Towards a Taxonomy of Cognitive RPA Components

Robotic Process Automation (RPA) is a discipline that is increasingly growing hand in hand with Artificial Intelligence (AI) and Machine Learning enabling the so-called cognitive automation. In such context, the existing RPA platforms that include AI-based solutions clas sify their components, i.e. constituting part of a robot that performs a set of actions, in a way that seems to obey market or business deci sions instead of common-sense rules. To be more precise, components that present similar functionality are identified with different names and grouped in different ways depending on the platform that provides the components. Therefore, the analysis of different cognitive RPA platforms to check their suitability for facing a specific need is typically a time consuming and error-prone task. To overcome this problem and to pro vide users with support in the development of an RPA project, this paper proposes a method for the systematic construction of a taxonomy of cognitive RPA components. Moreover, such a method is applied over components that solve selected real-world use cases from the industry obtaining promising resultsMinisterio de Economía y Competitividad TIN2016-76956-C3-2-RJunta de Andalucía CEI-12-TIC021Centro para el Desarrollo Tecnológico Industrial P011-19/E0

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

On-going collaborative priority-setting for research activity: a method of capacity building to reduce the research-practice translational gap

Background: International policy suggests that collaborative priority setting (CPS) between researchers and end users of research should shape the research agenda, and can increase capacity to address the research-practice translational gap. There is limited research evidence to guide how this should be done to meet the needs of dynamic healthcare systems. One-off priority setting events and time-lag between decision and action prove problematic. This study illustrates the use of CPS in a UK research collaboration called Collaboration and Leadership in Applied Health Research and Care (CLAHRC). Methods: Data were collected from a north of England CLAHRC through semi-structured interviews with 28 interviewees and a workshop of key stakeholders (n = 21) including academics, NHS clinicians, and managers. Documentary analysis of internal reports and CLAHRC annual reports for the first two and half years was also undertaken. These data were thematically coded. Results: Methods of CPS linked to the developmental phase of the CLAHRC. Early methods included pre-existing historical partnerships with on-going dialogue. Later, new platforms for on-going discussions were formed. Consensus techniques with staged project development were also used. All methods demonstrated actual or potential change in practice and services. Impact was enabled through the flexibility of research and implementation work streams; ‘matched’ funding arrangements to support alignment of priorities in partner organisations; the size of the collaboration offering a resource to meet project needs; and the length of the programme providing stability and long term relationships. Difficulties included tensions between being responsive to priorities and the possibility of ‘drift’ within project work, between academics and practice, and between service providers and commissioners in the health services. Providing protected ‘matched’ time proved difficult for some NHS managers, which put increasing work pressure on them. CPS is more time consuming than traditional approaches to project development. Conclusions: CPS can produce needs-led projects that are bedded in services using a variety of methods. Contributing factors for effective CPS include flexibility in use and type of available resources, flexible work plans, and responsive leadership. The CLAHRC model provides a translational infrastructure that enables CPS that can impact on healthcare systems

Asteroseismology and Interferometry

Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36

Antiangiogenic agents in the treatment of recurrent or newly diagnosed glioblastoma: Analysis of single-agent and combined modality approaches

Surgical resection followed by radiotherapy and temozolomide in newly diagnosed glioblastoma can prolong survival, but it is not curative. For patients with disease progression after frontline therapy, there is no standard of care, although further surgery, chemotherapy, and radiotherapy may be used. Antiangiogenic therapies may be appropriate for treating glioblastomas because angiogenesis is critical to tumor growth. In a large, noncomparative phase II trial, bevacizumab was evaluated alone and with irinotecan in patients with recurrent glioblastoma; combination treatment was associated with an estimated 6-month progression-free survival (PFS) rate of 50.3%, a median overall survival of 8.9 months, and a response rate of 37.8%. Single-agent bevacizumab also exceeded the predetermined threshold of activity for salvage chemotherapy (6-month PFS rate, 15%), achieving a 6-month PFS rate of 42.6% (p < 0.0001). On the basis of these results and those from another phase II trial, the US Food and Drug Administration granted accelerated approval of single-agent bevacizumab for the treatment of glioblastoma that has progressed following prior therapy. Potential antiangiogenic agents-such as cilengitide and XL184-also show evidence of single-agent activity in recurrent glioblastoma. Moreover, the use of antiangiogenic agents with radiation at disease progression may improve the therapeutic ratio of single-modality approaches. Overall, these agents appear to be well tolerated, with adverse event profiles similar to those reported in studies of other solid tumors. Further research is needed to determine the role of antiangiogenic therapy in frontline treatment and to identify the optimal schedule and partnering agents for use in combination therapy

Comparative analyses imply that the enigmatic sigma factor 54 is a central controller of the bacterial exterior

Contains fulltext : 95738.pdf (publisher's version ) (Open Access)BACKGROUND: Sigma-54 is a central regulator in many pathogenic bacteria and has been linked to a multitude of cellular processes like nitrogen assimilation and important functional traits such as motility, virulence, and biofilm formation. Until now it has remained obscure whether these phenomena and the control by Sigma-54 share an underlying theme. RESULTS: We have uncovered the commonality by performing a range of comparative genome analyses. A) The presence of Sigma-54 and its associated activators was determined for all sequenced prokaryotes. We observed a phylum-dependent distribution that is suggestive of an evolutionary relationship between Sigma-54 and lipopolysaccharide and flagellar biosynthesis. B) All Sigma-54 activators were identified and annotated. The relation with phosphotransfer-mediated signaling (TCS and PTS) and the transport and assimilation of carboxylates and nitrogen containing metabolites was substantiated. C) The function annotations, that were represented within the genomic context of all genes encoding Sigma-54, its activators and its promoters, were analyzed for intra-phylum representation and inter-phylum conservation. Promoters were localized using a straightforward scoring strategy that was formulated to identify similar motifs. We found clear highly-represented and conserved genetic associations with genes that concern the transport and biosynthesis of the metabolic intermediates of exopolysaccharides, flagella, lipids, lipopolysaccharides, lipoproteins and peptidoglycan. CONCLUSION: Our analyses directly implicate Sigma-54 as a central player in the control over the processes that involve the physical interaction of an organism with its environment like in the colonization of a host (virulence) or the formation of biofilm