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Only a few studies on the nocturnal behavior of African ungulates exist so far, with mostly small sample sizes. For a comprehensive understanding of nocturnal behavior, the data basis needs to be expanded. Results obtained by observing zoo animals can provide clues for the study of wild animals and furthermore contribute to a better understanding of animal welfare and better husbandry conditions in zoos. The current contribution reduces the lack of data in two ways. First, we present a stand-alone open-source software package based on deep learning techniques, named Behavioral Observations by Videos and Images using Deep-Learning Software (BOVIDS). It can be used to identify ungulates in their enclosure and to determine the three behavioral poses “Standing,” “Lying—head up,” and “Lying—head down” on 11,411 h of video material with an accuracy of 99.4%. Second, BOVIDS is used to conduct a case study on 25 common elands (Tragelaphus oryx) out of 5 EAZA zoos with a total of 822 nights, yielding the first detailed description of the nightly behavior of common elands. Our results indicate that age and sex are influencing factors on the nocturnal activity budget, the length of behavioral phases as well as the number of phases per behavioral state during the night while the keeping zoo has no significant influence. It is found that males spend more time in REM sleep posture than females while young animals spend more time in this position than adult ones. Finally, the results suggest a rhythm between the Standing and Lying phases among common elands that opens future research directions.
Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS) discipline with its close connections to Computer Science seems to be conservative when conducting empirical research endeavors. To assess the magnitude of the problem and to understand its causes, we conducted a bibliographic review on publications in high-level IS journals. We reviewed 1,838 articles that matched corresponding keyword-queries in journals from the AIS senior scholar basket, Electronic Markets and Decision Support Systems (Ranked B). In addition, we conducted a survey among IS researchers (N = 110). Based on the findings from our sample we evaluate different potential causes that could explain why ML methods are rather underrepresented in top-tier journals and discuss how the IS discipline could successfully incorporate ML methods in research undertakings.
OPEN SCIENCE, VERSION 3.0: Breaking down barriers for equitable and efficient research communication
(2022)
Why do we need to communicate science? Is science, with its highly specialised language and its arcane methods, too distant to be understood by the public? Is it really possible for citizens to participate meaningfully in scientific research projects and debate? Should scientists be mandated to engage with the public to facilitate better understanding of science? How can they best communicate their special knowledge to be intelligible? These and a plethora of related questions are being raised by researchers and politicians alike as they have become convinced that science and society need to draw nearer to one another. Once the persuasion took hold that science should open up to the public and these questions were raised, it became clear that coming up with satisfactory answers would be a complex challenge. The inaccessibility of scientific language and methods, due to ever increasing specialisation, is at the base of its very success. Thus, translating specialised knowledge to become understandable, interesting and relevant to various publics creates particular perils. This is exacerbated by the ongoing disruption of the public discourse through the digitisation of communication platforms. For example, the availability of medical knowledge on the internet and the immense opportunities to inform oneself about health risks via social media are undermined by the manipulable nature of this technology that does not allow its users to distinguish between credible content and misinformation. In countries around the world, scientists, policy-makers and the public have high hopes for science communication: that it may elevate its populations educationally, that it may raise the level of sound decision-making for people in their daily lives, and that it may contribute to innovation and economic well-being. This collection of current reflections gives an insight into the issues that have to be addressed by research to reach these noble goals, for South Africa and by South Africans in particular.
Modern-day science is under great pressure. A potent mix of increasing expectations, limited resources, tensions between competition and cooperation, and the need for evidence-based funding is creating major change in how science is conducted and perceived. Amidst this 'perfect storm' is the allure of 'research excellence', a concept that drives decisions made by universities and funders, and defines scientists' research strategies and career trajectories. But what is 'excellent' science? And how to recognise it? After decades of inquiry and debate there is still no satisfactory answer. Are we asking the wrong question? Is reality more complex, and 'excellence in science' more elusive, than many are willing to admit? And how should excellence be defined in different parts of the world, particularly in lower-income countries of the 'Global South' where science is expected to contribute to pressing development issues, despite often scarce resources? Many wonder whether the Global South is importing, with or without consenting, the flawed tools for research evaluation from North America and Europe that are not fit for purpose. This book takes a critical view of these issues, touching on conceptual issues and practical problems that inevitably emerge when 'excellence' is at the center of science systems. Emerging from the capacity-building work of the Science Granting Councils Initiative in sub-Saharan Africa, it speaks to scholars, as well as to managers and funders of research around the world. Confronting sticky problems and uncomfortable truths, the chapters contain insights and recommendations that point towards new solutions - both for the Global South and the Global North.
Biological ageing is a degenerative and irreversible process, ultimately leading to death of the organism. The process is complex and under the control of genetic, environmental and stochastic traits. Although many theories have been established during the last decades, none of these are able to fully describe the complex mechanisms, which lead to ageing. Generally, biological processes and environmental factors lead to molecular damage and an accumulation of impaired cellular components. In contrast, counteracting surveillance systems are effective, including repair, remodelling and degradation of damaged or impaired components, respectively. Nevertheless, at some point these systems are no longer effective, either because the increasing amount of molecular damages can not longer be removed efficiently or because the repairing and removing mechanisms themselves become affected by impairing effects. The organism finally declines and dies. To investigate and to understand these counteracting mechanisms and the complex interplay of decline and maintenance, holistic and systems biological investigations are required. Hence, the processes which lead to ageing in the fungal model organism Podospora anserina, had been analysed using different advanced bioinformatics methods. In contrast to many other ageing models, P. anserina exhibits a short lifespan, a less biochemical complexity and it provides a good accessibility for genetic manipulations.
To achieve a general overview on the different biochemical processes, which are affected during ageing in P. anserina, an initial comprehensive investigation was applied, which aimed to reveal genes significantly regulated and expressed in an age-dependent manner. This investigation was based on an age-dependent transcriptome analysis. Sophisticated and comprehensive analyses revealed different age-related pathways and indicated that especially autophagy may play a crucial role during ageing. For example, it was found that the expression of autophagy-associated genes increases in the course of ageing.
Subsequently, to investigate and to characterise the autophagy pathway, its associated single components and their interactions, Path2PPI, a new bioinformatics approach, was developed. Path2PPI enables the prediction of protein-protein interaction networks of particular pathways by means of a homology comparison approach and was applied to construct the protein-protein interaction network of autophagy in P. anserina.
The predicted network was extended by experimental data, comprising the transcriptome data as well as newly generated protein-protein interaction data achieved from a yeast two-hybrid analysis. Using different mathematical and statistical methods the topological properties of the constructed network had been compared with those of randomly generated networks to approve its biological significance. In addition, based on this topological and functional analysis, the most important proteins were determined and functional modules were identified, which correspond to the different sub-pathways of autophagy. Due to the integrated transcriptome data the autophagy network could be linked to the ageing process. For example, different proteins had been identified, which genes are continuously up- or down-regulated during ageing and it was shown for the first time that autophagy-associated genes are significantly often co-expressed during ageing.
The presented biological network provides a systems biological view on autophagy and enables further studies, which aim to analyse the relationship of autophagy and ageing. Furthermore, it allows the investigation of potential methods for intervention into the ageing process and to extend the healthy lifespan of P. anserina as well as of other eukaryotic organisms, in particular humans.