129 research outputs found
A new route for the synthesis of Streptococcus pneumoniae 19F and 19A capsular polysaccharide fragments avoiding the beta-mannosamine glycosylation step
No full textSUMMARY The recently described (Carbohydr. Res. 2008, 43, 2545-2556) b-D-MaNAcp- (1→4)-b-D-Glcp thiophenyl glycosyl donor 3 was used in a-glycosylation reactions of OH-2 and OH-3 of the suitably protected p-MeO-benzyl a-L-rhamnopyranoside acceptors 7 and 8. The glycosylation of axial OH-2 of 7 took place in high yield (76%) and with good stereoselectivity (a/b = 3.4) leading to the protected trisaccharide a-11, corresponding to the repeating unit of Streptococcus pneumoniae 19F. The same reaction on equatorial OH-3 of acceptor 8 gave the trisaccharide a-15, constituent of the repeating unit of S. pneumoniae 19A, but in lower yield (41%) and without stereoselection (a/b = 1:1.3). Utilizing the introduced orthogonal protection of OH-1 and OH-4’’, the trisaccharide a-11 was transformed into a trisaccharide building block suitable for the synthesis of its phosphorylated oligomers
SSH researchers make an impact differently. Looking at public research from the perspective of users
No full textWith the rise of the impact assessment revolution, governments and public opinion have started to ask researchers to give evidence of their impact outside the traditional audiences, i.e. students and researchers. There is a mismatch between the request to demonstrate the impact and the current methodologies for impact assessment. This mismatch is particularly worrisome for the research in Social Sciences and Humanities. This paper gives a contribution by examining systematically a key element of impact, i.e. the social groups that are directly or indirectly affected by the results of research. We use a Text mining approach applied to the Research Excellence Framework (REF) collection of 6,637 impact case studies in order to identify social groups mentioned by researchers. Differently from previous studies, we employ a lexicon of user groups that includes 76,857 entries, which saturates the semantic field, permits the identification of all users and opens the way to normalization. We then develop three new metrics measuring Frequency, Diversity and Specificity of user expressions. We find that Social Sciences and Humanities exhibit a distinctive structure with respect to frequency and specificity of users
Extracting and mapping industry 4.0 technologies using wikipedia
No full textThe explosion of the interest in the industry 4.0 generated a hype on both academia and business: the former is attracted for the opportunities given by the emergence of such a new field, the latter is pulled by incentives and national investment plans. The Industry 4.0 technological field is not new but it is highly heterogeneous (actually it is the aggregation point of more than 30 different fields of the technology). For this reason, many stakeholders feel uncomfortable since they do not master the whole set of technologies, they manifested a lack of knowledge and problems of communication with other domains. Actually such problem is twofold, on one side a common vocabulary that helps domain experts to have a mutual understanding is missing Riel et al. [1], on the other side, an overall standardization effort would be beneficial to integrate existing terminologies in a reference architecture for the Industry 4.0 paradigm Smit et al. [2]. One of the basics for solving this issue is the creation of shared semantic for industry 4.0. The paper has an intermediate goal and focuses on the development of an enriched dictionary of Industry 4.0 enabling technologies, with definitions and links between them in order to help the user in actively surfing the new domains by starting from known elements to reach the most far away from his/her background and knowledge
In-line industrial contaminants discrimination for the packaging sorting based on near-infrared reflectance spectroscopy: A proof of concept
No full textThe Industry 4.0 paradigm requires new technologies and methods not only to improve the profitability and the quality of the industrial production and products, but also new strategies to reduce the social and environmental impact of the production process. Many line manufacturing chains unbox and assembly components to create products, but create a large amount of waste that sometimes can't be recycled because of the exposure to contaminants. When it comes to the automotive industry, mineral oils may contaminate plastic packaging and cardboard boxes during manufacturing, making hard to recycle them. In this paper we propose a proof of concept of a packaging sorting system based on NIR spectroscopy, to automate sorting and get high quality outputs for the recycling of cardboard package boxes. Spectral datasets have been pre-processed and dimensionally reduced using PCA A SVM algorithm has been trained to distinguish between oil contaminated and non contaminated materials. Two NIR spectrometers with sensing range 640-1050 nm and 950-1650 nm have been used and evaluated, to select the proper sensor configuration. Eventually, the system classification accuracy was respectively up to the 98,68% and 98,64% using the 950-1650 nm and the 640-1050 nm spectrometers, demonstrating the opportunity to detect mineral oil contamination on boxes
Is there a European university model? New evidence on national path dependence and structural convergence
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User indoor localisation system enhances activity recognition: A proof of concept
No full textOlder people would like to live independently in their home as long as possible. They want to reduce the risk of domestic accidents because of polypharmacy, physical weakness and other mental illnesses, which could increase the risks of domestic accidents (i.e. a fall). Changes in the behaviour of healthy older people could be correlated with cognitive disorders; consequently, early intervention could delay the deterioration of the disease. Over the last few years, activity recognition systems have been developed to support the management of senior citizensâ daily life. In this context, this paper aims to go beyond the state-of-the-art presenting a proof of concept where information on body movement, vital signs and userâs indoor locations are aggregated to improve the activity recognition task. The presented system has been tested in a realistic environment with three users in order to assess the feasibility of the proposed method. These results encouraged the use of this approach in activity recognition applications; indeed, the overall accuracy values, amongst others, are satisfactory increased (+2.67% DT, +7.39% SVM, +147.37% NN)
DATA FOR ENGINEERING DESIGN: MAPS AND GAPS
No full textData, information and knowledge are strongly involved in Engineering Design (ED) process. Despite the crucial role played by data in the design process, there is a lack of studies about how different data are used and generated by the various phases of the ED process. This study is a first attempt to fill this gap by mapping which data types are involved in the different ED phases from a research perspective.
In order to achieve this objective, we used a methodology based on Text Mining. Firstly, we retrieve a corpus of scientific papers related to ED; then, we build two lexicons to recognize ED phases and data types; finally, we collect these entities within ED papers and map the relations between them.
The methodology application allows the building of a network graph for visualizing the relations among data lexicon and ED lexicon. Then, we investigate the specific relations among data types and ED phases by building a heatmap to investigate data types from 3 different perspective.
The insight coming from our analysis shows that ED studies have a great potential in the usage of many data sources, but also that there exist some gaps to be solved in order to reach a more effective data usage in the context of ED
Industry 4.0 vs Industrie 4.0: how Different Countries See the Fourth Industrial Revolution. A quantitative study.
No full textDuring the past six years, industries all over the world have been undergoing a transformation which is often called Industry 4.0. Formulated in Germany in 2011, the 4.0 paradigm has been quickly translated in the rest of the developed world. Despite this rapid convergence of interest there is no common ground in the delineation of the field .
The goal of this paper is to understand how the concept of Industry 4.0 changes from nation to nation, putting the focus on the differences existing between Germany and the rest of the developed world. To reach this goal we take Wikipedia as a source of knowledge, generate a graph of pages which are connected to the German and English Industry 4.0 pages, sanitize the graphs and apply clustering analysis to the networks.
The first results show that the topic of Industry 4.0 is still more discussed in Germany with a focus on the development of production technologies. In contrast to this, topics like big data analysis and cloud computing play a major role outside of Germany, where focus is on creating data-driven business models and large, digital platforms in manufacturing industries
Value creation in emerging technologies through text mining: the case of blockchain
No full textAs technology progresses, organisations must understand where to direct
their value-creating efforts to achieve or sustain competitive advantage.
This is even more true in the case of emerging technologies, where
innovative activities often focus on achieving a technology promise
while overlooking a set of technological, operational, organisational and
user-related problems that must be overcome before the technology
can fulfil this promise. Through an innovative application of textmining, this paper develops a practical methodology to identify a range
of problems related to a technological field in an unsupervised manner,
that may benefit firms, researchers and policymakers. We apply the
methodology to the field of blockchain and compare it to traditional
literature reviews
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