Bias in knowledge graphs - An empirical study with movie recommendation and different language editions of DBpedia

Public knowledge graphs such as DBpedia and Wikidata have been recognized as interesting sources of background knowledge to build content-based recommender systems. They can be used to add information about the items to be recommended and links between those. While quite a few approaches for exploiting knowledge graphs have been proposed, most of them aim at optimizing the recommendation strategy while using a fixed knowledge graph. In this paper, we take a different approach, i.e., we fix the recommendation strategy and observe changes when using different underlying knowledge graphs. Particularly, we use different language editions of DBpedia. We show that the usage of different knowledge graphs does not only lead to differently biased recommender systems, but also to recommender systems that differ in performance for particular fields of recommendations

ResearchSherlock: Toward a seamless integration of printed books into the digital academic workflow

With the increase of digital information practices (e.g. online search, desktop publishing, electronic reference management, etc.) in the academic context, printed books are sometimes cumbersome to integrate into the digital workflow. We present ResearchSherlock, an Android app that allows the user to quickly gather bibliographic information for a printed book by scanning its shelfmark or ISBN. The application also provides recommenddations for thematically related books, to promote the discovery of other relevant books that are available in the local library

Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data

The Contribution of Halos with Different Mass Ratios to the Overall Growth of Cluster-Sized Halos

We provide a new observational test for a key prediction of the \Lambda CDM cosmological model: the contributions of mergers with different halo-to-main-cluster mass ratios to cluster-sized halo growth. We perform this test by dynamically analyzing seven galaxy clusters, spanning the redshift range $0.13 < z_c < 0.45$ and caustic mass range $0.4-1.5$ $10^{15} h_{0.73}^{-1}$ M$_{\odot}$, with an average of 293 spectroscopically-confirmed bound galaxies to each cluster. The large radial coverage (a few virial radii), which covers the whole infall region, with a high number of spectroscopically identified galaxies enables this new study. For each cluster, we identify bound galaxies. Out of these galaxies, we identify infalling and accreted halos and estimate their masses and their dynamical states. Using the estimated masses, we derive the contribution of different mass ratios to cluster-sized halo growth. For mass ratios between ~0.2 and ~0.7, we find a ~1 $\sigma$ agreement with \Lambda CDM expectations based on the Millennium simulations I and II. At low mass ratios, $\lesssim 0.2$, our derived contribution is underestimated since the detection efficiency decreases at low masses, $\sim 2 \times 10^{14}$ $h_{0.73}^{-1}$ M$_{\odot}$. At large mass ratios, $\gtrsim 0.7$, we do not detect halos probably because our sample, which was chosen to be quite X-ray relaxed, is biased against large mass ratios. Therefore, at large mass ratios, the derived contribution is also underestimated.Comment: 25 pages, 16 figures, 6 tables, 2 machine readable tables, accepted for publication in ApJ, updated acknowledgements and data table format modifications mad

Longitudinal ambulatory measurements of gait abnormality in dystrophin-deficient dogs

Chantier qualité GAInternational audienceABSTRACT: BACKGROUND: This study aimed to measure the gait abnormalities in GRMD (Golden retriever muscular dystrophy) dogs during growth and disease progression using an ambulatory gait analyzer (3D-accelerometers) as a possible tool to assess the effects of a therapeutic intervention. METHODS: Six healthy and twelve GRMD dogs were evaluated twice monthly, from the age of two to nine months. The evolution of each gait variable previously shown to be modified in control and dystrophin-deficient adults was assessed using two-ways variance analysis (age, clinical status) with repeated measurements. A principal component analysis (PCA) was applied to perfect multivariate data interpretation. RESULTS: Speed, stride length, total power and force significantly already decreased (p < 0.01) at the age of 2 months. The other gait variables (stride frequency, relative power distributions along the three axes) became modified at later stages. Using the PCA analysis, a global gait index taking into account the main gait variables was calculated, and was also consistent to detect the early changes in the GRMD gait patterns, as well as the progressive degradation of gait quality. CONCLUSION: The gait variables measured by the accelerometers were sensitive to early detect and follow the gait disorders and mirrored the heterogeneity of clinical presentations, giving sense to monitor gait in GRMD dogs during progression of the disease and pre-clinical therapeutic trials

anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data

Background: Compared to other omics techniques, quantitative metabolomics is still at its infancy. Complex sample preparation and analytical procedures render exact quantification extremely difficult. Furthermore, not only the actual measurement but also the subsequent interpretation of quantitative metabolome data to obtain mechanistic insights is still lacking behind the current expectations. Recently, the method of network-embedded thermodynamic (NET) analysis was introduced to address some of these open issues. Building upon principles of thermodynamics, this method allows for a quality check of measured metabolite concentrations and enables to spot metabolic reactions where active regulation potentially controls metabolic flux. So far, however, widespread application of NET analysis in metabolomics labs was hindered by the absence of suitable software. Results: We have developed in Matlab a generalized software called 'anNET' that affords a user-friendly implementation of the NET analysis algorithm. anNET supports the analysis of any metabolic network for which a stoichiometric model can be compiled. The model size can span from a single reaction to a complete genome-wide network reconstruction including compartments. anNET can (i) test quantitative data sets for thermodynamic consistency, (ii) predict metabolite concentrations beyond the actually measured data, (iii) identify putative sites of active regulation in the metabolic reaction network, and (iv) help in localizing errors in data sets that were found to be thermodynamically infeasible. We demonstrate the application of anNET with three published Escherichia coli metabolome data sets. Conclusion: Our user-friendly and generalized implementation of the NET analysis method in the software anNET allows users to rapidly integrate quantitative metabolome data obtained from virtually any organism. We envision that use of anNET in labs working on quantitative metabolomics will provide the systems biology and metabolic engineering communities with a mean to proof the quality of metabolome data sets and with all further benefits of the NET analysis approach.

Lensed arc statistics: comparison of Millennium-simulation galaxy clusters to Hubble Space Telescope observations of an X-ray selected sample

It has been debated for a decade whether there is a large overabundance of strongly lensed arcs in galaxy clusters, compared to expectations from LambdaCDM cosmology. We perform ray tracing through the most massive halos of the Millennium simulation at several redshifts in their evolution, using the Hubble Ultra Deep Field as a source image, to produce realistic simulated lensed images. We compare the lensed arc statistics measured from the simulations to those of a sample of 45 X-ray selected clusters, observed with the Hubble Space Telescope, that we have analysed in Horesh et al. (2010). The observations and the simulations are matched in cluster masses, redshifts, observational effects, and the algorithmic arc detection and selection. At z=0.6 there are too few massive-enough clusters in the Millennium volume for a proper statistical comparison with the observations. At redshifts 0.3<z<0.5, however, we have large numbers of simulated and observed clusters, and the latter are an unbiased selection from a complete sample. For these redshifts, we find excellent agreement between the observed and simulated arc statistics, in terms of the mean number of arcs per cluster, the distribution of number of arcs per cluster, and the angular separation distribution. At z ~ 0.2 some conflict remains, with real clusters being ~3 times more efficient arc producers than their simulated counterparts. This may arise due to selection biases in the observed subsample at this redshift, to some mismatch in masses between the observed and simulated clusters, or to physical effects that arise at low redshift and enhance the lensing efficiency, but which are not represented by the simulations.Comment: 10 pages, 8 figures, Accepted by MNRA

Faseroptische Schaltmodule

Gegenstand dieser Arbeit ist die Entwicklung faseroptischer Schaltmodule. Hierzu werden Einsatzgebiete beschrieben und ein systematisierender Vergleich über optische Schalter, optische Abschwächer und das Signalmonitoring für Schaltmodule beliebiger Größenordnungen gegeben. Am Beispiel eines 2x2-Schaltmoduls für Singlemodefasern wird die Optimierung durch die Funktionsintegration Schalten und variables Abschwächen dargestellt. Das entwickelte mechanische Schaltkonzept basiert auf einer Freistrahlausbreitung mit kollimierten Lichtstrahlen und einem Umschalten durch bewegte Spiegel, wobei die Abschwächung durch ein definiertes Verrücken der Spiegel und einer daraus resultierenden Fehleinkopplung realisiert wird. Ein universelles Berechnungsverfahren wird vorgestellt, mit dem sich die erforderliche Positioniergenauigkeit zur Realisierung einer beliebigen Verbindung von Singlemodefasern bestimmen lässt. Ferner wird die Abschwächung durch in die Freistrahlausbreitungsstrecke eingeführte Blenden untersucht. Gezeigt wird die Entwicklung von Linearantrieben, die beliebige Positionen einnehmen, sowie diese strom- und spannungslos halten können. Der im Schaltmodul eingesetzte elektrodynamische Linearantrieb mit einem Stellweg > 3 mm basiert auf einer Parallelführung, einer Spule mit Magnetkreis, zwei Klemmaktoren zur Selbsthaltung und einem eingebauten Positionssensor für einen geregelten Betrieb. Die Einhaltung der optischen Anforderungen des 2x2-Schaltmoduls ist weitgehend experimentell nachgewiesen. Konzepte zur Miniaturisierung des Schaltmoduls werden beschrieben

Probenentnahme für Algenzellkulturen

Zusammenfassung: Aufgabenstellung dieser Arbeit ist es, Volumina einer Algenzellkultur (ca. 20 - 100ml) zu bestimmten Zeiten aus einem Anzucht-Fermenter zu entnehmen, vom Wasser zu trennen und die Algenzellen in einem Behälter mit flüssigem Stickstoff abzuwerfen. Die Probenentnahme soll stündlich erfolgen. Entwickelt wurde ein Automat, der zu festgelegten Zeitpunkten die Algensuspension aus zwei Anzucht-Fermentern entnimmt und auf ein vor Versuchsbeginn eingestelltes Suspensionsvolumen abmißt. Die Fermenter werden für die Suspensionsentnahme verschlossen, so daß die zugeführte Luft einen Überdruck im Fermenter erzeugt und die Algensuspension durch die geöffnete Entnahmeleitung aus dem Fermenter herausdrückt. Das Suspensionsvolumen wird nach dem Überlaufprinzip abgemessen. Hierbei wir die Algensuspension in ein Gefäß mit einstellbarem Volumen geleitet. Ist das Gefäß voll, läuft die überschüssige Algensuspension in ein weiteres Gefäß ab. In diesem befindet sich ein Sensor, der den Fördervorgang abbricht. In dem Gefäß befindet sich das definierte Suspensionsvolumen. Die kontaminierten Leitungen werden anschließend gespült. Für die Eingabe der Entnahmezeiten und für die Ablaufsteuerung wird ein PC verwendet. Das Problem, die Algen aus dem Wasser zu extrahieren, behandelt eine Machbarkeitsstudie. Die Studie repräsentiert drei realisierbare Lösungen, die modulartig in den entstandenen Automat integriert werden können, nämlich eine durch Filtern, eine durch Zentrifugieren und eine Lösung, bei der die Algensuspension komplett tiefgefroren bzw. nur heruntergekühlt wird, ohne die Algen vorher aus dem Wasser zu extrahieren. Der Vorteil bei diesem Verfahren liegt im geringen technischen Aufwand. Versuche zur Eignung dieser Lösung wurden eingeleitet. Technische Daten: * Sterile Suspensionsentnahme aus zwei Anzucht-Fermentern * Entnehmbare Algenzellgröße: 5 - 10µm * Einstellbares Volumen für die Entnahme: 10 - 105ml * Vollautomatische Ablaufsteuerun