Louis M. Shekhtman, Alexander J. Gates, Albert-László Barabási
While philanthropic support plays an increasing role in supporting research, there is limited quantitative knowledge about the patterns that characterize the distribution of philanthropic support. Here, we map philanthropic funding to universities and research institutions based on IRS tax forms from 685,397 non-profit organizations. We identify nearly one million grants supporting institutions involved in science, finding that in volume and scope, philanthropic funding is comparable to federal research funding. However, whereas federal funding relies on a few large organizations to distribute grants, the philanthropic ecosystem’s support is fragmented among a large number of funders with diverse focus that support research institutions at varying levels. Furthermore, we find that distinct from government support, philanthropic funders tend to focus locally, indicating that other criteria, beyond research excellence, play a role in their funding decisions. We also show evidence of persistence, i.e., once a grant-giving relationship begins, it tends to continue in time. Finally, we discuss the policy implications of our findings for philanthropic funders, individual researchers, the science of science, and for quantitative studies of philanthropy in general.
Read the full article at: arxiv.org
Silja Sormunen, Thilo Gross, Jari Saramäki
It has been postulated that the brain operates in a self-organized critical state that brings multiple benefits, such as optimal sensitivity to input. Thus far, self-organized criticality has typically been depicted as a one-dimensional process, where one parameter is tuned to a critical value. However, the number of adjustable parameters in the brain is vast, and hence critical states can be expected to occupy a high-dimensional manifold inside a high-dimensional parameter space. Here, we show that adaptation rules inspired by homeostatic plasticity drive a neuro-inspired network to drift on a critical manifold, where the system is poised between inactivity and persistent activity. During the drift, global network parameters continue to change while the system remains at criticality.
Read the full article at: arxiv.org
Sergey N. Dorogovtsev and José F. F. Mendes
Provides a systematic account of the statistical mechanics of complex networks
Covers recent trends, concepts, and theoretical techniques, and emphasises interdisciplinary strands
Broad appeal to researchers in complex systems including theoretical physicists and applied mathematicians as well as epidemiologists
Extensive bibliography and appendices offer excellent reference source for students and researchers
More at: global.oup.com
The global pandemic showed the critical importance of integrating fundamental , computational and clinical research to promote systemic understanding of a global threat to humankind. Global epidemiological assessments informing national and regional policy-making around the world were only made possible due to fundamental mechanistic knowledge of coronavirus biology dating back decades, large-scale data on human mobility patterns enabled by recent technologies, as well as massive onsite and dynamic clinical reporting from health institutions.
It is now clear that complex human diseases can only be tackled by transdisciplinary efforts that integrate fundamental, computational, and clinical research. This is not, however, an easily achievable feat, as fundamental laboratory discoveries are often not directly transferable into clinical settings, with controlled experiments not necessarily reflecting organismic and societal complexity. Only with synergy between fundamental researchers, clinicians, and data scientists can we hope to gain the depth of understanding required to address the physiological mechanisms behind some of the most challenging human diseases at the interface between hosts and pathogens.
The goal of the [3C] Cells, Computers & Clinics Symposium is to do exactly that, to bridge fundamental, computational, and clinical research in the scope of complex diseases, particularly those related to host-pathogen interactions.
More at: gulbenkian.pt
Hao Peng, Daniel M. Romero, and Emőke-Ágnes Horvát
PNAS June 14, 2022 119 (25) e2119086119
Scientific retraction has been on the rise recently. Retracted papers are frequently discussed online, enabling the broad dissemination of potentially flawed findings. Our analysis spans a nearly 10-y period and reveals that most papers exhaust their attention by the time they get retracted, meaning that retractions cannot curb the online spread of problematic papers. This is striking as we also find that retracted papers are pervasive across mediums, receiving more attention after publication than nonretracted papers even on curated platforms, such as news outlets and knowledge repositories. Interestingly, discussions on social media express more criticism toward subsequently retracted results and may thus contain early signals related to unreliable work.
Read the full article at: www.pnas.org