The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems

Social bookmarking systems have established themselves as an important part in today’s Web. In such systems, tag recommender systems support users during the posting of a resource by suggesting suitable tags. Tag recommender algorithms have often been evaluated in offline benchmarking experiments. Yet, the particular setup of such experiments has rarely been analyzed. In particular, since the recommendation quality usually suffers from difficulties such as the sparsity of the data or the cold-start problem for new resources or users, datasets have often been pruned to so-called cores (specific subsets of the original datasets), without much consideration of the implications on the benchmarking results. In this article, we generalize the notion of a core by introducing the new notion of a set-core, which is independent of any graph structure, to overcome a structural drawback in the previous constructions of cores on tagging data. We show that problems caused by some types of cores can be eliminated using set-cores. Further, we present a thorough analysis of tag recommender benchmarking setups using cores. To that end, we conduct a large-scale experiment on four real-world datasets, in which we analyze the influence of different cores on the evaluation of recommendation algorithms. We can show that the results of the comparison of different recommendation approaches depends on the selection of core type and level. For the benchmarking of tag recommender algorithms, our results suggest that the evaluation must be set up more carefully and should not be based on one arbitrarily chosen core type and level

Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy

In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points

CO2 Gasification of Biomass Chars: A Kinetic Study

The CO2 gasification of pine and birch charcoals was studied by thermogravimetric analysis (TGA) at CO2 partial pressures of 51 and 101 kPa. Linear and stepwise heating programs were employed to increase the information content of the experimental data sets. Low sample masses were used because of the high enthalpy change. Seven experiments with different experimental conditions were evaluated simultaneously for each sample. The method of least-squares was employed. Three reactions appeared in the temperature domain evaluated (600-1000 degrees C). The first and second reactions were due to the devolatilization and did not show a significant dependence upon the CO2 concentration. They were approximated by first-order kinetics. The third reaction corresponded to the gasification. Its modeling was based on an empirical approximation of the change of the reaction surface during the gasification and by a formal reaction order with respect to the CO2 concentration. Very close results were obtained for the two charcoals. The dependence upon the conversion could be well-approximated by power law kinetics. In the next step of the evaluation, the experiments of the two samples (14 experiments combined) were evaluated together, assuming common activation energy values and a common reaction order with respect to the CO2 concentration. This process led to nearly the same fit as the separate evaluation of the two samples. The activation energy of the gasification step was 262 kJ/mol. The reaction order of CO2 was 0.40

Ablation and functionalization of flexographic printing forms using femtosecond lasers for additively manufactured polymer-optical waveguides

An efficient and low-cost approach to manufacture Opto-Mechatronic Interconnect Devices will be obligatory to handle the strongly increasing amount of data. The presented approach is based on a flexographic printing process. To adjust the transferred material the printing form is functionalized by means of laser-induced structures using an ultrashort-pulsed laser. The long-term goal is to adjust the printing result through microstructures in the printing form in order to create spatially resolved material transfer. In this work, first the ablation parameters are investigated at different repetition rates using a femtosecond laser. Further, a line structure is inserted in the material transferring areas of the printing form, which is consequently widened. Its influence on the printing result is presented. © 2020 The Authors. Published by Elsevier B.V

Towards a Soft Evaluation and Refinement of Tagging in Digital Humanities

In this paper we estimate the soundness of tagging in digital repositories within the field of Digital Humanities by studying the (semantic) conceptual structure behind the folksnonomy. The use of association rules associated to this conceptual structure (Stem and Luxenburger basis) allows to faithfully (from a semantic point of view) complete the tagging (or suggest such a completion).Ministerio de Economía y Competitividad TIN2013-41086-PJunta de Andalucía TIC-606

Fast-exchanging spirocyclic rhodamine probes for aptamer-based super-resolution RNA imaging

Live-cell RNA imaging with high spatial and temporal resolution remains a major challenge. Here we report the development of RhoBAST:SpyRho, a fluorescent light-up aptamer (FLAP) system ideally suited for visualizing RNAs in live or fixed cells with various advanced fluorescence microscopy modalities. Overcoming problems associated with low cell permeability, brightness, fluorogenicity, and signal-to-background ratio of previous fluorophores, we design a novel probe, SpyRho (Spirocyclic Rhodamine), which tightly binds to the RhoBAST aptamer. High brightness and fluorogenicity is achieved by shifting the equilibrium between spirolactam and quinoid. With its high affinity and fast ligand exchange, RhoBAST:SpyRho is a superb system for both super-resolution SMLM and STED imaging. Its excellent performance in SMLM and the first reported super-resolved STED images of specifically labeled RNA in live mammalian cells represent significant advances over other FLAPs. The versatility of RhoBAST:SpyRho is further demonstrated by imaging endogenous chromosomal loci and proteins

Tag Recommendation for Large-Scale Ontology-Based Information Systems

We tackle the problem of improving the relevance of automatically selected tags in large-scale ontology-based information systems. Contrary to traditional settings where tags can be chosen arbitrarily, we focus on the problem of recommending tags (e.g., concepts) directly from a collaborative, user-driven ontology. We compare the effectiveness of a series of approaches to select the best tags ranging from traditional IR techniques such as TF/IDF weighting to novel techniques based on ontological distances and latent Dirichlet allocation. All our experiments are run against a real corpus of tags and documents extracted from the ScienceWise portal, which is connected to ArXiv.org and is currently used by growing number of researchers. The datasets for the experiments are made available online for reproducibility purposes

Synthesis by High-Efficiency Liquid-Phase (HELP) Method of Oligonucleotides Conjugated with High-Molecular Weight Polyethylene Glycols (PEGs)

The chemical modification of synthetic oligonucleotides has recently been investigated to improve their pharmacological utilization. In addition to chemical alterations of the backbone and of the heterocyclic bases, their conjugation with amphiphylic moieties, such as the polyethylene glycol has been proposed. The large scale production of these molecules as demanded for commercial purposes is hampered by the heterogeneity of the solid-phase processes and by the low reactivity of high-molecular weight PEGs in solution. A new synthetic procedure based on the recently developed liquid-phase method (HELP), has been set up to overcome these limitations

Unsupervised machine learning on encrypted data

In the context of Fully Homomorphic Encryption, which allows computations on encrypted data, Machine Learning has been one of the most popular applications in the recent past. All of these works, however, have focused on supervised learning, where there is a labeled training set that is used to configure the model. In this work, we take the first step into the realm of unsupervised learning, which is an important area in Machine Learning and has many real-world applications, by addressing the clustering problem. To this end, we show how to implement the K-Means-Algorithm. This algorithm poses several challenges in the FHE context, including a division, which we tackle by using a natural encoding that allows division and may be of independent interest. While this theoretically solves the problem, performance in practice is not optimal, so we then propose some changes to the clustering algorithm to make it executable under more conventional encodings. We show that our new algorithm achieves a clustering accuracy comparable to the original K-Means-Algorithm, but has less than $5\%$ of its runtime

Three critical hydrogen bonds determine the catalytic activity of the Diels–Alderase ribozyme

Compared to protein enzymes, our knowledge about how RNA accelerates chemical reactions is rather limited. The crystal structures of a ribozyme that catalyzes Diels–Alder reactions suggest a rich tertiary architecture responsible for catalysis. In this study, we systematically probe the relevance of crystallographically observed ground-state interactions for catalytic function using atomic mutagenesis in combination with various analytical techniques. The largest energetic contribution apparently arises from the precise shape complementarity between transition state and catalytic pocket: A single point mutant that folds correctly into the tertiary structure but lacks one H-bond that normally stabilizes the pocket is completely inactive. In the rate-limiting chemical step, the dienophile is furthermore activated by two weak H-bonds that contribute ∼7–8 kJ/mol to transition state stabilization, as indicated by the 25-fold slower reaction rates of deletion mutants. These H-bonds are also responsible for the tight binding of the Diels–Alder product by the ribozyme that causes product inhibition. For high catalytic activity, the ribozyme requires a fine-tuned balance between rigidity and flexibility that is determined by the combined action of one inter-strand H-bond and one magnesium ion. A sharp 360° turn reminiscent of the T-loop motif observed in tRNA is found to be important for catalytic function