Identification of a BRCA1-mRNA Splicing Complex Required for Efficient DNA Repair and Maintenance of Genomic Stability

Mutations within BRCA1 predispose carriers to a high risk of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through the assembly of multiple protein complexes involved in DNA repair, cell-cycle arrest, and transcriptional regulation. Here, we report the identification of a DNA damage-induced BRCA1 protein complex containing BCLAF1 and other key components of the mRNA-splicing machinery. In response to DNA damage, this complex regulates pre-mRNA splicing of a number of genes involved in DNA damage signaling and repair, thereby promoting the stability of these transcripts/proteins. Further, we show that abrogation of this complex results in sensitivity to DNA damage, defective DNA repair, and genomic instability. Interestingly, mutations in a number of proteins found within this complex have been identified in numerous cancer types. These data suggest that regulation of splicing by the BRCA1-mRNA splicing complex plays an important role in the cellular response to DNA damage.

The use of a dynamic truck-trailer drive-by system to monitor bridge damping

Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck-trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle-bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investigated. In addition, the sensitivity of the approach to the vehicle speed, road roughness class, bridge span length, changes in the equal axle properties and noise is investigated.

Dynamic Axle Force and Road Profile Identification Using a Moving Vehicle

In the interaction between vehicles, pavements and bridges, it is essential to aim towards a reduction of vehicle axle forces to promote longer pavement life spans and to prevent bridges loads becoming too high. Moreover, as the road surface roughness affects the vehicle dynamic forces, an efficient monitoring of pavement condition is also necessary to achieve this aim. This paper uses a novel algorithm to identify the dynamic interaction forces and pavement roughness from vehicle accelerations in both theoretical simulations and a laboratory experiment; moving force identification theory is applied to a vehicle model for this purpose. Theoretical simulations are employed to evaluate the ability of the algorithm to predict forces over a range of bridge spans and to evaluate the influence of road roughness level on the accuracy of the results. Finally, in addressing the challenge for the real-world problem, the effects of vehicle configuration and speed on the predicted road roughness are also investigated in a laboratory experiment.

Theoretical investigation of the use of a moving vehicle to identify bridge dynamic parameters

Pavements and bridges are subject to a continuous degradation due to traffic aggressiveness, ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure in order to provide adequate maintenance and guarantee the required levels of transport service and safety. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamics of bridges. A simplified quarter carbridge interaction model is used in theoretical simulations and the natural frequency of the bridge is extracted from the spectra of the vehicle accelerations. The accuracy is better at lower speeds and for smooth road profiles. The structural damping of the bridge was also monitored for smooth and rough road profiles. The magnitude of peaks in the power spectral density of the vehicle accelerations decreased with increasing bridge damping and this decrease was easier to detect the smoother the road profile.

Mathematical anxiety is linked to reduced cognitive reflection: A potential road from discomfort in the mathematics classroom to susceptibility to biases

Background
When asked to solve mathematical problems, some people experience anxiety and threat, which can lead to impaired mathematical performance (Curr Dir Psychol Sci 11:181–185, 2002). The present studies investigated the link between mathematical anxiety and performance on the cognitive reflection test (CRT; J Econ Perspect 19:25–42, 2005). The CRT is a measure of a person’s ability to resist intuitive response tendencies, and it correlates strongly with important real-life outcomes, such as time preferences, risk-taking, and rational thinking.

Methods
In Experiments 1 and 2 the relationships between maths anxiety, mathematical knowledge/mathematical achievement, test anxiety and cognitive reflection were analysed using mediation analyses. Experiment 3 included a manipulation of working memory load. The effects of anxiety and working memory load were analysed using ANOVAs.

Results
Our experiments with university students (Experiments 1 and 3) and secondary school students (Experiment 2) demonstrated that mathematical anxiety was a significant predictor of cognitive reflection, even after controlling for the effects of general mathematical knowledge (in Experiment 1), school mathematical achievement (in Experiment 2) and test anxiety (in Experiments 1–3). Furthermore, Experiment 3 showed that mathematical anxiety and burdening working memory resources with a secondary task had similar effects on cognitive reflection.

Conclusions
Given earlier findings that showed a close link between cognitive reflection, unbiased decisions and rationality, our results suggest that mathematical anxiety might be negatively related to individuals’ ability to make advantageous choices and good decisions.

A predictive maintenance system for integral type faults based on support vector machines:An application to ion implantation

In semiconductor fabrication processes, effective management of maintenance operations is fundamental to decrease costs associated with failures and downtime. Predictive Maintenance (PdM) approaches, based on statistical methods and historical data, are becoming popular for their predictive capabilities and low (potentially zero) added costs. We present here a PdM module based on Support Vector Machines for prediction of integral type faults, that is, the kind of failures that happen due to machine usage and stress of equipment parts. The proposed module may also be employed as a health factor indicator. The module has been applied to a frequent maintenance problem in semiconductor manufacturing industry, namely the breaking of the filament in the ion-source of ion-implantation tools. The PdM has been tested on a real production dataset. © 2013 IEEE.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

Women's Nightwork :deregulation as a straight road to equality?

The book considers the question whether the traditional prohibition of nightwork for female manual workers could be defended against EU (then: EEC) discrimination law requirements and against the German constitution itself. While I was working on the PhD, German labour law still prohibited manual workers (but not white collar employees, or nurses, or policewomen) from working nights. Just before the thesis was published, the German constitutional court held that the prohibition indeed violates the Constitution, but that it must not be repealed without providing for specific protection against health risks ensuing from night work. The Court thus mainly confirmed the thesis' results. The thesis first considers the history of the legislation (which was based on an ILO convention), and discusses the social and health risks related to night work. It then comes to the conclusion that gender roles imply that women are at a greater risk when working nights, but that there is no biological justification (except during pregnancy of course). The thesis further develops a recommendation, based on the constitutional welfare states principle and the constitutional protection of health, to not just abolish the prohibition, but to provide uplevel equalisation of working conditions for women and men. This was the first time I also tried to work comparatively (not perfect at all), but I have certainly improved since then. An English summary of the thesis was published in the 3rd issue of the Cardozo Women's Law Journal 1996, which was also my first ever publicatin in English

Institutional maintenance work and power preservation in business exchanges: Insights from industrial supplier workshops

This paper aims to offer new theoretical and empirical insights into power dynamics in an industrial supplier workshop setting. Theoretically, it advances an institutional perspective on supplier workshops as an important venue in managing, preserving and instituting industrial market power. Based on a detailed ethnographic analysis of an industrial workshop setting, this article investigates the institutional maintenance work of Retail Co. in preserving the power dynamics of market dominance in business exchanges and market structures. Our findings revealed three previously unreported insights into the subtle, but nonetheless pervasive power from institutional maintenance work in an industrial workshop setting. First, the institutional workshop work comprised a cultural performance; constituting socialization practice through a performance game, the power of numbers in field comprehension and an award ceremony. Second, the institutional workshop work mobilized projective agency, stipulating, directing and appealing for the instituting of distinct market rules and collective identities. Finally, the institutional workshop work increases supplier docility and utility via the regulative technologies-of-the-self to enhance business planning, operations and market decision-making practice, without necessarily being seen to be disciplinarian.

Predictive Maintenance for Improved Sustainability - An Ion Beam Etch Endpoint Detection System Use Case

In modern semiconductor manufacturing facilities maintenance strategies are increasingly shifting from traditional preventive maintenance (PM) based approaches to more efficient and sustainable predictive maintenance (PdM) approaches. This paper describes the development of such an online PdM module for the endpoint detection system of an ion beam etch tool in semiconductor manufacturing. The developed system uses optical emission spectroscopy (OES) data from the endpoint detection system to estimate the RUL of lenses, a key detector component that degrades over time. Simulation studies for historical data for the use case demonstrate the effectiveness of the proposed PdM solution and the potential for improved sustainability that it affords.

An Adaptive Machine Learning Decision System for Flexible Predictive Maintenance

Process monitoring and Predictive Maintenance (PdM) are gaining increasing attention in most manufacturing environments as a means of reducing maintenance related costs and downtime. This is especially true in industries that are data intensive such as semiconductor manufacturing. In this paper an adaptive PdM based flexible maintenance scheduling decision support system, which pays particular attention to associated opportunity and risk costs, is presented. The proposed system, which employs Machine Learning and regularized regression methods, exploits new information as it becomes available from newly processed components to refine remaining useful life estimates and associated costs and risks. The system has been validated on a real industrial dataset related to an Ion Beam Etching process for semiconductor manufacturing.

A new performance based method for design and maintenance of reinforced concrete structures

Best concrete research paper by a student - Research has shown that the cost of managing structures puts high strain on the infrastructure budget, with
estimates of over 50% of the European construction budget being dedicated to repair and maintenance. If reinforced concrete
structures are not suitably designed and adequately maintained, their service life is compromised, resulting in the full economic
value of the investment not realised. The issue is more prevalent in coastal structures as a result of combinations of aggressive
actions, such as those caused by chlorides, sulphates and cyclic freezing and thawing.
It is a common practice nowadays to ensure durability of reinforced concrete structures by specifying a concrete mix and a
nominal cover at the design stage to cater for the exposure environment. This in theory should produce the performance required
to achieve a specified service life. Although the European Standard EN 206-1 specifies variations in the exposure environment,
it does not take into account the macro and micro climates surrounding structures, which have a significant influence on their
performance and service life. Therefore, in order to construct structures which will perform satisfactorily in different exposure
environments, the following two aspects need to be developed: a performance based specification to supplement EN 206-1
which will outline the expected performance of the structure in a given environment; and a simple yet transferrable procedure
for assessing the performance of structures in service termed KPI Theory. This will allow the asset managers not only to design
structures for the intended service life, but also to take informed maintenance decisions should the performance in service fall
short of what was specified. This paper aims to discuss this further.