Influence of boron additions on physical and mechanical properties of arc-melted tungsten and tungsten - 1 percent tantalum alloy

Influence of boron additions on physical and mechanical properties of arc-melted tungsten and of tungsten-tantalum allo

Reverse engineering of CAD models via clustering and approximate implicitization

In applications like computer aided design, geometric models are often represented numerically as polynomial splines or NURBS, even when they originate from primitive geometry. For purposes such as redesign and isogeometric analysis, it is of interest to extract information about the underlying geometry through reverse engineering. In this work we develop a novel method to determine these primitive shapes by combining clustering analysis with approximate implicitization. The proposed method is automatic and can recover algebraic hypersurfaces of any degree in any dimension. In exact arithmetic, the algorithm returns exact results. All the required parameters, such as the implicit degree of the patches and the number of clusters of the model, are inferred using numerical approaches in order to obtain an algorithm that requires as little manual input as possible. The effectiveness, efficiency and robustness of the method are shown both in a theoretical analysis and in numerical examples implemented in Python

Lower-cost tungsten-rhenium alloys

Tungsten-rhenium alloys with a substantially more dilute rhenium content have ductilities and other mechanical properties which compare favorably with the tungsten-rhenium alloys having much higher concentrations of the costly rhenium

Empirical Studies Applied to Software Process Models

Working Group Report: ICSE'99 Workshop on Empirical Studies of Software Development and Evolutio

Effects of Grain Size on the Tensile and Creep Properties of Arc-melted and Electron-beam-melted Tungsten at 2250 Deg to 4140 Deg f

Effects of grain size on tensile and creep properties of arc melted and electron beam melted tungste

High-strength tungsten alloy with improved ductility

Alloy combines superior strength at elevated temperatures with improved ductility at lower temperatures relative to unalloyed tungsten. Composed of tungsten, rhenium, hafnium, and carbon, the alloy is prepared by consumable electrode vacuum arc-melting and can be fabricated into rod, plate, and sheet

What are Hybrid Development Methods Made Of?

Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods-so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. Based on 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods

Housing problems in a changing society. Regulation and training needs in Italy

The paper focuses on the social, economic and environmental trends of recent years in Italy, highlighting the issue of housing emergency, both in quantitative and qualitative terms. What emerges are several shortages in housing especially in the suburbs of large cities, emphasizing the relevance of this issue in terms of health consequences and its priority for the definition of local policies. The authors underline that the availability of accessible and healthy housing is a human right, and a multisectoral responsibility, achievable only if a contribution is made by all relevant sectors including housing, environmental, social welfare, urban planning, building management and public health. The authors conclude by stressing the strategic role of training and illustrating a proposal addressed to all stakeholders, aiming to provide health evidences in terms of impact of housing hazards on health and to describe good building practices, helpful in order to obtain safe and healthy homes

An Adaptive Cognitive Sensor Node for ECG Monitoring in the Internet of Medical Things

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials and healthcare procedures. Cardiovascular diseases monitoring, usually involving electrocardiogram (ECG) traces analysis, is one of the most promising and high-impact applications. Nevertheless, to fully exploit the potential of IoMT in this domain, some steps forward are needed. First, the edge-computing paradigm must be added to the picture. A certain level of near-sensor processing has to be enabled, to improve the scalability, portability, reliability and responsiveness of the IoMT nodes. Second, novel, increasingly accurate data analysis algorithms, such as those based on artificial intelligence and Deep Learning, must be exploited. To reach these objectives, designers, and programmers of IoMT nodes, have to face challenging optimization tasks, in order to execute fairly complex computing tasks on low-power wearable and portable processing systems, with tight power and battery lifetime budgets. In this work, we explore the implementation of a cognitive data analysis algorithm, based on a convolutional neural network trained to classify ECG waveforms, on a resource-constrained microcontroller-based computing platform. To minimize power consumption, we add an adaptivity layer that dynamically manages the hardware and software configuration of the device to adapt it at runtime to the required operating mode. Our experimental results show that adapting the node setup to the workload at runtime can save up to 50% power consumption. Our optimized and quantized neural network reaches an accuracy value higher than 97% for arrhythmia disorders detection on MIT-BIH Arrhythmia dataset

Electrically-assisted bikes: potential impacts on travel behaviour

This paper reports on a review of the European literature about the impacts of having an electrically-assisted bike available to use, together with results from a trial in the UK city of Brighton, where 80 employees were loaned an electrically-assisted bike for a 6–8 week period. In the Brighton trial, three-quarters of those who were loaned an e-bike used them at least once a week. Across the sample as a whole, average usage was in the order of 15–20 miles per week, and was accompanied by an overall reduction in car mileage of 20%. At the end of the trial, 38% participants expected to cycle more in the future, and at least 70%said that they would like to have an e-bike available for use in the future, and would cycle more if this was the case. This is consistent with the results of the European literature which shows that when e-bikes are made available, they get used; that a proportion of e-bike trips typically substitutes for car use; and that many people who take part in trials become interested in future e-bike use, or cycling more generall