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DeepGreen—A Data Hub for the Distribution of Scholarly Articles From Publishers to Open Access Repositories in Germany
No full textDeepGreen is an automated delivery service for open access articles. Originally conceived to take advantage of the so-called open access component—a secondary publication right in Alliance and National licences in Germany to promote green open access—it aims to streamline open access processes by automating the distribution of full-text articles and metadata from publishers to repositories.
The service, developed by a consortium and funded by the German Research Foundation (DFG) in its initial phase, has successfully established itself as a national service, facilitating open access content distribution and contributing to Germany's open access infrastructure.
As of December 2024, DeepGreen distributes articles from 14 publishers to 84 institutional repositories and 6 subject-specific repositories.
This article describes the role of the DeepGreen service in Germany, its collaboration with publishers and the potential of automated processes for storing articles in open access repositories, which, as publicly owned institutional infrastructures, ensure sustainable access and provide secure, redundant storage
Quantum Optimization Benchmark Library -- The Intractable Decathlon
No full textThrough recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particularly in combinatorial optimization -- where most algorithms are heuristics -- it is key to empirically analyze their performance on hardware and track progress towards quantum advantage. To this extent, we present ten optimization problem classes that are difficult for existing classical algorithms and can (mostly) be linked to practically-relevant applications, with the goal to enable systematic, fair, and comparable benchmarks for quantum optimization methods. Further, we introduce the Quantum Optimization Benchmark Library (QOBLIB) where the problem instances and solution track records can be found. The individual properties of the problem classes vary in terms of objective and variable type, coefficient ranges, and density. Crucially, they all become challenging for established classical methods already at system sizes ranging from less than 100 to, at most, an order of 100,000 decision variables, allowing to approach them with today's quantum computers. We reference the results from state-of-the-art solvers for instances from all problem classes and demonstrate exemplary baseline results obtained with quantum solvers for selected problems. The baseline results illustrate a standardized form to present benchmarking solutions, which has been designed to ensure comparability of the used methods, reproducibility of the respective results, and trackability of algorithmic and hardware improvements over time. We encourage the optimization community to explore the performance of available classical or quantum algorithms and hardware platforms with the benchmarking problem instances presented in this work toward demonstrating quantum advantage in optimization
Is innovation slowing down? Insights from the AIMS framework of patent values
No full textAmidst the unprecedented expansion of scientific and technological knowledge over the past century, concerns persist regarding a slowdown in innovation. To address this, we introduce the AIMS framework, which categorizes patents into four types—Aurora, Invisible, Mirage, and Success—based on their respective inherent scientific values and market-recognized economic values. Utilizing USPTO patent and citation data from 1976 to 2022, our analysis reveals an increasing volume of patent issuances but a concerning dilution in scientific quality starting in the 2000s. This trend is primarily attributed to the rise of low scientific value patents—categorized as Mirage and Invisible—and a modest decline in high-impact scientific patents—categorized as Success and Aurora. Meanwhile, the economic value of patents has risen, especially noted with the growth in Mirage patents since the 2010s, indicating a shift towards strategies that prioritize market-driven patenting. This study highlights the evolving nature of patents from mere indicators of scientific innovation to strategic tools for market dominance, providing an alternative understanding of patent value and its implications for firms’ strategic decisions over patent issuance across different sectors
A connectomic resource for neural cataloguing and circuit dissection of the larval zebrafish brain
No full textWe present a correlated light and electron microscopy (CLEM) dataset from a 7-day-old larval zebrafish, integrating confocal imaging of genetically labeled excitatory (vglut2a) and inhibitory (gad1b) neurons with nanometer-resolution serial section EM. The dataset spans the brain and anterior spinal cord, capturing >180,000 segmented soma, >40,000 molecularly annotated neurons, and 30 million synapses, most of which were classified as excitatory, inhibitory, or modulatory. To characterize the directional flow of activity across the brain, we leverage the synaptic and cell body annotations to compute region-wise input and output drive indices at single cell resolution. We illustrate the dataset’s utility by dissecting and validating circuits in three distinct systems: water flow direction encoding in the lateral line, recurrent excitation and contralateral inhibition in a hindbrain motion integrator, and functionally relevant targeted long-range projections from a tegmental excitatory nucleus, demonstrating that this resource enables rigorous hypothesis testing as well as exploratory-driven circuit analysis. The dataset is integrated into an open-access platform optimized to facilitate community reconstruction and discovery efforts throughout the larval zebrafish brain
Interobserver Reliability of the Modified Radiographic Union Score (mRUST) for Tibial and Femoral Fractures
No full textOBJECTIVES:
To evaluate the reliability of the modified Radiographic Union Score for Tibial fractures (mRUST) as a reliable tool for monitoring lower limb fractures (femur, tibia) treated with various modalities (nail, plate).
METHODS:
Design:
Retrospective analysis.
Setting:
Single center academic hospital in Germany.
Patient Selection Criteria:
Adult patients (≥18 years) with extra-articular long bone fractures of the lower extremities treated surgically between January 2005 and April 2022, requiring radiographs in two perpendicular planes and at least one follow-up visit, were included. Exclusion criteria were critical clinical conditions, inability to consent, joint articulation fractures, inadequate documentation, or insufficient imaging quality.
Outcome Measures and Comparisons:
Six international investigators (five orthopedic surgeons, one radiologist) independently assessed fracture line and callus growth per cortex (mRUST) at individualized follow-up time points based on clinical practice. To evaluate interrater reliability, intraclass correlation coefficients were calculated for the overall dataset, and for subsets of rated images, that were defined based on anatomical location (femur/tibia), treatment type (plate/nail fixation), and treatment combinations across locations.
RESULTS:
A total of 166 patients (63 femur fractures, 103 tibia fractures; 32.5% female, mean age 43.4 (18–84)) with 1136 follow-up time points were analyzed. Overall interrater reliability for mRUST was good (intraclass correlation coefficient 0.77), consistent across fixation methods (nail/plate fixation, 0.79) and anatomical locations (tibia, 0.78; femur, 0.81). Cortex-specific reliability varied, with highest agreement for the medial cortex (0.70–0.74) and lowest for the posterior cortex (0.65–0.74).
CONCLUSIONS:
The mRUST (radiographic score) demonstrated reliability for monitoring fracture healing in the femur and tibia, irrespective of fixation method, supporting its use as a generalizable tool across lower limb fractures.
LEVEL OF EVIDENCE:
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence
MoMo - Combining Neuron Morphology and Connectivity for Interactive Motif Analysis in Connectomes
No full textConnectomics, a subfield of neuroscience, reconstructs structural and functional brain maps at synapse-level resolution. These complex spatial maps consist of tree-like neurons interconnected by synapses. Motif analysis is a widely used method for identifying recurring subgraph patterns in connectomes. These motifs, thus, potentially represent fundamental units of information processing. However, existing computational tools often oversimplify neurons as mere nodes in a graph, disregarding their intricate morphologies. In this paper, we introduce MoMo, a novel interactive visualization framework for analyzing neuron morphology-aware motifs in large connectome graphs. First, we propose an advanced graph data structure that integrates both neuronal morphology and synaptic connectivity. This enables highly efficient, parallel subgraph isomorphism searches, allowing for interactive morphological motif queries. Second, we develop a sketch-based interface that facilitates the intuitive exploration of morphology-based motifs within our new data structure. Users can conduct interactive motif searches on state-of-the-art connectomes and visualize results as interactive 3D renderings. We present a detailed goal and task analysis for motif exploration in connectomes, incorporating neuron morphology. Finally, we evaluate MoMo through case studies with four domain experts, who asses the tool’s usefulness and effectiveness in motif exploration, and relevance to real-world neuroscience research. The source code for MoMo is available here: https://github.com/VCG/momo
A Compact Cycle Formulation for the Multiperiodic Event Scheduling Problem
No full textThe Periodic Event Scheduling Problem (PESP) is a fundamental model in periodic timetabling for public transport systems, assuming a common period across all events. However, real-world networks often feature heterogeneous service frequencies. This paper studies the Multiperiodic Event Scheduling Problem (MPESP), a generalization of PESP that allows each event to recur at its own individual period. While more expressive, MPESP presents new modeling challenges due to the loss of a global period. We present a cycle-based formulation for MPESP that extends the strongest known formulation for PESP and, in contrast to existing approaches, is valid for any MPESP instance. Crucially, the formulation requires a cycle basis derived from a spanning tree satisfying specific structural properties, which we formalize and algorithmically construct, extending the concept of sharp spanning trees to rooted instances. We further prove a multiperiodic analogue of the cycle periodicity property. Our new formulation solves nearly all tested instances, including several large-scale real-world public transport networks, to optimality or with small optimality gaps, dramatically outperforming existing arc-based models. The results demonstrate the practical potential of MPESP in capturing heterogeneous frequencies without resorting to artificial event duplication
