care nursing assessments to semantic domains and their qualifiers to the ISO model. The mapping results of the entity and attribute concepts were classified into four categories: mapped to a semantic domain qualifier, mapped to a semantic domain, mapped to a broader semantic domain concept, and not mapped. The DCM mapping results were classified into three categories: fully mapped, partially mapped, and not mapped. The second author verified the mapping. Results: All of the entities and 53.3 % of the attribute concepts of the DCMs were mapped to semantic domains or semantic domain qualifiers of the ISO model, 37.8 % of the attributes were mapped to the broader semantic domain concept, and 8.9 % of the attributes were not mapped. At the model level, 48.1 % of the DCMs were fully mapped to semantic domains or semantic domain qualifiers of the ISO model, and 51.9 % of the DCMs were partially mapped. Conclusions: The findings of this study demonstrate that the ISO reference terminology model for nursing is applicable in representing the DCM structure for perinatal care nursing assessment. However, more qualifiers of the Judgment semantic domain are required in orde

Quantitative estimation of sampling uncertainties for mycotoxins in cereal shipments

Many countries receive shipments of bulk cereals from primary producers. There is a volume of work that is ongoing that seeks to arrive at appropriate standards for the quality of the shipments and the means to assess the shipments as they are out-loaded. Of concern are mycotoxin and heavy metal levels, pesticide and herbicide residue levels, and contamination by genetically modified organisms (GMOs). As the ability to quantify these contaminants improves through improved analytical techniques, the sampling methodologies applied to the shipments must also keep pace to ensure that the uncertainties attached to the sampling procedures do not overwhelm the analytical uncertainties. There is a need to understand and quantify sampling uncertainties under varying conditions of contamination. The analysis required is statistical and is challenging as the nature of the distribution of contaminants within a shipment is not well understood; very limited data exist. Limited work has been undertaken to quantify the variability of the contaminant concentrations in the flow of grain coming from a ship and the impact that this has on the variance of sampling. Relatively recent work by Paoletti et al. in 2006 [Paoletti C, Heissenberger A, Mazzara M, Larcher S, Grazioli E, Corbisier P, Hess N, Berben G, Lubeck PS, De Loose M, et al. 2006. Kernel lot distribution assessment (KeLDA): a study on the distribution of GMO in large soybean shipments. Eur Food Res Tech. 224:129–139] provides some insight into the variation in GMO concentrations in soybeans on cargo out-turn. Paoletti et al. analysed the data using correlogram analysis with the objective of quantifying the sampling uncertainty (variance) that attaches to the final cargo analysis, but this is only one possible means of quantifying sampling uncertainty. It is possible that in many cases the levels of contamination passing the sampler on out-loading are essentially random, negating the value of variographic quantitation of the sampling variance. GMOs and mycotoxins appear to have a highly heterogeneous distribution in a cargo depending on how the ship was loaded (the grain may have come from more than one terminal and set of storage silos) and mycotoxin growth may have occurred in transit. This paper examines a statistical model based on random contamination that can be used to calculate the sampling uncertainty arising from primary sampling of a cargo; it deals with what is thought to be a worst-case scenario. The determination of the sampling variance is treated both analytically and by Monte Carlo simulation. The latter approach provides the entire sampling distribution and not just the sampling variance. The sampling procedure is based on rules provided by the Canadian Grain Commission (CGC) and the levels of contamination considered are those relating to allowable levels of ochratoxin A (OTA) in wheat. The results of the calculations indicate that at a loading rate of 1000 tonnes h-1, primary sample increment masses of 10.6 kg, a 2000-tonne lot and a primary composite sample mass of 1900 kg, the relative standard deviation (RSD) is about 1.05 (105%) and the distribution of the mycotoxin (MT) level in the primary composite samples is highly skewed. This result applies to a mean MT level of 2 ng g-1. The rate of false-negative results under these conditions is estimated to be 16.2%. The corresponding contamination is based on initial average concentrations of MT of 4000 ng g-1 within average spherical volumes of 0.3m diameter, which are then diluted by a factor of 2 each time they pass through a handling stage; four stages of handling are assumed. The Monte Carlo calculations allow for variation in the initial volume of the MT-bearing grain, the average concentration and the dilution factor. The Monte Carlo studies seek to show the effect of variation in the sampling frequency while maintaining a primary composite sample mass of 1900 kg. The overall results are presented in terms of operational characteristic curves that relate only to the sampling uncertainties in the primary sampling of the grain. It is concluded that cross-stream sampling is intrinsically unsuited to sampling for mycotoxins and that better sampling methods and equipment are needed to control sampling uncertainties. At the same time, it is shown that some combination of crosscutting sampling conditions may, for a given shipment mass and MT content, yield acceptable sampling performance

An ontology for integrated machining and inspection process planning focusing on resource capabilities

The search for and assignment of resources is extremely important for the efficient planning of any process in a distributed environment, such as the collaborative product integrated development process. These environments require a degree of semantic interoperability, which currently can only be provided by ontological models. However, the ontological proposals centred on Resources for Machining and nspection Process Planning have a limited reach, do not adopt a unified view of machining and inspection, and fail to express knowledge in the manner required by some of the planning tasks, as is the case with those concerned with resource assignment and plan validation. With the aim of providing a solution to these shortcomings the manufacturing and inspection resource capability (MIRC) ontology has been developed, as a specialist offshoot of the product and processes development resources capability ontology. This ontology considers resource capabilities to be a characteristic of the resource executing any activity present in an integrated process plan. Special attention is given to resource preparation activities, due to their influence on the quality of the final product. After describing the MIRC ontology, a case study demonstrates how the ontology supports the process planning for any level, approach or plan strategy.This work has been possible thanks to the funding received from the Spanish Ministry of Science and Education through the COAPP Research Project [reference DPI2007-66871-C02-01/02].Solano García, L.; Romero Subirón, F.; Rosado Castellano, P. (2016). An ontology for integrated machining and inspection process planning focusing on resource capabilities. International Journal of Computer Integrated Manufacturing. 29(1):1-15. doi:10.1080/0951192X.2014.1003149S11529

Biodegradability standards for carrier bags and plastic films in aquatic environments: a critical review

Plastic litter is encountered in aquatic ecosystems across the globe, including polar environments and the deep sea. To mitigate the adverse societal and ecological impacts of this waste, there has been debate on whether ‘biodegradable’ materials should be granted exemptions from plastic bag bans and levies. However, great care must be exercised when attempting to define this term, due to the broad and complex range of physical and chemical conditions encountered within natural ecosystems. Here, we review existing international industry standards and regional test methods for evaluating the biodegradability of plastics within aquatic environments (wastewater, unmanaged freshwater and marine habitats). We argue that current standards and test methods are insufficient in their ability to realistically predict the biodegradability of carrier bags in these environments, due to several shortcomings in experimental procedures and a paucity of information in the scientific literature. Moreover, existing biodegradability standards and test methods for aquatic environments do not involve toxicity testing or account for the potentially adverse ecological impacts of carrier bags, plastic additives, polymer degradation products or small (microscopic) plastic particles that can arise via fragmentation. Successfully addressing these knowledge gaps is a key requirement for developing new biodegradability standard(s) for lightweight carrier bags

Identification of mass–spring–damper model of walking humans

Interaction of walking people with vibrating structures is known to be an important yet challenging phenomenon to simulate. Despite of its considerable effects on the structural response, no properly formulated and experimentally verified model currently exists to simulate this interaction in the vertical direction. This work uses a single-degree-of-freedom mass–spring–damper model of a walking human to simulate its interaction with a vibrating structure. Extensive frequency response function measurements were performed on a test structure that was occupied by more than a hundred test subjects walking in various group sizes and at different times in 23 tests. The identified modal properties of the occupied structure were used in three different identification procedures to estimate the parameters of the walking human model. A discrete model of human–structure system was used to simulate interaction of each walking person with the structure. The analysis identified the range of 2.75–3.00 Hz for the natural frequency and 27.5%–30% for the damping ratio of the model of a walking human, having constant mass of 70 kg. The extent of the experimental data and the measurement details, diversity of loading scenarios and consistency of the results of the different identification procedures, provided high level of confidence on the suggested parameters for the single-degree-of-freedom walking human model.UK Engineering and Physical Sciences Research Council (EPSRC

Health implications of PAH release from coated cast iron drinking water distribution systems in The Netherlands.

BACKGROUND: Coal tar and bitumen have been historically used to coat the insides of cast iron drinking water mains. Polycyclic aromatic hydrocarbons (PAHs) may leach from these coatings into the drinking water and form a potential health risk for humans. OBJECTIVE: We estimated the potential human cancer risk from PAHs in coated cast iron water mains. METHOD: In a Dutch nationwide study, we collected drinking water samples at 120 locations over a period of 17 days under various operational conditions, such as undisturbed operation, during flushing of pipes, and after a mains repair, and analyzed these samples for PAHs. We then estimated the health risk associated with an exposure scenario over a lifetime. RESULTS: During flushing, PAH levels frequently exceeded drinking water quality standards; after flushing, these levels dropped rapidly. After the repair of cast iron water mains, PAH levels exceeded the drinking water standards for up to 40 days in some locations. CONCLUSIONS: The estimated margin of exposure for PAH exposure through drinking water was > 10,000 for all 120 measurement locations, which suggests that PAH exposure through drinking water is of low concern for consumer health. However, factors that differ among water systems, such as the use of chlorination for disinfection, may influence PAH levels in other locations