Immediately after President Trump's inauguration, U.S. federal science agencies began deleting information about climate change from their websites, triggering alarm among scientists, environmental activists, and journalists about the administration's attempt to suppress information about climate change and promulgate climate denialism. The Environmental Data & Governance Initiative (EDGI) was founded in late 2016 to build a multidisciplinary collaboration of scholars and volunteers who could monitor the Trump administration's dismantling of environmental regulations and science deemed harmful to its industrial and ideological interests. One of EDGI's main initiatives has been training activists and volunteers to monitor federal agency websites to identify how the climate-denialist ideology is affecting public debate and science policy. In this paper, we explain how EDGI's web-monitoring protocols are being incorporated into college curricula. Students are trained how to use the open-source online platforms that EDGI has created, but are also trained in how to analyze changes, determine whether they are significant, and contextualize them for a public audience. In this way, EDGI's work grows out of STS work on "critical making" and "making and doing." We propose that web-monitoring exemplifies an STS approach to responsive and responsible knowledge production that demands a more transparent and trustworthy relationship between the state and the public. EDGI's work shows how STS scholars can establish new modes of engagement with the state, and create spaces where the public can not only define and demand responsible knowledge practices, but also participate in the process of creating STS inspired forms of careful, collective and public knowledge construction.
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http://dx.doi.org/10.17351/ests2020.313 | DOI Listing |
Biochem Genet
December 2024
Department of Obstetrics and Gynecology, Wuhan Third Hospital (Tongren Hospital of Wuhan University), No.216, Guanshan Avenue, Hongshan District, Wuhan, 430074, Hubei, China.
Cisplatin, a platinum-based chemotherapeutic agent, can be used to treat cervical cancer (CC), but cisplatin resistance is increased during the cisplatin treatment. Long non-coding RNA PGM5-AS1 reportedly participates in CC tumorigenesis; however, its role in CC patients with cisplatin resistance has not been revealed. The present aimed to examine the role of PGM5-AS1 in modulating cisplatin resistance in CC.
View Article and Find Full Text PDFSci Rep
December 2024
School of Marxism, China University of Political Science and Law (CUPL), Beijing, 100091, China.
To improve students' understanding of physical education teaching concepts and help teachers analyze students' cognitive patterns, the study proposes an association learning-based method for understanding physical education teaching concepts using deep learning algorithms, which extracts image features related to teaching concepts using convolutional neural networks. Moreover, a neurocognitive diagnostic model based on hypergraph convolution is constructed to mine the data of students' long-term learning sequences and identify students' cognitive outcomes. The findings revealed that the highest accuracy of the association graph convolutional neural network was 0.
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December 2024
Communication University of China, State Key Laboratory of Media Convergence and Communication, Beijing, 100024, China.
Knowledge distillation improves student model performance. However, using a larger teacher model does not necessarily result in better distillation gains due to significant architecture and output gaps with smaller student networks. To address this issue, we reconsider teacher outputs and find that categories with strong teacher confidence benefit distillation more, while those with weaker certainty contribute less.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
December 2024
Department of Public Health, School of Public Health & Safety, Shahid Beheshti University of Medical Sciences, P.O. Box, Tehran, 19835-35511, Iran.
Background: This study addresses the determination of educational intervention-based on the Theory of Planned Behavior (TPB)-effectiveness on continued breastfeeding among Iranian mothers attending health centers, considering low researchers' attention to the continued breastfeeding index despite its important impact on children's health.
Methods: The present study was conducted among 230 mothers with exclusively breastfed infant (115 in the intervention group and 115 in the control group). Sampling starts with randomly selecting 12 health centers among all health centers in Karaj, Alborz province, and allocating them randomly into two equal groups of intervention and control.
Neural Netw
December 2024
School of Computer Science, Wuhan University, Luojiashan Road, Wuchang District., Wuhan, 430072, Hubei Province, China; Hubei Key Laboratory of Digital Finance Innovation, Hubei University of Economics, No. 8, Yangqiaohu Avenue, Zanglong Island Development Zone, Jiangxia District, Wuhan, 2007, Hubei Province, China. Electronic address:
The remarkable success of Graph Neural Networks underscores their formidable capacity to assimilate multimodal inputs, markedly enhancing performance across a broad spectrum of domains. In the context of molecular modeling, considerable efforts have been made to enrich molecular representations by integrating data from diverse aspects. Nevertheless, current methodologies frequently compartmentalize geometric and semantic components, resulting in a fragmented approach that impairs the holistic integration of molecular attributes.
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