413 research outputs found
Effective Unsupervised Author Disambiguation with Relative Frequencies
This work addresses the problem of author name homonymy in the Web of
Science. Aiming for an efficient, simple and straightforward solution, we
introduce a novel probabilistic similarity measure for author name
disambiguation based on feature overlap. Using the researcher-ID available for
a subset of the Web of Science, we evaluate the application of this measure in
the context of agglomeratively clustering author mentions. We focus on a
concise evaluation that shows clearly for which problem setups and at which
time during the clustering process our approach works best. In contrast to most
other works in this field, we are sceptical towards the performance of author
name disambiguation methods in general and compare our approach to the trivial
single-cluster baseline. Our results are presented separately for each correct
clustering size as we can explain that, when treating all cases together, the
trivial baseline and more sophisticated approaches are hardly distinguishable
in terms of evaluation results. Our model shows state-of-the-art performance
for all correct clustering sizes without any discriminative training and with
tuning only one convergence parameter.Comment: Proceedings of JCDL 201
Does updating education curricula accelerate technology adoption in the workplace? Evidence from dual vocational education and training curricula in Switzerland
In an environment of accelerating technological change and increasing digitalization, firms need to adopt new technologies faster than ever before to stay competitive. This paper examines whether updates of education curricula help to bring new technologies faster into firmsâ workplaces. We study technology changes and curriculum updates from an early wave of digitalization (i.e., computer-numerically controlled machinery, computer-aided design, and desktop publishing software). We take a text-as-data approach and tap into two novel data sources to measure change in educational content and the use of technology at the workplace: first, vocational education curricula and, second, firmsâ job advertisements. To examine the causal effects of adding new technology skills to curricula on the diffusion of these technologies in firmsâ workplaces (measured by job advertisements), we use an event study design. Our results show that curriculum updates substantially shorten the time it takes for new technologies to arrive in firmsâ workplaces, especially for mainstream firms
The role of fields of study for the effects of higher education institutions on regional firm location
The literature on knowledge spillovers provides evidence that higher education institutions (HEIs) positively affect regional firm location (i.e., start-ups or firms located in a region). However, less is known about how HEIs in different fields of study impact regional firm location in different industries. To investigate this question, we exploit the establishment of universities of applied sciences (UASs)âbachelorâs degree-granting three-year HEIs in Switzerland. We find that the effects of UASs are heterogeneous across fields of study and industries. UASs specializing in âchemistry and the life sciencesâ and âbusiness, management, and servicesâ are the only UASs that positively affect regional firm location across several industries. Positive effects emerge in service industries characterized by radical service, incremental product, or process innovations. Thus, UASs are not a one-size-fits-all solution for increasing regional firm location. Instead, only UASs specializing in particular fields of study positively influence firm location in certain industries
Different degrees of skill obsolescence across hard and soft skills and the role of lifelong learning for labor market outcomes
This paper examines the role of lifelong learning in counteracting skill depreciation and obsolescence. We differentiate between occupations with more hard skills versus more soft skills and draw on representative job advertisement data that contain machine-learning categorized skill requirements and cover the Swiss job market in great detail across occupations (from 1950 to 2019). We examine lifelong learning effects for âharderâ versus âsofterâ occupations, thereby analyzing the role of training in counteracting skill depreciation in occupations that are differently affected by skill depreciation. Our results reveal novel empirical patterns regarding the benefits of lifelong learning, which are consistent with theoretical explanations based on structurally different skill depreciation rates: In harder occupations, with large shares of fast-depreciating hard skills, the role of lifelong learning is primarily as a hedge against unemployment risks rather than a boost to wages. By contrast, in softer occupations, in which workers build on more value-stable soft-skill foundations, the role of lifelong learning instead lies mostly in acting as a boost for upward career mobility and leads to larger wage gains
Towards hierarchical affiliation resolution: framework, baselines, dataset
Author affiliations provide key information when attributing academic performance like publication counts. So far, such measures have been aggregated either manually or only to top-level institutions, such as universities. Supervised affiliation resolution requires a large number of annotated alignments between affiliation strings and known institutions, which are not readily available. We introduce the task of unsupervised hierarchical affiliation resolution, which assigns affiliations to institutions on all hierarchy levels (e.g. departments), discovering the institutions as well as their hierarchical ordering on the fly. From the corresponding requirements, we derive a simple conceptual framework based on the subset partial order that can be extended to account for the discrepancies evident in realistic affiliations from the Web of Science. We implement initial baselines and provide datasets and evaluation metrics for experimentation. Results show that mapping affiliations to known institutions and discovering lower-level institutions works well with simple baselines, whereas unsupervised top-level- and hierarchical resolution is more challenging. Our work provides structured guidance for further in-depth studies and improved methodology by identifying and discussing a number of observed difficulties and important challenges that future work needs to address
Tertiary education expansion and regional firm development
This study investigates the impact of a tertiary education expansion on regional firm development, as measured by average profits per firm. We exploit the quasi-random establishment of universities of applied sciences (UASs) â bachelorâs degree-granting three-year colleges teaching and conducting applied research â to construct treatment and control groups and to apply both a difference-in-differences model and an event study design. We find that after the establishment of new UASs in Switzerland, average profits per firm in the treated municipalities increase by 19.6% more than in the control group. This increase corresponds roughly to an additional annual growth in average profits per firm in the treatment group of 0.7%. The effects start shortly after the establishment of UASs but also persist over a period of up to 10 years
DynaVenn: web-based computation of the most significant overlap between ordered sets
Background: In many research disciplines, ordered lists are compared. One example is to compare a subset of all
significant genes or proteins in a primary study to those in a replication study. Often, the top of the lists are compared
using Venn diagrams, ore more precisely Euler diagrams (set diagrams showing logical relations between a finite
collection of different sets). If different cohort sizes, different techniques or algorithms for evaluation were applied, a
direct comparison of significant genes with a fixed threshold can however be misleading and approaches comparing
lists would be more appropriate.
Results: We developed DynaVenn, a web-based tool that incrementally creates all possible subsets from two or three
ordered lists and computes for each combination a p-value for the overlap. Respectively, dynamic Venn diagrams are
generated as graphical representations. Additionally an animation is generated showing how the most significant
overlap is reached by backtracking. We demonstrate the improved performance of DynaVenn over an arbitrary cut-off
approach on an Alzheimerâs Disease biomarker set.
Conclusion: DynaVenn combines the calculation of the most significant overlap of different cohorts with an intuitive
visualization of the results. It is freely available as a web service at http://www.ccb.uni-saarland.de/dynavenn
PLSDB: a resource of complete bacterial plasmids
The study of bacterial isolates or communities requires the analysis of the therein included plasmids
in order to provide an extensive characterization of
the organisms. Plasmids harboring resistance and
virulence factors are of especial interest as they
contribute to the dissemination of antibiotic resistance. As the number of newly sequenced bacterial
genomes is growing a comprehensive resource is
required which will allow to browse and filter the
available plasmids, and to perform sequence analyses. Here, we present PLSDB, a resource containing 13 789 plasmid records collected from the NCBI
nucleotide database. The web server provides an
interactive view of all obtained plasmids with additional meta information such as sequence characteristics, sample-related information and taxonomy.
Moreover, nucleotide sequence data can be uploaded
to search for short nucleotide sequences (e.g. specific genes) in the plasmids, to compare a given
plasmid to the records in the collection or to determine whether a sample contains one or multiple of the known plasmids (containment analysis).
The resource is freely accessible under https://ccbmicrobe.cs.uni-saarland.de/plsdb/
Education expansion and high-skill job opportunities for workers: Does a rising tide lift all boats?
We examine how education expansions affect the job opportunities for workers with and without the new education. To identify causal effects, we exploit a quasi-random establishment of Universities of Applied Sciences (UASs), bachelor-granting three-year colleges that teach and conduct applied research. By applying machine-learning methods to job advertisement data, we analyze job content before and after the education expansion. We find that, in regions with the newly established UASs, not only job descriptions of the new UAS graduates but also job descriptions of workers without this degree (i.e., middle-skilled workers with vocational training) contain more high-skill job content. This upskilling in job content is driven by an increase in high-skill R&D-related tasks and linked to employment and wage gains. The task spillovers likely occur because UAS graduates with applied research skills build a bridge between middle-skilled workers and traditional university graduates, facilitating the integration of the former into R&D-related tasks
Critical ProteinâProtein Interactions Determine the Biological Activity of Elk-1, a Master Regulator of Stimulus-Induced Gene Transcription
Elk-1 is a transcription factor that binds together with a dimer of the serum response factor
(SRF) to the serum-response element (SRE), a genetic element that connects cellular stimulation
with gene transcription. Elk-1 plays an important role in the regulation of cellular proliferation
and apoptosis, thymocyte development, glucose homeostasis and brain function. The biological
function of Elk-1 relies essentially on the interaction with other proteins. Elk-1 binds to SRF and
generates a functional ternary complex that is required to activate SRE-mediated gene transcription.
Elk-1 is kept in an inactive state under basal conditions via binding of a SUMO-histone deacetylase
complex. Phosphorylation by extracellular signal-regulated protein kinase, c-Jun N-terminal protein
kinase or p38 upregulates the transcriptional activity of Elk-1, mediated by binding to the mediator
of RNA polymerase II transcription (Mediator) and the transcriptional coactivator p300. Strong
and extended phosphorylation of Elk-1 attenuates Mediator and p300 recruitment and allows the
binding of the mSin3A-histone deacetylase corepressor complex. The subsequent dephosphorylation
of Elk-1, catalyzed by the protein phosphatase calcineurin, facilitates the re-SUMOylation of Elk1, transforming Elk-1 back to a transcriptionally inactive state. Thus, numerous proteinâprotein
interactions control the activation cycle of Elk-1 and are essential for its biological function
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