Evaluation of the effect of heat input in superduplex stainless steel deposition by the plasma powder process*

Plasma powder surfacing is one of the latest processes for application of coatings, with control of dilution as its main feature. Surfacing with superduplex stainless steels is an interesting option for the construction and repair of equipment for applications in a highly corrosive environment, allowing the desired characteristics to be achieved: corrosion resistance and good mechanical properties. The aim of this work is to assess the ferrite content in the weld metal and the mechanical characteristics via microhardness profiles in surfacing of C-Mn steel pipes with deposition of UNS S32760 by plasma powder surfacing. Welding operations were carried out on pipes with deposition of SDSS, employing three welding heat input levels, varying the welding speed or the welding current. Then the geometry was analysed, the ferrite content in the weld metal was quantified and the microhardness profile was recorded. Variation in welding heat input caused changes in weld bead geometry, with variation in the welding current producing the most significant changes. Increase in heat input caused decrease in ferrite content of the weld metal. Regarding microhardness, only the condition with a higher level of welding current gave sufficiently high levels of microhardness in the weld metal.     

Mixture and non-mixture cure fraction models based on the generalized modified Weibull distribution with an application to gastric cancer data

The cure fraction models are usually used to model lifetime time data with long-term survivors. In the present article, we introduce a Bayesian analysis of the four-parameter generalized modified Weibull (GMW) distribution in presence of cure fraction, censored data and covariates. In order to include the proportion of “cured” patients, mixture and non-mixture formulation models are considered. To demonstrate the ability of using this model in the analysis of real data, we consider an application to data from patients with gastric adenocarcinoma. Inferences are obtained by using MCMC (Markov Chain Monte Carlo) methods.     

Universality in ant behaviour

Prediction for social systems is a major challenge. Universality at the social level has inspired a unified theory for urban living but individual variation makes predicting relationships within societies difficult. Here, we show that in ant societies individual average speed is higher when event duration is longer. Expressed as a single scaling function, this relationship is universal because for any event duration an ant, on average, moves at the corresponding average speed except for a short acceleration and deceleration at the beginning and end. This establishes cause and effect within a social system and may inform engineering and control of artificial ones.     

Single passage in mouse organs enhances the survival and spread of Salmonella enterica

Intravenous inoculation of Salmonella enterica serovar Typhimurium into mice is a prime experimental model of invasive salmonellosis. The use of wild-type isogenic tagged strains (WITS) in this system has revealed that bacteria undergo independent bottlenecks in the liver and spleen before establishing a systemic infection. We recently showed that those bacteria that survived the bottleneck exhibited enhanced growth when transferred to naive mice. In this study, we set out to disentangle the components of this in vivo adaptation by inoculating mice with WITS grown either in vitro or in vivo. We developed an original method to estimate the replication and killing rates of bacteria from experimental data, which involved solving the probability-generating function of a non-homogeneous birth–death–immigration process. This revealed a low initial mortality in bacteria obtained from a donor animal. Next, an analysis of WITS distributions in the livers and spleens of recipient animals indicated that in vivo-passaged bacteria started spreading between organs earlier than in vitro-grown bacteria. These results further our understanding of the influence of passage in a host on the fitness and virulence of Salmonella enterica and represent an advance in the power of investigation on the patterns and mechanisms of host–pathogen interactions.     

Combustion properties of Brazilian natural wood species

This paper investigates the combustion characteristics of 12 wood species natural to Brazil. A mass loss cone calorimeter was used to obtain the properties associated with (i) heat release rate (HRR), peak HRR, and total heat released; (ii) total mass loss and mass loss rate; (iii) average effective heat of combustion; and (iv) time to ignition, time of pyrolysis and temperature of ignition. The samples used in this work were as follows: (i) prepared in accordance to ISO 5660‐1:2002; (ii) oven dried; (iii) irradiated with a constant heat flux of 50 kW/m²; and (iv) exhibit wood fiber orientation in a plane orthogonal to the flux incidence. Finally, the paper explores the possibility of linking the obtained combustion properties with the density and classes of selected wood species. Copyright © 2014 John Wiley & Sons, Ltd.     

Collective cell migration: leadership,invasion and segregation

A number of biological processes, such as embryo development, cancer metastasis or wound healing, rely on cells moving in concert. The mechanisms leading to the emergence of coordinated motion remain however largely unexplored. Although biomolecular signalling is known to be involved in most occurrences of collective migration, the role of physical and mechanical interactions has only been recently investigated. In this study, a versatile framework for cell motility is implemented in silico in order to study the minimal requirements for the coordination of a group of epithelial cells. We find that cell motility and cell–cell mechanical interactions are sufficient to generate a broad array of behaviours commonly observed in vitro and in vivo. Cell streaming, sheet migration and susceptibility to leader cells are examples of behaviours spontaneously emerging from these simple assumptions, which might explain why collective effects are so ubiquitous in nature. The size of the population and its confinement appear, in particular, to play an important role in the coordination process. In all cases, the complex response of the population can be predicted from the knowledge of the correlation length of the velocity field measured in the bulk of the epithelial layer. This analysis provides also new insights into cancer metastasis and cell sorting, suggesting, in particular, that collective invasion might result from an emerging coordination in a system where single cells are mechanically unable to invade.     

SCOOP: A Real-Time Sparsity Driven People Localization Algorithm

Detecting and tracking people in scenes monitored by cameras is an important step in many application scenarios such as surveillance, urban planning or behavioral studies to name a few. The amount of data produced by camera feeds is so large that it is also vital that these steps be performed with the utmost computational efficiency and often even real-time. We propose SCOOP, a novel algorithm that reliably localizes people in camera feeds, using only the output of a simple background removal technique. SCOOP can handle a single or many video feeds. At the heart of our technique there is a sparse model for binary motion detection maps that we solve with a novel greedy algorithm based on set covering. We study the convergence and performance of the algorithm under various degradation models such as noisy observations and crowded environments, and we provide mathematical and experimental evidence of both its efficiency and robustness using standard datasets. This clearly shows that SCOOP is a viable alternative to existing state-of-the-art people localization algorithms, with the marked advantage of real-time computations.     

Execution profiling blueprints

Although traditional approaches to code profiling help locate performance bottlenecks, they offer only limited support for removing these bottlenecks. The main reason is the lack of detailed visual runtime information to identify and eliminate computation redundancy. We provide three profiling blueprints that help identify and remove performance bottlenecks. The structural distribution blueprint graphically represents the CPU consumption share for each method and class of an application. The behavioral distribution blueprint depicts the distribution of CPU consumption along method invocations and hints at method candidates for caching optimizations. The behavioral evolution blueprint compares profiles of different versions of a software system and highlights performance‐critical changes in the system. These three blueprints helped us to significantly optimize Mondrian, an open source visualization engine. Our implementation is freely available for the Pharo development environment and has been evaluated in a number of different scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

Generating model-based test cases from natural language requirements for space application software

Natural Language (NL) deliverables suffer from ambiguity, poor understandability, incompleteness, and inconsistency. Howewer, NL is straightforward and stakeholders are familiar with it to produce their software requirements documents. This paper presents a methodology, SOLIMVA, which aims at model-based test case generation considering NL requirements deliverables. The methodology is supported by a tool that makes it possible to automatically translate NL requirements into Statechart models. Once the Statecharts are derived, another tool, GTSC, is used to generate the test cases. SOLIMVA uses combinatorial designs to identify scenarios for system and acceptance testing, and it requires that a test designer defines the application domain by means of a dictionary. Within the dictionary there is a Semantic Translation Model in which, among other features, a word sense disambiguation method helps in the translation process. Using as a case study a space application software product, we compared SOLIMVA with a previous manual approach developed by an expert under two aspects: test objectives coverage and characteristics of the Executable Test Cases. In the first aspect, the SOLIMVA methodology not only covered the test objectives associated to the expert’s scenarios but also proposed a better strategy with test objectives clearly separated according to the directives of combinatorial designs. The Executable Test Cases derived in accordance with the SOLIMVA methodology not only possessed similar characteristics with the expert’s Executable Test Cases but also predicted behaviors that did not exist in the expert’s strategy. The key benefits from applying the SOLIMVA methodology/tool within a Verification and Validation process are the ease of use and, at the same time, the support of a formal method consequently leading to a potential acceptance of the methodology in complex software projects.