Minimal requirements for parameters to be used for the development of predictive models for microbial source tracking. The example of the pair somatic coliphages and phages infecting Bacteroides

Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.

Effect of Tocopherol Extract, Staphylococcus carnosus Culture, and Celery Concentrate Addition on Quality Parameters of Organic and Conventional Dry-Cured Sausages

The effects of the addition to sausage mix of tocopherols (200 mg/kg), a conventional starter culture with or without Staphylococcus carnosus, celery concentrate (CP) (0.23% and 0.46%), and two doses of nitrate (70 and 140 mg/kg expressed as NaNO(3)) on residual nitrate and nitrite amounts, instrumental CIE Lab color, tocol content, oxidative stability, and overall acceptability were studied in fermented dry-cured sausages after ripening and after storage. Nitrate doses were provided by nitrate-rich CP or a chemical grade source. The lower dose complies with the EU requirements governing the maximum for ingoing amounts in organic meat products. Tocopherol addition protected against oxidation, whereas the nitrate dose, nitrate source, or starter culture had little influence on secondary oxidation values. The residual nitrate and nitrite amounts found in the sausages with the lower nitrate dose were within EU-permitted limits for organic meat products and residual nitrate can be further reduced by the presence of the S. carnosus culture. Color measurements were not affected by the CP dose. Product consumer acceptability was not affected negatively by any of the factors studied. As the two nitrate sources behaved similarly for the parameters studied, CP is a useful alternative to chemical ingredients for organic dry-cured sausage production.

Computational Approach to the Study of Thermal Spin Crossover Phenomena

The key parameters associated to the thermally induced spin crossover process have been calculated for a series of Fe(II) complexes with mono-, bi-, and tridentate ligands. Combination of density functional theory calculations for the geometries and for normal vibrational modes, and highly correlated wave function methods for the energies, allows us to accurately compute the entropy variation associated to the spin transition and the zero-point corrected energy difference between the low- and high-spin states. From these values, the transition temperature, T 1/2, is estimated for different compounds.

Estudi comparatiu dels filtres de Kalman i IMM per a navegació

Els sistemes híbrids de navegació integren mesures de posició i velocitat provinents de satèl·lits (GPS) i d’unitats de mesura inercials (IMU).Les dades d’aquests sensors s’han de fusionar i suavitzar, i per a aquest propòsit existeixen diversos algorismes de filtratge, que tracten les dades conjuntament o per separat. En aquest treball s’han codificat en Matlab els algorismes dels filtres de Kalman i IMM, i s’han comparat les seves prestacions en diverses trajectòries d’un vehicle. S’han avaluat quantitativament els errors dels dos filtres, i s’han sintonitzat els seus paràmetres per a minimitzar aquests errors. Amb una correcta sintonia dels filtres, s’ha comprovat que el filtre IMM és superior al filtre de Kalman, tant per maniobres brusques com per maniobres suaus, malgrat que la complexitat i el temps de càlcul requerit són majors.

Measuring gait using a ground laser range sensor

This paper describes a mesurement system designed to register the displacement of the legs using a two-dimensional laser range sensor with a scanning plane parallel to the ground and extract gait parameters. In the proposed methodology, the position of the legs is estimated by fitting two circles with the laser points that define their contour and the gait parameters are extracted applying a step-line model to the estimated displacement of the legs to reduce uncertainty in the determination of the stand and swing phase of the gait. Results obtained in a range up to 8 m shows that the systematic error in the location of one static leg is lower than 10 mm with and standard deviation lower than 8 mm; this deviation increases to 11 mm in the case of a moving leg. The proposed measurement system has been applied to estimate the gait parameters of six volunteers in a preliminary walking experiment.

Minimal requirements for parameters to be used for the development of predictive models for microbial source tracking. The example of the pair somatic coliphages and phages infecting Bacteroides

Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.

The Total Deviation Index estimated by Tolerance Intervals to evaluate the concordance of measurement devices

Background In an agreement assay, it is of interest to evaluate the degree of agreement between the different methods (devices, instruments or observers) used to measure the same characteristic. We propose in this study a technical simplification for inference about the total deviation index (TDI) estimate to assess agreement between two devices of normally-distributed measurements and describe its utility to evaluate inter- and intra-rater agreement if more than one reading per subject is available for each device. Methods We propose to estimate the TDI by constructing a probability interval of the difference in paired measurements between devices, and thereafter, we derive a tolerance interval (TI) procedure as a natural way to make inferences about probability limit estimates. We also describe how the proposed method can be used to compute bounds of the coverage probability. Results The approach is illustrated in a real case example where the agreement between two instruments, a handle mercury sphygmomanometer device and an OMRON 711 automatic device, is assessed in a sample of 384 subjects where measures of systolic blood pressure were taken twice by each device. A simulation study procedure is implemented to evaluate and compare the accuracy of the approach to two already established methods, showing that the TI approximation produces accurate empirical confidence levels which are reasonably close to the nominal confidence level. Conclusions The method proposed is straightforward since the TDI estimate is derived directly from a probability interval of a normally-distributed variable in its original scale, without further transformations. Thereafter, a natural way of making inferences about this estimate is to derive the appropriate TI. Constructions of TI based on normal populations are implemented in most standard statistical packages, thus making it simpler for any practitioner to implement our proposal to assess agreement.

Assessment of the levels of degradation in fat co- and by-products for feed uses and their relationships with some lipid composition parameters

This paper discusses the levels of degradation of some co- and byproducts of the food chain intended for feed uses. As the first part of a research project, 'Feeding Fats Safety', financed by the sixth Framework Programme-EC, a total of 123 samples were collected from 10 European countries, corresponding to fat co- and byproducts such as animal fats, fish oils, acid oils from refining, recycled cooking oils, and other. Several composition and degradation parameters (moisture, acid value, diacylglycerols and monoacylglycerols, peroxides, secondary oxidation products, polymers of triacylglycerols, fatty acid composition, tocopherols, and tocotrienols) were evaluated. These findings led to the conclusion that some fat by- and coproducts, such as fish oils, lecithins, and acid oils, show poor, nonstandardized quality and that production processes need to be greatly improved. Conclusions are also put forward about the applicability and utility of each analytical parameter for characterization and quality control.

Prediction of the economic cost of individual long-term care in the Spanish population

Pensions together with savings and investments during active life are key elements of retirement planning. Motivation for personal choices about the standard of living, bequest and the replacement ratio of pension with respect to last salary income must be considered. This research contributes to the financial planning by helping to quantify long-term care economic needs. We estimate life expectancy from retirement age onwards. The economic cost of care per unit of service is linked to the expected time of needed care and the intensity of required services. The expected individual cost of long-term care from an onset of dependence is estimated separately for men and women. Assumptions on the mortality of the dependent people compared to the general population are introduced. Parameters defining eligibility for various forms of coverage by the universal public social care of the welfare system are addressed. The impact of the intensity of social services on individual predictions is assessed, and a partial coverage by standard private insurance products is also explored. Data were collected by the Spanish Institute of Statistics in two surveys conducted on the general Spanish population in 1999 and in 2008. Official mortality records and life table trends were used to create realistic scenarios for longevity. We find empirical evidence that the public long-term care system in Spain effectively mitigates the risk of incurring huge lifetime costs. We also find that the most vulnerable categories are citizens with moderate disabilities that do not qualify to obtain public social care support. In the Spanish case, the trends between 1999 and 2008 need to be further explored.

Influence of process parameters on part quality and mechanical properties for DMLS and SLM with iron-based materials

Rapid manufacturing is an advanced manufacturing technology based on layer-by-layer manufacturing to produce a part. This paper presents experimental work carried out to investigate the effects of scan speed, layer thickness, and building direction on the following part features: dimensional error, surface roughness, and mechanical properties for DMLS with DS H20 powder and SLM with CL 20 powder (1.4404/AISI 316L). Findings were evaluated using ANOVA analysis. According to the experimental results, build direction has a significant effect on part quality, in terms of dimensional error and surface roughness. For the SLM process, the build direction has no influence on mechanical properties. Results of this research support industry estimating part quality and mechanical properties before the production of parts with additive manufacturing, using iron-based powders

Characterizing major avalanche episodes in space and time in the twentieth and early twentyfirst centuries in the Catalan Pyrenees

With the aim of better understanding avalanche risk in the Catalan Pyrenees, the present work focuses on the analysis of major (or destructive) avalanches. For such purpose major avalanche cartography was made by an exhaustive photointerpretation of several flights, winter and summer field surveys and inquiries to local population. Major avalanche events were used to quantify the magnitude of the episodes during which they occurred, and a Major Avalanche Activity Magnitude Index (MAAMI) was developed. This index is based on the number of major avalanches registered and its estimated frequency in a given time period, hence it quantifies the magnitude of a major avalanche episode or winter. Furthermore, it permits a comparison of the magnitude between major avalanche episodes in a given mountain range, or between mountain ranges, and for a long enough period, it should allow analysis of temporal trends. Major episodes from winter 1995/96 to 2013/14 were reconstructed. Their magnitude, frequency and extent were also assessed. During the last 19 winters, the episodes of January 22-23 and February 6-8 in 1996 were those with highest MAAMI values,followed by January 30-31, 2003, January 29, 2006, and January 24-25, 2014. To analyze the whole twentieth century, a simplified MAAMI was defined in order to attain the same purpose with a less complete dataset. With less accuracy, the same parameters were obtained at winter time resolution throughout the twentieth century. Again, 1995/96 winter had the highest MAAMI value followed by 1971/72, 1974/75 and 1937/38 winter seasons. The analysis of the spatial extent of the different episodes allowed refining the demarcation of nivological regions, and improving our knowledge about the atmospheric patterns that cause major episodes and their climatic interpretation. In some cases, the importance of considering a major avalanche episode as the result of a previous preparatory period, followed by a triggering one was revealed.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications