Substantiation of the allowable measurement error when controlling deviations of the shape and lication of the surfaces of parts

Criteria for choosing measuring instruments for controlling deviations in the shape and location of surfaces of parts are theorerically substantiated, taking into account the formula for their calculation as a result of indirect measurements. The allowable measurement errors and limiting errors of measuring instruments for monitoring the deviation of the shape and location of the surfaces of new parts of Yaroslavl Motor Plant engines were determined. Keywords: control, indirect measurements, error, deviations of the shape and location of surfaces, measuring instruments, allowable error. [email protected]

MODELING OF BILATERAL END-FINISHING KINEMATIC CHARACTERISTICS

The paper is dedicated to the bilateral end-finishing improvement at the expense of efficient kinematic characteristics realization in parts machined ensuring limiting errors minimization in end surfaces. A systematization of parts rotation experimental characteristics is carried out. It is shown that they may be referred to six basic kinds. There are offered equivalent characteristics of rotation used while grinding modeling and their mathematical description is given. The dependences obtained determine a kinematic parameter of a shaping form in the equation of the surface worked. There is considered an influence of billet rotation characteristics upon shaping and accuracy of frictionless bearing cylindrical roller machining under virtual technological conditions equivalent to industrial. As a result of computer experiments carried out it is defined that dynamics and balance of shape errors and a relative position of end surfaces of the roller to a considerable extent are defined with the kind of realized rotation characteristics. The error sensitivity of a shape and end beating to kinematic characteristics realized and technological parameters must be taken into account during bilateral end-finishing control.

Why We Don’t See Race: How Australia Has Overlooked Race as an Influence on Miscarriages of Justice

While criminal justice systems are increasingly prepared to identify and overturn wrongful convictions, the focus of limiting errors has centered upon commonly accepted “causal factors” of wrongful conviction. Importantly, there has been limited work that has explored the question of who is most vulnerable to fall victim to this error. We explore three landmark case studies highlighting wrongful convictions in Australia where race, racialized policing, or racism were crucial yet unresolved issues leading to an erroneous conviction. These cases and the absence of resolutions of these racialized issues in these convictions typify the inadequacies of Australian approaches to wrongful conviction. We argue that to achieve justice in Australia we must not be limited to the causal factors that have come to define American innocence and should support greater acknowledgment of how race and ethnicity influence wrongful conviction.

Visualisation and analysis of RNA-Seq assembly graphs

RNA-sequencing (RNA-Seq) is a powerful transcriptome profiling technology enabling transcript discovery and quantification. RNA-Seq data are large, and most commonly used as a source of genelevel quantification measurements, whilst the underlying assemblies of reads, if inspected, are usually viewed as sequence reads mapped on to a reference genome. Whilst sufficient for many needs, when the underlying transcript assemblies are complex, this visualisation approach can be limiting; errors in assembly can be difficult to spot and interpretation of splicing events is challenging.Here we report on the development of a graph-based visualisation method as a complementary approach to understanding transcript diversity and read assembly from short-read RNA-Seq data. Following the mapping of reads to the reference genome, read-to-read comparison is performed on all reads mapping to a given gene, producing a matrix of weighted similarity scores between reads. This is used to produce an RNA assembly graph where nodes represent reads derived from a cDNA and edges similarity scores between reads, above a defined threshold. Visualisation of resulting graphs is performed using Graphia Professional. This tool can render the often large and complex graph topologies that result from DNA/RNA sequence assembly in 3D space and supports info rmatio no verlay on to nodes, e.g. transcript models. We have also implemented an analysis pipeline for the creation of RNA assembly graphs with both a command-line and web-based interface that allows users to create and visualise these data. Here we demonstrate the utility of this approach on RNA-Seq data, including the unusual structure of these graphs and how they can be used to identify issues in assembly, repetitive sequences within transcripts and splice variants. We believe this approach has the potential to significantly improve our understanding of transcript complexity.

Avoiding accuracy-limiting pitfalls in the study of protein-ligand interactions with isothermal titration calorimetry

Isothermal titration calorimetry (ITC) can yield precise (±3%) estimates of the thermodynamic parameters describing biomolecular association (affinity, enthalpy, and entropy), making it an indispensable tool for biochemistry and drug discovery. Surprisingly, interlaboratory comparisons suggest that errors of ∼20% are common and widely underreported. Here, we show how to reduce precision- and accuracy-limiting errors while obtaining good estimates and minimizing material and time consumed by an experiment. We provide a simple spreadsheet that allows practitioners to identify precision-limiting operations during protocol design, track precision during the experiment, and propagate error to yield realistic final uncertainties.

Stress and strain measurements in static tensile tests

The paper deals with the accuracy of measurements of strains (elongation and necking) and stresses (tensile strength) in static room-temperature tensile strength tests. We present methods for calculating measurement errors and uncertainties, and discuss the determination of the limiting errors of the quantities measured for circular and rectangular specimens, which is illustrated with examples.

Celestial reference frames at multiple radio wavelengths

In 1997 the IAU adopted the International Celestial Reference Frame (ICRF) built from S/X VLBI data. In response to IAU resolutions encouraging the extension of the ICRF to additional frequency bands, VLBI frames have been made at 24, 32, and 43 GHz. Meanwhile, the 8.4 GHz work has been greatly improved with the 2009 release of the ICRF-2. This paper discusses the motivations for extending the ICRF to these higher frequency radio bands. Results to date will be summarized including evidence that the high frequency frames are rapidly approaching the accuracy of the 8.4 GHz ICRF-2. We discuss current limiting errors and prospects for the future accuracy of radio reference frames. We note that comparison of multiple radio frames is characterizing the frequency dependent systematic noise floor from extended source morphology and core shift. Finally, given Gaia's potential for high accuracy optical astrometry, we have simulated the precision of a radio-optical frame tie to be ~10–15 μas (1-σ, per component).

Performance of Five Models to Predict the Naturalization of Non-Native Woody Plants in Iowa

Use of risk-assessment models that can predict the naturalization and invasion of non-native woody plants is a potentially beneficial approach for protecting human and natural environments. This study validates the power and accuracy of four risk-assessment models previously tested in Iowa, and examines the performance of a new random forest modeling approach. The random forest model was fitted with the same data used to develop the four earlier risk-assessment models. The validation of all five models was based on a new set of 11 naturalizing and 18 non-naturalizing species in Iowa. The fitted random forest model had a high classification rate (92.0%), no biologically significant errors (accepting a plant that has a high risk of naturalizing), and few horticulturally limiting errors (rejecting a plant that has a low risk of naturalizing) (8.7%). Classification rates for validation of all five models ranged from 62.1 to 93.1%. Horticulturally limiting errors for the four models previously developed for Iowa ranged from 11.1 to 38.5%, and biologically significant errors from 4.2 to 18.5%. Because of the small sample size, few classification and error rate results were significantly different from the original tests of the models. Overall, the random forest model shows promise for powerful and accurate risk-assessment, but mixed results for the other models suggest a need for further refinement.