Reducing the Probability of False Positive Research Findings by Pre-Publication Validation - Experience with a Large Multiple Sclerosis Database

*Objective*
We have assessed the utility of a pre-publication validation policy in reducing the probability of publishing false positive research findings. 
*Study design and setting*
The large database of the Sylvia Lawry Centre for Multiple Sclerosis Research was split in two parts: one for hypothesis generation and a validation part for confirmation of selected results. We present case studies from 5 finalized projects that have used the validation policy and results from a simulation study.
*Results*
In one project, the "relapse and disability" project as described in section II (example 3), findings could not be confirmed in the validation part of the database. The simulation study showed that the percentage of false positive findings can exceed 20% depending on variable selection. 
*Conclusion*
We conclude that the validation policy has prevented the publication of at least one research finding that could not be validated in an independent data set (and probably would have been a "true" false-positive finding) over the past three years, and has led to improved data analysis, statistical programming, and selection of hypotheses. The advantages outweigh the lost statistical power inherent in the process

A novel procedure for fast surface structural analysis based on LEED intensity data

By evaluating LEED intensities from different diffraction beams taken only at discrete energy intervals (which may be as large as 15–20 eV) the same degree of reliability in surface structure determination can be reached as with the conventional techniques based on analysis of continuous I/V-spectra. The minimum of the corresponding R-factor can be found by a least-squares fit method, as will be exemplified with a system in which 8 structural parameters were subject to simultaneous refinement

A passive GHz frequency-division multiplexer/demultiplexer based on anisotropic magnon transport in magnetic nanosheets

The emerging field of magnonics employs spin waves and their quanta, magnons, to implement wave-based computing on the micro- and nanoscale. Multi-frequency magnon networks allow for parallel data processing within single logic elements whereas this is not the case with conventional transistor-based electronic logic. However, a lack of experimentally proven solutions to efficiently combine and separate magnons of different frequencies has impeded the intensive use of this concept. In this Letter, we demonstrate the experimental realization of a spin-wave demultiplexer enabling frequency-dependent separation of GHz signals. The device is based on two-dimensional magnon transport in the form of spin-wave beams in unpatterned magnetic nanosheets. The intrinsic frequency-dependence of the beam direction is exploited to realize a passive functioning obviating an external control and additional power consumption. This approach paves the way to magnonic multiplexing circuits enabling simultaneous information transport and processing.Comment: 16 pages, 3 figure

Double-blind, placebo-controlled first in human study to investigate an oral vaccine aimed to elicit an immune reaction against the VEGF-Receptor 2 in patients with stage IV and locally advanced pancreatic cancer

BACKGROUND: The investigational oral DNA vaccine VXM01 targets the vascular endothelial growth factor receptor 2 (VEGFR-2) and uses Salmonella typhi Ty21a as a vector. The immune reaction elicited by VXM01 is expected to disrupt the tumor neovasculature and, consequently, inhibit tumor growth. VXM01 potentially combines the advantages of anti-angiogenic therapy and active immunotherapy. METHODS/DESIGN: This phase I trial examines the safety, tolerability, and immunological and clinical responses to VXM01. The randomized, placebo-controlled, double blind dose-escalation study includes up to 45 patients with locally advanced and stage IV pancreatic cancer. The patients will receive four doses of VXM01 or placebo in addition to gemcitabine as standard of care. Doses from 10(6) cfu up to 10(10) cfu of VXM01 will be evaluated in the study. An independent data safety monitoring board (DSMB) will be involved in the dose-escalation decisions. In addition to safety as primary endpoint, the VXM01-specific immune reaction, as well as clinical response parameters will be evaluated. DISCUSSION: The results of this study shall provide the first data regarding the safety and immunogenicity of the oral anti-VEGFR-2 vaccine VXM01 in cancer patients. They will also define the recommended dose for phase II and provide the basis for further clinical evaluation, which may also include additional cancer indications. TRIAL REGISTRATION: EudraCT No.: 2011-000222-29, NCT01486329, ISRCTN6880927

Selecting Data Assets in Data Marketplaces – Leveraging Machine Learning and Explainable AI for Value Quantification

In the era of digital transformation, data is a critical asset driving innovation and competitive advantage for businesses. Data marketplaces have emerged as a key solution for data sharing, yet they face significant challenges, including competitive concerns, matchmaking between data providers and consumers, and a lack of appropriate market mechanisms. This study introduces a data asset value quantification and selection mechanism (DQSM) as an innovative feature for data marketplaces to address these concerns. The DQSM uses Machine Learning and Explainable AI methods to assess the value of data assets, aiding consumers in making informed purchasing decisions. This mechanism addresses the inherent complexities of data asset valuation and selection, thereby increasing marketplace efficiency. Using a design science research approach, the study identifies design principles for the development of the DQSM as a feature of data marketplaces, which are validated through technical experiments with industry and public datasets, as well as interviews with experts in this field. The findings highlight the potential of the DQSM to optimize the discovery and implementation of viable data sharing use cases and to incentivize the adoption of data marketplaces, thereby contributing to more viable and sustainable data ecosystems

All uns’re problems oder: ›Witty, sexy, gimmicky, glamorous‹ heute

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Super Wirklichkeit

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Schimmernder Dunst. Konsumrealismus und die paralogischen Pop-Potenziale

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Schleiermacher ÄKSCHN

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