Unipolar plasma electrolytic oxidation: Waveform optimisation for corrosion resistance of commercially pure titanium

This study deals with the anodisation of titanium grade 2 in 0.5-M sulphuric acid using a pulsed signal in a unipolar regime. The electrical parameters investigated are voltage, frequency and duty cycle. The use of duty cycles with a high percentage of anodic polarisation (90%), combined with high frequencies (1000 Hz) and the higher voltage tested (220 V), favoured the establishment of a plasma regime involving strong dielectric discharges, allowing the growth of thicker oxides but with rough architecture. The corrosion resistance of the formed film has been characterised by potentiodynamic tests in 0.5-M NaBr for localised corrosion resistance and by immersion tests in 10% v/v sulphuric acid solution for a uniform corrosion assessment. Current–time curves, visual observations and electron microscope analysis (scanning electron microscopy, energy-dispersive X-ray spectroscopy) were the tools selected to provide a correlation between technological parameters and oxide growth mechanism. For localised and uniform corrosion, anodisation at 220 V with a high level of anodic polarisation (90%) and frequency (1000 Hz) was verified to be particularly advantageous.     

Weak Delocalization in Graphene on a Ferromagnetic Insulating Film

Graphene has been predicted to develop a magnetic moment by proximity effect when placed on a ferromagnetic film, a promise that could open exciting possibilities in the fields of spintronics and magnetic data recording. In this work, the interplay between the magnetoresistance of graphene and the magnetization of an underlying ferromagnetic insulating film is studied in detail. A clear correlation between both magnitudes is observed but through a careful modeling of the magnetization and the weak localization measurements, that such correspondence can be explained by the effects of the magnetic stray fields arising from the ferromagnetic insulator is found. The results emphasize the complexity arising at the interface between magnetic and 2D materials.     

Efficient primal-dual heuristic for a dynamic location problem

In this paper the dynamic location problem with opening, closure and reopening of facilities is formulated and an efficient primal-dual heuristic that computes both upper and lower limits to its optimal solution is described. The problem here studied considers the possibility of reconfiguring any location more than once over the planning horizon. This problem is NP-hard (the simple plant location problem is a special case of the problem studied). A primal-dual heuristic based on the work of Erlenkotter [A dual-based procedure for uncapacitated facility location. Operations Research 1978;26:992–1009] and Van Roy and Erlenkotter [A dual-based procedure for dynamic facility location. Management Science 1982;28:1091–105] was developed and tested over a set of randomly generated test problems. The results obtained are quite good, both in terms of the quality of lower and upper bounds calculated as in terms of the computational time spent by the heuristic. A branch-and-bound procedure that enables to optimize the problem is also described and tested over the same set of randomly generated problems.     

Inbreeding in Swiss Braunvieh and its influence on breeding values predicted from a repeatability animal model.

Inbreeding coefficients were computed for 910,444 animals of the Swiss Braunvieh population. Of the animals born in 1984, 71.5% were inbred with 67.9, 3.4, and .2% having inbreeding coefficients between greater than 0 and 5%, greater than 5 to 10%, and greater than 10%, respectively. The average inbreeding coefficient was 1.14% but, for animals with both parents and at least one grandparent known, it was 1.67%. Breeding values for total milk, fat, and protein yields and for fat and protein percentages were predicted using a repeatability animal model including a regression on the inbreeding coefficient. Phenotypic performance was sizeably depressed for milk yield only (-26 kg/% of inbreeding or 2.4% of the phenotypic standard deviation). Adjusting for inbreeding increased the estimated genetic trend slightly. Inbreeding is only partially accounted for when it is ignored in the construction of the inverse of the numerator relationship matrix. This effect was investigated by comparing predicted breeding values from a model including the complete matrix with predicted breeding values from a model including a matrix constructed with inbreeding ignored. Only .8% of all predicted breeding values were affected by more than +/- 5.5 kg. The maximum difference observed was 55.3 kg. The observed average absolute differences between the breeding values of offspring predicted with the two models increased with inbreeding of parents.     

PhotoGeo: a photo digital library with spatial-temporal support and self-annotation

The recent popularity of digital cameras has posed a new problem: how to efficiently store and retrieve the very large number of digital photos captured and chaotically stored in multiple locations without any annotation. This paper proposes an infrastructure, called PhotoGeo, which aims at helping users with the people photo annotation, event photo annotation, storage and retrieval of personal digital photos. To achieve the desired objective, PhotoGeo uses new algorithms that make it possible to annotate photos with the key metadata to facilitate their retrieval, such as: the people who were shown in the photo (who); where it was captured (where); the date and time of capture (when); and the event that was captured. The paper concludes with a detailed evaluation of these algorithms.     

The Chick Chorioallantoic Membrane Model: A New In Vivo Tool to Evaluate Breast Cancer Stem Cell Activity

The high plasticity of cancer stem-like cells (CSCs) allows them to differentiate and proliferate, specifically when xenotransplanted subcutaneously into immunocompromised mice. CSCs are highly tumorigenic, even when inoculated in small numbers. Thus, in vivo limiting dilution assays (LDA) in mice are the current gold standard method to evaluate CSC enrichment and activity. The chick embryo chorioallantoic membrane (CAM) is a low cost, naturally immune-incompetent and reproducible model widely used to evaluate the spontaneous growth of human tumor cells. Here, we established a CAM-LDA assay able to rapidly reproduce tumor specificities—in particular, the ability of the small population of CSCs to form tumors. We used a panel of organotropic metastatic breast cancer cells, which show an enrichment in a stem cell gene signature, enhanced CD44⁺/CD24^−/low cell surface expression and increased mammosphere-forming efficiency (MFE). The size of CAM-xenografted tumors correlate with the number of inoculated cancer cells, following mice xenograft growth pattern. CAM and mice tumors are histologically comparable, displaying both breast CSC markers CD44 and CD49f. Therefore, we propose a new tool for studying CSC prevalence and function—the chick CAM-LDA—a model with easy handling, accessibility, rapid growth and the absence of ethical and regulatory constraints.     

P16 and HPV Genotype Significance in HPV-Associated Cervical Cancer—A Large Cohort of Two Tertiary Referral Centers

The expression of p16 is a good surrogate of human papillomavirus (HPV) infection in HPV-associated cancers. The significance of p16 expression, HPV genotype and genera in the outcome of patients with HPV-associated cervical cancer (CC) is unclear. Our aim is to ascertain the prognostic significance of these factors. Data from 348 patients (median age: 47.5 years old) with CC, diagnosed in two referral centers, were retrospectively collected. Advanced disease (FIGO2018 IB2-IV) was present in 68% of patients. A single HPV genotype was identified in 82.8% of patients. The most common HPVs were HPV16 (69%) and HPV18 (14%). HPV genera reflected this distribution. HPV16 tumors presented at an earlier stage. P16 was negative in 18 cases (5.2%), 83.3% of which were squamous cell carcinomas. These cases occurred in older patients who tended to have advanced disease. In the univariate analysis, HPV16 (HR: 0.58; p = 0.0198), α-9 genera (HR: 0.37; p = 0.0106) and p16 overexpression (HR: 0.54; p = 0.032) were associated with better survival. HPV16 (HR: 0.63; p = 0.0174) and α-9 genera (HR: 0.57; p = 0.0286) were associated with less relapse. In the multivariate analysis, only the International Federation of Gynecology and Obstetrics (FIGO) stage retained an independent prognostic value. HPV16, α-9 genera and p16 overexpression were associated with better survival, although not as independent prognostic factors. Patients with p16-negative HPV-associated CC were older, presented with advanced disease and had worse prognosis.     

Multirate control with incomplete information over Profibus-DP network

When a process field bus-decentralized peripherals (Profibus-DP) network is used in an industrial environment, a deterministic behaviour is usually claimed. However, due to some concerns such as bandwidth limitations, lack of synchronisation among different clocks and existence of time-varying delays, a more complex problem must be faced. This problem implies the transmission of irregular and, even, random sequences of incomplete information. The main consequence of this issue is the appearance of different sampling periods at different network devices. In this paper, this aspect is checked by means of a detailed Profibus-DP timescale study. In addition, in order to deal with the different periods, a delay-dependent dual-rate proportional-integral-derivative control is introduced. Stability for the proposed control system is analysed in terms of linear matrix inequalities.     

EDT Method for Multiple Labelled Objects Subject to Tied Distances

Machine Intelligence Research - The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches aligned with real-world applications. The...     

Selecting linear algebra kernel composition using response time prediction

Numerical linear algebra libraries provide many kernels that can be composed to perform complex computations. For a given computation, there is typically a large number of functionally equivalent kernel compositions. Some of these compositions achieve better response times than others for particular data and when executed on a particular computer architecture. Previous research provides methods to enumerate (a subset of) these kernel compositions. In this work, we study the problem of determining the composition that yields the lowest response time. Our approach is based on a response time prediction for each candidate combination. While this prediction could in principle be obtained using analytical and/or empirical performance models, developing accurate such models is known to be challenging. Instead, we define a feature space that captures salient properties of kernel combinations and predict response time using supervised machine learning. We experiment with a standard set of machine learning algorithms and identify an effective algorithm for our kernel composition selection problem. Using this algorithm, our approach widely outperforms the strategy that would consist in always using the simplest kernel composition and is often close to the fastest kernel compositions among those evaluated. We quantify the potential benefit of our approach if it were to be implemented as part of an interactive computational tool. We find that although the potential benefit is substantial, a limiting factor is the kernel composition enumeration overhead. Copyright © 2014 John Wiley & Sons, Ltd.