Raman spectroscopy characterization of diamond films on steel substrates with titanium carbide arc-plated interlayer

Diamond chemical vapour deposition (CVD) on steel represents a difficult task. The major problem is represented by large diffusion of carbon into steel at CVD temperatures. This leads to very low diamond nucleation and degradation of steel microstructure and properties. Recent work [R. Polini, F. Pighetti Mantini, M. Braic, M. Amar, W Ahmed, H. Taylor, Thin Solid Films 494 (2006) 116] demonstrated that well-adherent diamond films can be grown on high-speed steels by using a TiC interlayer deposited by the PVD-arc technique. The resulting multilayer (TiC/ diamond) coating had a rough surface morphology due to the presence of droplets formed at the substrate surface during the reactive evaporation of TiC. In this work, we first present an extensive Raman investigation of 2 mu m, 4 mu m and 6 mu m thick diamond films deposited by hot filament CVD on TiC interlayers obtained by the PVD-arc technique. The stress state of the diamond was dependent on both the films thickness and the spatial position of the coating on the substrate. In fact, on the top of TiC droplets, the stress state of the diamond was much lower than that of diamond in flatter substrate areas. These results showed that diamond films deposited on rough TiC interlayers exhibited a wide distribution of stress values and that very large compressive stress exists in the diamond film grown on flat regions of steel substrates with a TiC interlayer. Diamond films could accommodate stresses as large as 10 GPa without delamination

Fostering resilient execution of multi-agent plans through self-organisation

Traditional multi-agent planning addresses the coordination of multiple agents towards common goals, by producing an integrated plan of actions for each of those agents. For systems made of large numbers of cooperating agents, however, the execution and monitoring of a plan should enhance its high-level steps, possibly involving entire sub-teams, with a flexible and adaptable lower-level behaviour of the individual agents. In order to achieve such a goal, we need to integrate the behaviour dictated by a multi-agent plan with self-organizing, swarm-based approaches, capable of automatically adapting their behaviour based on the contingent situation, departing from the predetermined plan whenever needed. Moreover, in order to deal with multiple domains and unpredictable situations, the system should, as far as possible, exhibit such capabilities without hard-coding the agents behaviour and interactions. In this paper, we investigate the relationship between multi-agent planning and self-organisation through the combination of two representative approaches both enjoying declarativity. We consider a functional approach to self-organising systems development, called Aggregate Programming (AP), and propose to exploit collective adaptive behaviour to carry out plan revisions. We describe preliminary results in this direction on a case study of execution monitoring and repair of a Multi-Agent PDDL plan

Towards Reinforcement Learning-based Aggregate Computing

Recent trends in pervasive computing promote the vision of Collective Adaptive Systems (CASs): large-scale collections of relatively simple agents that act and coordinate with no central orchestrator to support distributed applications. Engineering global behaviour out of local activity and interaction, however, is a difficult task, typically addressed by try-and-error approaches in simulation environments. In the context of Aggregate Computing (AC), a prominent functional programming approach for CASs based on field-based coordination, this difficulty is reflected in the design of versatile algorithms preserving efficiency in a variety of environments. To deal with this complexity, in this work we propose to apply Machine Learning techniques to automatically devise local actions to improve over manually-defined AC algorithms specifications. Most specifically, we adopt a Reinforcement Learning-based approach to let a collective learn local policies to improve over the standard gradient algorithm—a cornerstone brick of several higher-level self-organisation algorithms. Our evaluation shows that the learned policies can speed up the self-stabilisation of the gradient to external perturbations

Machine Learning for Aggregate Computing: a Research Roadmap

Aggregate computing is a macro-approach for programming collective intelligence and self-organisation in distributed systems. In this paradigm, a single 'aggregate program' drives the collective behaviour of the system, provided that the agents follow an execution protocol consisting of asynchronous sense-compute-act rounds. For actual execution, a proper aggregate computing middleware or platform has to be deployed across the nodes of the target distributed system, to support the services needed for the execution of applications. Overall, the engineering of aggregate computing applications is a rich activity that spans multiple concerns including designing the aggregate program, developing reusable algorithms, detailing the execution model, and choosing a deployment based on available infrastructure. Traditionally, these activities have been carried out through ad-hoc designs and implementations tailored to specific contexts and goals. To overcome the complexity and cost of manually tailoring or fixing algorithms, execution details, and deployments, we propose to use machine learning techniques, to automatically create policies for applications and their management. To support such a goal, we detail a rich research roadmap, showing opportunities and challenges of integrating aggregate computing and learning

Effect of mobile carrier on the performance of pvam–nanocellulose facilitated transport membranes for co2 capture

Facilitated transport membranes obtained by coupling polyvinylamine with highly charged carboxymethylated nanocellulose fibers were studied considering both water sorption and gas permeation experiments. In particular, the effect of the L-arginine as a mobile carrier was investigated to understand possible improvements in CO2 transport across the membranes. The results show that L-arginine addition decreases the water uptake of the membrane, due to the lower polyvinylamine content, but was able to improve the CO2 transport. Tests carried on at 35◦ C and high relative humidity indeed showed an increase of both CO2 permeability and selectivity with respect to nitrogen and methane. In particular, the CO2 permeability increased from 160 to about 340 Barrer when arginine loading was increased from 0 to 45 wt%. In the same conditions, selectivity with respect to nitrogen was more than doubled, increasing from 20 to 45. Minor improvements were instead obtained with respect to methane; CO2 /CH4 selectivity, indeed, even in presence of the mobile carrier, was limited to about 20

The Local Interstellar Spectrum of Cosmic Ray Electrons

The direct measurements of electrons and positrons over the last 30 years, corrected for the solar effect in the force-field approximation, are considered. The resulting overall electron spectrum may be fitted with a single power law above few GeV with spectral index ($\gamma_{-} = 3.41 \pm 0.02$), consistent with the spectral index of the positron spectrum ($\gamma_{+} = 3.40 \pm 0.06$), therefore suggesting a common acceleration process for both species. We propose that the engine was a shock wave originating from the last supernova explosion among those that formed the local bubble. In addition, at low energy, the electron spectrum measured during the last $A+$ solar phase is damped, whereas the positron spectrum is well represented by a single power law down to the lowest inferred local interstellar energy (0.8 GeV). We suggest that this difference arises from a time- and charge-dependent effect of the solar modulation that is not taken into account by the force-field approximation.Comment: 10 pages, 9 figures, 1 table. OBSOLETE: please refer to ApJ 612 (2004) 262-267, that is the final version of this wor

Hot filament chemical vapour deposition and wear resistance of diamond films on WC-Co substrates coated using PVD-arc deposition technique

Different Cr- and Ti-base films were deposited using PVD-arc deposition onto WC-Co substrates, and multilayered coatings were obtained from the superimposition of diamond coatings, deposited on the PVD interlayer using hot filament chemical vapour deposition (HFCVD). The behaviour of PVD-arc deposited CrN and CrC interlayers between diamond and WC-Co substrates was studied and compared to TiN, TiC, and Ti(C,N) interlayers. Tribological tests with alternative sliding motion were carried out to check the multilayer (PVD+ diamond) film adhesion on WC-Co substrate. Multilayer films obtained using PVD arc, characterised by large surface droplets, demonstrated good wear resistance, while diamond deposited on smooth PVD TiN films was not adherent. Multilayered Ti(C,N)+diamond film samples generally showed poor wear resistance. Diamond adhesion on Cr-based PVD coatings deposited on WC-Co substrate was good. In particular, CrN interlayers improved diamond film properties and 6 gm-thick diamond films deposited on CrN showed excellent wear behaviour characterised by the absence of measurable wear volume after sling tests. Good diamond adhesion on Cr-based PVD films has been attributed to chromium carbide formation on PVD film surfaces during the CVD process. (c) 2005 Elsevier B.V. All rights reserved

Dry turning of alumina/aluminum composites with CVD diamond coated Co-cemented tungsten carbide tools

Triangular (TPGN 160308) WC-6 wt.%Co inserts having different average grain sizes (1 and 3 µm) were submitted to surface roughening either by wet etching with Murakami's reagent or by a heat treatment in the hot filament chemical vapour deposition (HFCVD) reactor. The heat treatment was performed in a monohydrogen-rich atmosphere at substrate temperatures as high as 1000 degrees C. Scanning electron microscopy and energy-dispersive spectroscopy showed that this pre-treatment led to surface roughening of the as-ground inserts and to a lower surface Co concentration. Prior to deposition, all inserts were etched with an acid solution of hydrogen peroxide. Diamond coatings were deposited by HFCVD. The coated inserts were tested by dry machining of aluminum-matrix composite (Al-10%Al2O3) bars. Turning test results indicated that a proper combination of substrate pretreatment and microstructure can significantly improve tool life

Late postpancreatectomy hemorrhage after pancreaticoduodenectomy: is it possible to recognize risk factors?

CONTEXT: Post-pancreatectomy hemorrhage is one of the most common complications after pancreaticoduodenectomy. OBJECTIVE: To evaluate the late post-pancreatectomy hemorrhage rate according to the International Study Group of Pancreatic Surgery criteria and to recognize factors related to its onset. METHODS: A prospective study of 113 patients who underwent pancreaticoduodenectomy was conducted. Late post-pancreatectomy hemorrhage was defined according to the criteria of the International Study Group of Pancreatic Surgery. Demographic, clinical, surgical and pathological data were considered and related to late post-pancreatectomy hemorrhage. RESULTS: Thirty-one (27.4%) patients had a post-pancreatectomy hemorrhage. Twenty-five (22.1%) patients developed late post-pancreatectomy hemorrhage: 19 (16.8%) grade B, 6 (5.3%) grade C. Surgical re-operation was performed in 2 out of the 25 cases with late post-pancreatectomy hemorrhage (8.0%) grade C associated with postoperative pancreatic fistula. At univariate analysis, the only factor significantly related to late post-pancreatectomy hemorrhage was postoperative pancreatic fistula (P<0.001). Multivariate analysis underlined that the severity of postoperative pancreatic fistula (P<0.001) and pancreatic anastomosis (P=0.049) independently increased the risk of late hemorrhage. CONCLUSION: In patients undergoing pancreaticoduodenectomy, the criteria introduced by International Study Group of Pancreatic Surgery to define late postpancreatectomy hemorrhage are related to a higher incidence of hemorrhage than previously detected because they considered also mild hemorrhage

Computation Against a Neighbour: Addressing Large-Scale Distribution and Adaptivity with Functional Programming and Scala

Recent works in contexts like the Internet of Things (IoT) and large-scale Cyber-Physical Systems (CPS) propose the idea of programming distributed systems by focussing on their global behaviour across space and time. In this view, a potentially vast and heterogeneous set of devices is considered as an “aggregate” to be programmed as a whole, while abstracting away the details of individual behaviour and exchange of messages, which are expressed declaratively. One such a paradigm, known as aggregate programming, builds on computational models inspired by field-based coordination. Existing models such as the field calculus capture interaction with neighbours by a so-called “neighbouring field” (a map from neighbours to values). This requires ad-hoc mechanisms to smoothly compose with standard values, thus complicating programming and introducing clutter in aggregate programs, libraries and domain-specific languages (DSLs). To address this key issue we introduce the novel notion of “computation against a neighbour”, whereby the evaluation of certain subexpressions of the aggregate program are affected by recent corresponding evaluations in neighbours. We capture this notion in the neighbours calculus (NC), a new field calculus variant which is shown to smoothly support declarative specification of interaction with neighbours, and correspondingly facilitate the embedding of field computations as internal DSLs in common general-purpose programming languages—as exemplified by a Scala implementation, called ScaFi. This paper formalises NC, thoroughly compares it with respect to the classic field calculus, and shows its expressiveness by means of a case study in edge computing, developed in ScaFi