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.

A novel approach to analysing the regimes of temporary streams in relation to their controls on the composition and structure of aquatic biota

Temporary streams are those water courses that undergo the recurrent cessation of flow or the complete drying of their channel. The structure and composition of biological communities in temporary stream reaches are strongly dependent on the temporal changes of the aquatic habitats determined by the hydrological conditions. Therefore, the structural and functional characteristics of aquatic fauna to assess the ecological quality of a temporary stream reach cannot be used without taking into account the controls imposed by the hydrological regime. This paper develops methods for analysing temporary streams' aquatic regimes, based on the definition of six aquatic states that summarize the transient sets of mesohabitats occurring on a given reach at a particular moment, depending on the hydrological conditions: Hyperrheic, Eurheic, Oligorheic, Arheic, Hyporheic and Edaphic. When the hydrological conditions lead to a change in the aquatic state, the structure and composition of the aquatic community changes according to the new set of available habitats. We used the water discharge records from gauging stations or simulations with rainfall-runoff models to infer the temporal patterns of occurrence of these states in the Aquatic States Frequency Graph we developed. The visual analysis of this graph is complemented by the development of two metrics which describe the permanence of flow and the seasonal predictability of zero flow periods. Finally, a classification of temporary streams in four aquatic regimes in terms of their influence over the development of aquatic life is updated from the existing classifications, with stream aquatic regimes defined as Permanent, Temporary-pools, Temporary-dry and Episodic. While aquatic regimes describe the long-term overall variability of the hydrological conditions of the river section and have been used for many years by hydrologists and ecologists, aquatic states describe the availability of mesohabitats in given periods that determine the presence of different biotic assemblages. This novel concept links hydrological and ecological conditions in a unique way. All these methods were implemented with data from eight temporary streams around the Mediterranean within the MIRAGE project. Their application was a precondition to assessing the ecological quality of these streams.

Value perceptions of measurement and monitoring system customers

The value that the customer perceives from a supplier’s offering, impacts customer’s decision making and willingness to pay at the time of the purchase, and the overall satisfaction. Thus, for a business supplier, it is critical to understand their customers’ value perceptions. The objective of this thesis is to understand what measurement and monitoring system customers value, by examining their key purchasing criteria and perceived benefits. Theoretical part of this study consists on reviewing relevant literature on organizational buying behavior and customer perceived value. This study employs a qualitative interview research method. The empirical part of this research consisted of conducting 20 in-depth interviews with life science customers in USA and in Europe. Quality and technical features are the most important purchasing criteria, while product-related benefits seem to be the most important perceived benefits. At the marketing of the system, the emphasis should be at which regulations the system complies with, references of supplier’s prior experience, the reliability and usability of the system, and total costs. The benefits that should be emphasized are the better control of customer’s process, and the proof of customer’s product quality

Development of Measurement Systems in Scientific Research: Case Study

In recent years, technological advancements in microelectronics and sensor technologies have revolutionized the field of electrical engineering. New manufacturing techniques have enabled a higher level of integration that has combined sensors and electronics into compact and inexpensive systems. Previously, the challenge in measurements was to understand the operation of the electronics and sensors, but this has now changed. Nowadays, the challenge in measurement instrumentation lies in mastering the whole system, not just the electronics. To address this issue, this doctoral dissertation studies whether it would be beneficial to consider a measurement system as a whole from the physical phenomena to the digital recording device, where each piece of the measurement system affects the system performance, rather than as a system consisting of small independent parts such as a sensor or an amplifier that could be designed separately. The objective of this doctoral dissertation is to describe in depth the development of the measurement system taking into account the challenges caused by the electrical and mechanical requirements and the measurement environment. The work is done as an empirical case study in two example applications that are both intended for scientific studies. The cases are a light sensitive biological sensor used in imaging and a gas electron multiplier detector for particle physics. The study showed that in these two cases there were a number of different parts of the measurement system that interacted with each other. Without considering these interactions, the reliability of the measurement may be compromised, which may lead to wrong conclusions about the measurement. For this reason it is beneficial to conceptualize the measurement system as a whole from the physical phenomena to the digital recording device where each piece of the measurement system affects the system performance. The results work as examples of how a measurement system can be successfully constructed to support a study of sensors and electronics.

Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Motor brain regions are involved in the encoding of delayed intentions: a fMRI study

In studies of prospective memory, recall of the content of delayed intentions is normally excellent, probably because they contain actions that have to be enacted at a later time. Action words encoded for later enactment are more accessible from memory than those encoded for later verbal report [Freeman, J.E., and Ellis, J.A. 2003a. The representation of delayed intentions: A prospective subject-performed task? Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 976-992.]. As this higher assessibility is lost when the intended actions have to be enacted during encoding, or when a motor interference task is introduced concurrent to intention encoding, Freeman and Ellis suggested that the advantage of to-be-enacted actions is due to additional preparatory motor operations during encoding. Accordingly, in a fMRI study with 10 healthy young participants, we investigated whether motor brain regions are differentially activated during verbal encoding of actions for later enactment with the right hand in contrast to verbal encoding of actions for later verbal report. We included an additional condition of verbal encoding of abstract verbs for later verbal report to investigate whether the semantic motor information inherent in action verbs in contrast to abstract verbs activates motor brain regions different from those involved in the verbal encoding of actions for later enactment. Differential activation for the verbal encoding of to-be-enacted actions in contrast to to-be-reported actions was found in brain regions known to be involved in covert motor preparation for hand movements, i.e. the postcentral gyrus, the precuneus, the dorsal and ventral premotor cortex, the posterior middle temporal gyrus and the inferior parietal lobule. There was no overlap between these brain regions and those differentially activated during the verbal encoding of actions in contrast to abstract verbs for later verbal report. Consequently, the results of this fMRI study suggest the presence of preparatory motor operations during the encoding of delayed intentions requiring a future motor response, which cannot be attributed to semantic information inherent to action verbs. (c) 2006 Elsevier B.V. All rights reserved.

A review of measurement-based assessments of the aerosol direct radiative effect and forcing

Aerosols affect the Earth's energy budget directly by scattering and absorbing radiation and indirectly by acting as cloud condensation nuclei and, thereby, affecting cloud properties. However, large uncertainties exist in current estimates of aerosol forcing because of incomplete knowledge concerning the distribution and the physical and chemical properties of aerosols as well as aerosol-cloud interactions. In recent years, a great deal of effort has gone into improving measurements and datasets. It is thus feasible to shift the estimates of aerosol forcing from largely model-based to increasingly measurement-based. Our goal is to assess current observational capabilities and identify uncertainties in the aerosol direct forcing through comparisons of different methods with independent sources of uncertainties. Here we assess the aerosol optical depth (τ), direct radiative effect (DRE) by natural and anthropogenic aerosols, and direct climate forcing (DCF) by anthropogenic aerosols, focusing on satellite and ground-based measurements supplemented by global chemical transport model (CTM) simulations. The multi-spectral MODIS measures global distributions of aerosol optical depth (τ) on a daily scale, with a high accuracy of ±0.03±0.05τ over ocean. The annual average τ is about 0.14 over global ocean, of which about 21%±7% is contributed by human activities, as estimated by MODIS fine-mode fraction. The multi-angle MISR derives an annual average AOD of 0.23 over global land with an uncertainty of ~20% or ±0.05. These high-accuracy aerosol products and broadband flux measurements from CERES make it feasible to obtain observational constraints for the aerosol direct effect, especially over global the ocean. A number of measurement-based approaches estimate the clear-sky DRE (on solar radiation) at the top-of-atmosphere (TOA) to be about -5.5±0.2 Wm-2 (median ± standard error from various methods) over the global ocean. Accounting for thin cirrus contamination of the satellite derived aerosol field will reduce the TOA DRE to -5.0 Wm-2. Because of a lack of measurements of aerosol absorption and difficulty in characterizing land surface reflection, estimates of DRE over land and at the ocean surface are currently realized through a combination of satellite retrievals, surface measurements, and model simulations, and are less constrained. Over the oceans the surface DRE is estimated to be -8.8±0.7 Wm-2. Over land, an integration of satellite retrievals and model simulations derives a DRE of -4.9±0.7 Wm-2 and -11.8±1.9 Wm-2 at the TOA and surface, respectively. CTM simulations derive a wide range of DRE estimates that on average are smaller than the measurement-based DRE by about 30-40%, even after accounting for thin cirrus and cloud contamination. A number of issues remain. Current estimates of the aerosol direct effect over land are poorly constrained. Uncertainties of DRE estimates are also larger on regional scales than on a global scale and large discrepancies exist between different approaches. The characterization of aerosol absorption and vertical distribution remains challenging. The aerosol direct effect in the thermal infrared range and in cloudy conditions remains relatively unexplored and quite uncertain, because of a lack of global systematic aerosol vertical profile measurements. A coordinated research strategy needs to be developed for integration and assimilation of satellite measurements into models to constrain model simulations. Enhanced measurement capabilities in the next few years and high-level scientific cooperation will further advance our knowledge.

Valorisation of side streams from wheat milling and confectionery industries for consolidated production and extraction of microbial lipids

Crude enzymes produced via solid state fermentation (SSF) using wheat milling by-products have been employed for both fermentation media production using flour-rich waste (FRW) streams and lysis of Rhodosporidium toruloides yeast cells. Filter sterilization of crude hydrolysates was more beneficial than heat sterilization regarding yeast growth and microbial oil production. The initial carbon to free amino nitrogen ratio of crude hydrolysates was optimized (80.2 g/g) in fed-batch cultures of R. toruloides leading to a total dry weight of 61.2 g/L with microbial oil content of 61.8 % (w/w). Employing a feeding strategy where the glucose concentration was maintained in the range of 12.2 – 17.6 g/L led to the highest productivity (0.32 g/L∙h). The crude enzymes produced by SSF were utilised for yeast cell treatment leading to simultaneous release of around 80% of total lipids in the broth and production of a hydrolysate suitable as yeast extract replacement.

Effect of measurement error and autocorrelation on the (X)over-bar chart

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)