Mechanical and structural assessment of laboratory- and field-compacted asphalt mixtures

Compaction forms an integral part in the formation of the aggregate orientation and structure of an asphalt mixture and therefore has a profound influence on its final volumetric and mechanical performance. This article describes the influence of various forms of laboratory (gyratory, vibratory and slab-roller) and field compaction on the internal structure of asphalt specimens and subsequently on their mechanical properties, particularly stiffness and permanent deformation. A 2D image capturing and image analysis system has been used together with alternative specimen sizes and orientations to quantify the internal aggregate structure (orientation and segregation) for a range of typically used continuously graded asphalt mixtures. The results show that in terms of aggregate orientation, slab-compacted specimens tend to mimic field compaction better than gyratory and vibratory compaction. The mechanical properties of slab-compacted specimens also tend to be closer to that of field cores. However, the results also show that through careful selection of specimen size, specimen orientation and compaction variables, even mould-based compaction methods can be utilised with particular asphalt mixtures to represent field-compacted asphalt mixtures

Innovation for an inclusive future

This workshop will focus on setting the agenda for research, practice and policy in support of inclusive design for third generation computer-based products. The next generation of technology represents an unprecedented opportunity to improve the quality of life for groups of users who have previously faced exclusion, such as those with impairments and older citizens. At the same time it risks creating a greater digital divide and further exclusion. How we approach design for this new generation will determine whether or not the third wave will provide positive advances towards an inclusive digital world. We therefore need to put forward both a rationale for inclusive design and provide pointers towards technical development and design practice in support of inclusion. It is our belief that there is not only a strong moral case for design for inclusion but also significant commercial incentive, which may be key to persuading influential players to focus on inclusion. Therefore one of our key objectives is to describe and promote the advantages of designing ‘in from the edges’ of the user population rather than designing for a notional ‘average’ user

Extrapolation for Time-Series and Cross-Sectional Data

Extrapolation methods are reliable, objective, inexpensive, quick, and easily automated. As a result, they are widely used, especially for inventory and production forecasts, for operational planning for up to two years ahead, and for long-term forecasts in some situations, such as population forecasting. This paper provides principles for selecting and preparing data, making seasonal adjustments, extrapolating, assessing uncertainty, and identifying when to use extrapolation. The principles are based on received wisdom (i.e., experts’ commonly held opinions) and on empirical studies. Some of the more important principles are:• In selecting and preparing data, use all relevant data and adjust the data for important events that occurred in the past.• Make seasonal adjustments only when seasonal effects are expected and only if there is good evidence by which to measure them.• In extrapolating, use simple functional forms. Weight the most recent data heavily if there are small measurement errors, stable series, and short forecast horizons. Domain knowledge and forecasting expertise can help to select effective extrapolation procedures. When there is uncertainty, be conservative in forecasting trends. Update extrapolation models as new data are received.• To assess uncertainty, make empirical estimates to establish prediction intervals.• Use pure extrapolation when many forecasts are required, little is known about the situation, the situation is stable, and expert forecasts might be biased

Multi-step time series prediction intervals using neuroevolution

Multi-step time series forecasting (TSF) is a crucial element to support tactical decisions (e.g., designing production or marketing plans several months in advance). While most TSF research addresses only single-point prediction, prediction intervals (PIs) are useful to reduce uncertainty related to important decision making variables. In this paper, we explore a large set of neural network methods for multi-step TSF and that directly optimize PIs. This includes multi-step adaptations of recently proposed PI methods, such as lower--upper bound estimation (LUBET), its ensemble extension (LUBEXT), a multi-objective evolutionary algorithm LUBE (MLUBET) and a two-phase learning multi-objective evolutionary algorithm (M2LUBET). We also explore two new ensemble variants for the evolutionary approaches based on two PI coverage--width split methods (radial slices and clustering), leading to the MLUBEXT, M2LUBEXT, MLUBEXT2 and M2LUBEXT2 methods. A robust comparison was held by considering the rolling window procedure, nine time series from several real-world domains and with different characteristics, two PI quality measures (coverage error and width) and the Wilcoxon statistic. Overall, the best results were achieved by the M2LUBET neuroevolution method, which requires a reasonable computational effort for time series with a few hundreds of observations.This article is a result of the project NORTE-01- 0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). We would also like to thank the anonymous reviewers for their helpful suggestionsinfo:eu-repo/semantics/publishedVersio

ACL injuries identifiable for pre-participation imagiological analysis: Risk factors

Identification of pre-participation risk factors for noncontact anterior cruciate ligament (ACL) injuries has been attracting a great deal of interest in the sports medicine and traumatology communities. Appropriate methods that enable predicting which patients could benefit from pre- ventive strategies are most welcome. This would enable athlete-specific training and conditioning or tailored equipment in order to develop appropriate strategies to reduce incidence of injury. In order to accomplish these goals, the ideal system should be able to assess both anatomic and functional features. Complementarily, the screening method must be cost-effective and suited for widespread application. Anatomic study protocol requiring only standard X rays could answer some of such demands. Dynamic MRI/CT evaluation and electronically assisted pivot-shift evaluation can be powerful tools providing complementary information. These upcoming insights, when validated and properly combined, envision changing pre-participation knee examination in the near future. Herein different methods (validated or under research) aiming to improve the capacity to identify persons/athletes with higher risk for ACL injury are overviewed.

Sources of stakeholder salience in the responsible investment movement: why do investors sign the Principles for Responsible Investment?

Since its inception in 2006, the United Nations-backed Principles for Responsible Investment (PRI) have grown to over 1300 signatories representing over $45 trillion. This growth is not slowing down. In this paper, we argue that there is a set of attributes which make the PRI salient as a stakeholder and its claim to sign the six PRI important to institutional investors. We use Mitchell et al.’s (Acad Manag Rev 22:853–886, 1997) theoretical framework of stakeholder salience, as extended by Gifford (J Bus Eth 92:79–97, 2010). We use as evidence confidential data from the annual survey of signatories carried out by the PRI in a 5-year period between 2007 and 2011. The findings highlight pragmatic and organizational legitimacy, normative and utilitarian power, and management values as the attributes that contribute most to the salience of the PRI as a stakeholder

Rotational knee laxity: Reliability of a simple measurement device in vivo

<p>Abstract</p> <p>Background</p> <p>Double bundle ACL reconstruction has been demonstrated to decrease rotational knee laxity. However, there is no simple, commercially-available device to measure knee rotation. The investigators developed a simple, non-invasive device to measure knee rotation. In conjunction with a rigid boot to rotate the tibia and a force/moment sensor to allow precise determination of torque about the knee, a magnetic tracking system measures the axial rotation of the tibia with respect to the femur. This device has been shown to have acceptable levels of test re-test reliability to measure knee rotation in cadaveric knees.</p> <p>Methods</p> <p>The objective of this study was to determine reliability of the device in measuring knee rotation of human subjects. Specifically, the intra-tester reliability within a single testing session, test-retest reliability between two testing sessions, and inter-tester reliability were assessed for 11 male subjects with normal knees.</p> <p>Results</p> <p>The 95% confidence interval for rotation was less than 5° for intra-tester, test-retest, and inter-tester reliability, and the standard error of measurement for the differences between left and right knees was found to be less than 3°.</p> <p>Conclusion</p> <p>It was found that the knee rotation measurements obtained with this device have acceptable limits of reliability for clinical use and interpretation.</p

Barriers to Predicting the Mechanisms and Risk Factors of Non-Contact Anterior Cruciate Ligament Injury

High incidences of non-contact anterior cruciate ligament (ACL) injury, frequent requirements for ACL reconstruction, and limited understanding of ACL mechanics have engendered considerable interest in quantifying the ACL loading mechanisms. Although some progress has been made to better understand non-contact ACL injuries, information on how and why non-contact ACL injuries occur is still largely unavailable. In other words, research is yet to yield consensus on injury mechanisms and risk factors. Biomechanics, video analysis, and related study approaches have elucidated to some extent how ACL injuries occur. However, these approaches are limited because they provide estimates, rather than precise measurements of knee - and more specifically ACL - kinematics at the time of injury. These study approaches are also limited in their inability to simultaneously capture many of the contributing factors to injury

Forecasting: theory and practice

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases