Report on the AFRIMETS.M. F-S1 supplementary force comparison for 10 kN and 100 kN

Main text This bilateral comparison of Force Standard Machines (FSM) named AFRIMETS.M. F-S1 was carried out in the force range from 1 kN to 100 kN between Physikalisch-Technische Bundesanstalt (PTB) of Germany as the pilot laboratory and Kenya Bureau of Standards (KEBS) of Kenya as the participant laboratory. KEBS had already participated in the APMP.M. F-K2 key comparison where measurements were made only at 50 kN and 100 kN force steps. Therefore, this bilateral comparison was planned to thoroughly compare the KEBS FSM and the PTB Deadweight Machines in wider force steps than those of the APMP.M. F-K2 key comparison and thus it had no corresponding key-comparisons values to be linked to at that time. PTB provided two force transducers for the supplementary comparison with 10 kN and 100 kN nominal capacities. The comparison method called "DKD" procedure was used. This procedure has already been used in several comparisons in Germany and other countries. The purpose to this comparison is to give support to the uncertainty claims for KEBS and will be used to determine the Calibration and Measurement Capability (CMC). In addition, this comparison will provide metrological proof of the application for a CMC entry in the BIPM Key Comparison Database (KCDB). This report describes the scheme and results of the comparison. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Digital Representation of Measurement Uncertainty: A Case Study Linking an RMO Key Comparison with a CIPM Key Comparison

This paper considers a future scenario in which digital reporting of measurement results is ubiquitous and digital calibration certificates (DCCs) contain information about the components of uncertainty in a measurement result. The task of linking international measurement comparisons is used as a case study to look at the benefits of digitalization. Comparison linking provides a context in which correlations are important, so the benefit of passing a digital record of contributions to uncertainty along a traceability chain can be examined. The International Committee for Weights and Measures (CIPM) uses a program of international “key comparisons” to establish the extent to which measurements of a particular quantity may be considered equivalent when made in different economies. To obtain good international coverage, the results of the comparisons may be linked together: a number of regional metrology organization (RMO) key comparisons can be linked back to an initial CIPM key comparison. Specific information about systematic effects in participants’ results must be available during linking to allow correct treatment of the correlations. However, the conventional calibration certificate formats used today do not provide this: participants must submit additional data, and the report of an initial comparison must anticipate the requirements for future linking. Special handling of additional data can be laborious and prone to error. An uncertain-number digital reporting format was considered in this case study, which caters to all the information required and would simplify the comparison analysis, reporting, and linking; the format would also enable a more informative presentation of comparison results. The uncertain-number format would be useful more generally, in measurement scenarios where correlations arise, so its incorporation into DCCs should be considered. A full dataset supported by open-source software is available.

Digitalization of the reporting of key comparisons for radionuclide metrology

The Bureau International des Poids et Mesures (BIPM) operates an international reference system (the SIR) to compare primary standards of radioactivity realized by National Metrology Institutes (NMIs). Recently, the way of managing data relating to this system has been redesigned. The new model is fully integrated into the SI digital transformation initiated by the metrology community. The new approach automates the production of reports on the results from key comparison exercises for publication in the Key Comparison DataBase (KCDB), aiming to reduce the time needed to prepare reports without impacting quality. In operation for a year, the new system has produced 12 comparison reports within deadlines at a quality that meets the needs of the stakeholders in radionuclide metrology. The database and the software are controlled using the states-of-the-art Git version control system. In addition, thanks to the machine-readable database it produces, it paves the way for more digital data exchanges meeting the FAIR principles and directly accessible through a new Application Programming Interface (API) that is under development.

Advancing a Five-Level Typology of Homelessness Prevention

This paper aims to demonstrate the efficacy of a five-level homelessness prevention typology, encompassing universal, targeted, crisis, emergency, and recovery categories. We argue that this typology can be deployed to illuminate key comparisons in homelessness prevention policy and practice between different jurisdictions and over time. Meanwhile, it avoids the confusions and overlaps that occur in extant categorisations. Using the UK jurisdictions as an empirical testbed for this analytical framework, four key lessons emerge which we contend have resonance across much of the global north. First, though there is growing evidence of the importance of both universal prevention measures (particularly the delivery of affordable housing and poverty reduction), and targeted preventative interventions (focused on high risk groups and transitions), practical action on both fronts has been deeply deficient to date. Second, and more encouragingly, there is a nascent shift in homelessness practice from an overwhelming focus on basic, emergency interventions, towards more upstream attempts to avert the kind of crisis situations that can lead to homelessness arising in the first place. Third, and also welcome, is a trend within recovery interventions from treatment-led to more housing-led models, albeit that this shift has been frustratingly slow to materialise in many countries. Fourth, across all of these categories of homelessness prevention, there remain substantial evidence gaps, especially outside of the US.

Integrated neurosymbolic decision support systems: problems and opportunities

The current problem of developing new kinds of decision support systems for different categories of management personnel is addressed in this study. A critical feature of such systems is their distributed and decentralized nature, which enables the construction of next-generation information systems in the form of Multi-Agent Systems, Internet of Things, or Fog Computing Architectures. Parallel models of the dynamics of artificial neural networks are produced under such realistic circumstances, demonstrating their potential for addressing a variety of issues. The purpose of this study is to conduct a critical analysis of the problem of integrating Artificial Neural Networks with decision support systems using a corpus of relevant scholarly literature. To tackle this question, the Design Science Research methodology was considered. According to this methodology, a literary search strategy was established, scientific literature was collected and analyzed, and key comparisons between different solutions were emphasized. The study resulted in the presentation of the most important findings, outstanding issues, and potential areas of fundamental and applied solutions. A consistent trend toward the development of decision support systems based on integrated neural-network methods has been observed, which is efficient and cost-effective since it enables the creation of distributed and trainable decision support systems.

The Texas flood registry: a flexible tool for environmental and public health practitioners and researchers

Background Making landfall in Rockport, Texas in August 2017, Hurricane Harvey resulted in unprecedented flooding, displacing tens of thousands of people, and creating environmental hazards and exposures for many more. Objective We describe a collaborative project to establish the Texas Flood Registry to track the health and housing impacts of major flooding events. Methods Those who enroll in the registry answer retrospective questions regarding the impact of storms on their health and housing status. We recruit both those who did and did not flood during storm events to enable key comparisons. We leverage partnerships with multiple local health departments, community groups, and media outlets to recruit broadly. We performed a preliminary analysis using multivariable logistic regression and a binomial Bayesian conditional autoregressive (CAR) spatial model. Results We find that those whose homes flooded, or who came into direct skin contact with flood water, are more likely to experience a series of self-reported health effects. Median household income is inversely related to adverse health effects, and spatial analysis provides important insights within the modeling approach. Significance Global climate change is likely to increase the number and intensity of rainfall events, resulting in additional health burdens. Population-level data on the health and housing impacts of major flooding events is imperative in preparing for our planet’s future.

The measurements results adjustment by the Least Square Method

The method for processing of the measurement results obtained from Comite International des Poids et Measures (CIPM) Key, Regional Metrology Organizations (RMO) or supplementary comparisons, from the proficiency testing by interlaboratory comparisons and the calibrations is proposed. It is named by authors as adjustment by least square method (LSM). Additive and multiplicative parameters for each measuring standard of every particular laboratory will be the results of this adjustment. As well as the parameters for each artifact. The parameters of the measurements standards are their additive and multiplicative degrees of equivalence from the comparison and the estimations of the systematic errors (biases) from calibrations. The parameters of the artifacts are the key comparisons reference value from the comparison and the assigned quantity values from the calibrations. The adjustment is considered as a way to solving a problem of processing the great amount of homogeneous measurements with many measuring standards at a different comparison levels (CIPM, RMO or supplementary), including connected problems. Four different cases of the adjustments are considered. The first one is a free case of adjustment. It was named so because of the fact that none of participants has any advantage except their uncertainties of measurements. The second one is a fixed case of adjustment. Measuring results of RMO and supplementary comparisons are rigidly linked to additive and multiplicative parameters of measuring standards of particular laboratories participated in CIPM key comparisons. The third one is a case of adjustment with dependent equations. This one is not so rigidly linked of the new comparisons results to previous or to some other comparisons as for fixed case. It means that the new results of comparisons are influenced by the known additive and multiplicative parameters and vice versa. The fourth one is a free case of adjustment with additional summary equations. In that case certain checking equations are added to the system of equations. So, the sum of parameters multiplied by their weights of all measurement standards for particular laboratories participated in comparisons should be equal to zero.

Decision Tree for Key Comparisons

This contribution describes a Decision Tree intended to guide the selection of statistical models and data reduction procedures in key comparisons (KCs). The Decision Tree addresses a specific need of the Inorganic Analysis Working Group (IAWG) of the Consultative Committee (CC) for Amount of Substance, Metrology in Chemistry and Biology (CCQM), of the International Committee for Weights and Measures (CIPM), and it is likely to address similar needs of other working groups and consultative committees. Because the portfolio of KCs previously organized by the CCQM-IAWG affords a full range of opportunities to demonstrate the capabilities of the Decision Tree, the majority of the illustrative examples of application of the Decision Tree are from this working group. However, the Decision Tree is widely applicable in other areas of metrology, as illustrated in examples of application to measurements of radionuclides and of the efficiency of a thermistor power sensor. The Decision Tree is intended for use after choices will have been made about the measurement results that qualify for inclusion in the calculation of the key comparison reference value (KCRV), and about the measurement results for which degrees of equivalence should be produced. Both these choices should be based on substantive considerations, not on purely statistical criteria. However, the Decision Tree does not require that the measurement results selected for either purpose be mutually consistent. The Decision Tree should be used as a guide, not as the sole and autonomous determinant of the model that should be selected for the measurement results obtained in a KC, or of the procedure that should be employed to reduce these results. The scientists running the KCs ultimately have the freedom and responsibility to make the corresponding choices that they deem most appropriate and that best fit the purpose of each KC. The Decision Tree involves three statistical tests, and comprises five terminal leaves, which correspond to as many alternative ways in which the KCRV, its associated uncertainty, and the degrees of equivalence (DoEs) may be computed. This contribution does not purport to suggest that any of the KCRVs, associated uncertainties, or DoEs, presented in previously approved final reports issued by working groups of the CCs should be modified. Neither do the alternative results question existing, demonstrated calibration and measurement capabilities (CMCs), nor do they support any new CMCs.