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Sexual dimorphism has been poorly evaluated or investigated in Pleistocene Eurasian Stephanorhinus species, leaving a gap in our knowledge about their morphometric variability. Among the representatives of this genus, S. etruscus is the most abundant species, with several remains collected from Western European localities, allowing us to investigate the presence of sexual dimorphism in the limb bones of this taxon. We considered measurements taken on 45 postcranial variables and three different statistical metrics to identify patterns of bimodality in the dataset. This work represents the first application of sex-combined statistical analysis to a dataset composed of individuals from various European localities. The morphometrical analyses revealed that a relatively weak sexual dimorphism is present in all the considered bones. Larger forelimbs and hindlimbs are interpreted as belonging to adult males of S. etruscus, similarly to what was observed in the modern Sumatran rhino, where males are a little bit larger than females. The recognition of a weak sexual dimorphism in the postcranial bones of S. etruscus increases our understanding of the paleoecology of this extinct taxon. However, only a better study of the morphological and morphometrical variability of the crania of fossil rhinoceroses could deeply contribute to the investigation of the social habits and behavior of these taxa.

Emerging online research platforms are bringing new efficiencies to the design research process. But the resulting data is large in scope and dense in nature. And the analytic tools and approaches design teams have come to rely on were not designed to manage this scale of inquiry. As design problems expand in complexity and require more inputs, generating big qualitative data sets is likely to become the new norm. This paper proposes two ways to manage this new condition: (1) adding visual coding techniques to textual coding to counteract "data sameness" and "data sprawl," and (2) developing new tools to support fast meta explorations of data sets.

Big data analytics can add value and provide a new perspective by improving predictive analysis and modeling practices. This research is centered on supply-chain management and how big data analytics can help Romanian supply-chain companies assess their experience, strategies, and professional capabilities in successfully implementing big data analytics, as well as assessing the tools needed to achieve these goals, including the results of implementation and performance achievement based on them. The research method used in the quantitative study was a sampling survey, using a questionnaire as a data collection tool. It included closed questions, measured with nominal and ordinal scales. A total of 205 managers provided complete and useful answers for this research. The collected data were analyzed with the Statistical Package for the Social Sciences (SPSS) package using frequency tables, contingency tables, and main component analysis. The major contributions of this research highlight the fact that companies are concerned with identifying new statistical methods, tools, and approaches, such as cloud computing and security technologies, that need to be rigorously explored.

Artificial intelligence (AI) is becoming ubiquitous in health care, largely through machine learning and predictive analytics applications. Recent applications of AI to common health care scenarios, such as screening and diagnosing, have fueled optimism about the use of advanced analytics to improve care. Careful and objective considerations need to be made before implementing an advanced analytics solution. Critical evaluation before, during, and after its implementation will ensure safe care, good outcomes, and the elimination of waste. In this commentary we offer basic practical considerations for developing, implementing, and evaluating such solutions based on many years of experience.

Dashboards are information management tools , for monitoring and analysing of different organization’s behaviour. The purpose of management Dashboards is to observe, identify and solve problems and to justify patterns with monitoring the key performance indicators. T he Dashboards are not just reporting tools , they are interactive communication tools with meaning and purpose. They can analyse big amount of data and return as a result complete storyline of information letting the audience to understand how an organizati on works. Thus, this Master Thesis aims to identify and analytically examine the key features, purposes, uses, and benefits of performance dashboards and to develop a Higher Education Management Dashboard in R for the needs of MASTEAM Master of the Polyte chnic University of Catalonia ( UPC ) . The Thesis is highlighting the methodology and the designing rules for creating dashboards and taking the full pote ntial and benefits of them. Based on them, in the Thesis is implemented a real education management Das hboard in R programing language . The fundamental rules are used for the implementation of the MASTEAM Master Dashboard . The Dashboard will include the most important features and information about the MASTEAM, which are pointed from the coordinator of the MASTEAM through an interview . T he main goal is to give the coordinator the ability to observe and analyse the behaviour of significant areas in the Master. For instance , some of the areas are the enrolment status, student’s information, grades, courses, graduated rates, etc. Finally, the results of the programing part will demonstrate the last version of the MASTEAM Dashboard web page that can be used from the coordinator . He can monitor the behaviour of the Maste r and take necessary decisions . A ccordin g to the visualised data, the maintenance of the good condition of the existing Master is also possible .

Globalisation, volatile markets, legal changes and technical progress have an immense impact on business environments in most industries. More and more IT is deployed to manage the complexity. As a result, companies and organisations have to handle growing volumes of data which have become a valuable asset. The ability to benefit from this asset is increasingly essential for business success. Therefore, fast storage, reliable data access, intelligent information retrieval, and new decision-making mechanisms are required. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges.

Technological advances have led to increasingly more data becoming available, a phenomenon known as Big Data. The volume of Big Data is to the order of zettabytes, offering the promise of valuable insights with visualisation the key to unlocking these insights, however the size and variety of Big Data poses significant challenges. The fundamental principles behind tried-and-tested methods for visualising data are still as relevant as ever, although the emphasis necessarily shifts to why visualisation is being attempted. This chapter outlines the use of graph semiotics to build data visualisations for exploration and decision-making and the formulation of elementary, intermediate- and overall-level analytical questions. The public scanner database Dominick's Finer Foods, consisting of approximately 98 million observations, is used as a demonstrative case study. Common Big Data analytic tools (SAS, R and Python) are used to produce visualisations and exemplars of student work are presented, based on the outlined visualisation approach.

International audience; Atom Probe Tomography (APT) technique is the only nano-scale-sensitive analytic tool allowing 3D chemical analysis with atomic scale resolution. For long restricted to conductive samples, implementation of ultra fast laser pulsing extend now the field of applications to the analysis of semiconductor materials. In the present study, high efficiency Cu(In, Ga)Se 2 (CIGSe) thin films have been investigated by APT in order to solve interrogations about grain boundaries (GBs) composition. The analyzed CIGSe layers have been grown by co-evaporation on Mo-coated soda-lime glass substrates following the standard 3-stage process and the atom probe tips prepared using a focused ion beam (FIB) equipment. In order to ensure the presence of GB in the small APT investigated volume, location and misorientation of GBs have been determined by electron backscattering scanning diffraction (EBSD) and one GB interface placed close to the edge of the tip. From APT analyses, spatial distribution of CIGSe elements can be imaged at atomic scale; particular attention has been devoted to the composition profiles at the vicinity of the CIGSe GB interface. New results are compared with usual CIGSe GB passivation models. © 2011 IEEE.

Exploitant les résultats d'une enquête ethnographique d'une société de multigestion, cette communication souhaite contribuer à une sociologie du calcul financier. Elle entend montrer que la rationalité financière gagne à être pensée à partir des modes de raisonnement effectivement menés par les acteurs qui pratiquent des activités financières, et non pas comme une entité logique transcendantale. Elle s'attache aux agents de rationalisation des processus de (multi-) gestion d'actifs et porte une attention particulière aux outils avec lesquels travaillent les analystes-multigérants pour choisir les fonds qu'ils intégreront à leurs portefeuilles. Ces éléments structurent la perception que les acteurs ont du monde de la gestion et construisent un ordre rationnel dans lequel se déploie l'activité. Mais ils n'empêchent pas les acteurs d'élaborer à leur tour des instruments symboliques avec lesquels donner sens à leur action. Au contraire, les artefacts matériels ou immatériels (supports d'écriture et formules de calcul par exemple) sont la trace d'une action humaine structurante autant qu'ils la structurent à leur tour. Résultant d'efforts destinés à dégager un profit monétaire dans un univers concurrentiel, les régimes de rationalité qui les accompagnent sont solidaires de pratiques de gestion qui sont elles-mêmes en affinité avec les positions qu'occupent les acteurs dans ce sous-espace de l'industrie financière.