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Proof of Existence as a blockchain service has first been published in 2013 as a public notary service on the Bitcoin network and can be used to verify the existence of a particular file in a specific point of time without sharing the file or its content itself. This service is also available on the Ethereum based bloxberg network, a decentralized research infrastructure that is governed, operated and developed by an international consortium of research facilities. Since it is desirable to integrate the creation of this proof tightly into the research workflow, namely the acquisition and processing of research data, we show a simple to integrate MATLAB extension based solution with the concept being applicable to other programming languages and environments as well.
The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that requires less manual intervention - especially the mining of chemical structure depictions. As an open-source platform that leverages recent advancements in deep learning, computer vision, and natural language processing, DECIMER.ai (Deep lEarning for Chemical IMagE Recognition) strives to automatically segment, classify, and translate chemical structure depictions from the printed literature. The segmentation and classification tools are the only openly available packages of their kind, and the optical chemical structure recognition (OCSR) core application yields outstanding performance on all benchmark datasets. The source code, the trained models and the datasets developed in this work have been published under permissive licences. An instance of the DECIMER web application is available at https://decimer.ai.
To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.
In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.
Design and Development of a Bioreactor System for Mechanical Stimulation of Musculoskeletal Tissue
(2023)
We report on the development of a bioreactor system for mechanical stimulation of musculoskeletal tissues. The ultimate object is to improve the quality of medical treatment following injuries of the enthesis tissue. To this end, the tissue formation process through the effect of mechanical stimulation is investigated. A six-well system was designed, 3D printed and tested. An integrated actuator creates strain by applying a force. A contactless position sensor monitors the travels. An electronic circuit controls the bioreactor using a microcontroller. An IoT platform connects the microcontroller to a smartphone, enabling the user to alter variables, trigger actions and monitor the system. The system was stabilised by implementing two PID controllers and safety measures. The results show that the bioreactor design is suited to execute mechanical stimulation and to investigate the tissue formation and regeneration process …
We argue that effective leadership development should be evidence-based, i.e. that it combines the best available scientific evidence with
research in the specific organizational context. To illustrate our proposition, we report findings from a case study in a multinational organization. The goal was to examine which rater source in the company’s 360 degree feedback would provide the most valid information about leadership competencies. Therefore, we explored relationships between 360 degree ratings and assessment center (AC) ratings of the same leadership competencies (N=151). It was predicted that AC ratings show higher overlap with 360 degree ratings for behaviors that specific rating
sources can more easily observe in the ratees’ work life. Results showed that peers were the most accurate observers of leadership competencies in 360 degree assessments, compared to managers and subordinates. This corroborates our argument for an evidence-based instead of an
intuitive handling of 360 degree feedback results. Practical implications and avenues for future research are discussed.
This paper makes a contribution to the discussion on microfoundations of dynamic capabilities – actions and interactions in organizations that enable continuous organizational renewal. More specifically, we propose the idea that dynamic capabilities of an organization
are a positive function of corresponding dynamic capabilities of individual and collective actors in the organization. Further, we develop the assumption that not only individual acts of managers but also of individuals and teams without managerial responsibility relate to dynamic capabilities of the organization. Following a holistic view, we also take into consideration empowering working conditions as enhancing factor of this function. To
examine these roots of dynamic capabilities, we use a multi level model of competence provided by Wilkens, Keller and Schmette (2006) that operationalizes the concept of dynamic
capabilities provided by Teece (2007) on a concisely behavioural base. We investigated our hypotheses with a standardized questionnaire in a case study of a German plant engineering company with 112 participants and found first support for our assumptions. Our results show an impact of individual dynamic capabilities on dynamic capabilities of the organization which is mediated by team dynamic capabilities. Psychological and social-structural empowerment moderated this relationship. A case-specific interpretation and implications for future research and practice are discussed.