Norm Implementation: the Achilles’ Heel of Constructivist Theory?

This article offers a review of the IR academic literature on international norms, exploring their functions and life cycle, as well as revealing that while the stages leading to their national adoption have been thoroughly studied, the implementation phase has mostly been neglected by scholars. It also considers the power international norms have to bring about change in different spheres and why states adopt them. The national implementation of international norms and the reasons why some norms reach compliance while others do not have been to a large extent overlooked. The reasons for this are multifold: while some scholars assume mature, or salient, norms automatically reach compliance or rely on the explanatory power of value conflicts, others point to the influence of groups of innovative experts or international pressure in ensuring norm implementation. Those describing the local adaptation of international norms offer the most convincing descriptions of how states attempt to implement international norms they have adopted. A gap persists, however, in the literature, with scholars focusing on the domestic reasons that norms may not be successfully implemented and neglecting the international ones. This article points out a gap in the influential constructivist literature on norms, emphasizing that if international norms adopted by national governments do not reach compliance, then the study of adoption and diffusion mechanisms loses its relevance

MaGIC: a machine learning tool set and web application for monoallelic gene inference from chromatin

Background: A large fraction of human and mouse autosomal genes are subject to random monoallelic expression (MAE), an epigenetic mechanism characterized by allele-specific gene expression that varies between clonal cell lineages. MAE is highly cell-type specific and mapping it in a large number of cell and tissue types can provide insight into its biological function. Its detection, however, remains challenging. Results: We previously reported that a sequence-independent chromatin signature identifies, with high sensitivity and specificity, genes subject to MAE in multiple tissue types using readily available ChIP-seq data. Here we present an implementation of this method as a user-friendly, open-source software pipeline for monoallelic gene inference from chromatin (MaGIC). The source code for the MaGIC pipeline and the Shiny app is available at https://github.com/gimelbrantlab/magic Conclusion: The pipeline can be used by researchers to map monoallelic expression in a variety of cell types using existing models and to train new models with additional sets of chromatin marks.National Institutes of Health (U.S.) (award U54 HG007963

Implementation of International Norms in Russia: The Case of Higher Education

This article analyses the reasons why Russia adopts foreign norms in the sphere of higher education, looking at how isomorphism, Transnational Advocacy Networks and the global market for education have brought about the country’s integration in the global network of universities. It investigates how Russia strives to adopt international and western educational norms by adhering to the Bologna process and launching projects such as 5-100 to reinforce the competitiveness of its universities on the global stage, but remains concerned about security and national identity issues. These fears have resulted in the government prioritizing the adherence to formal criteria while preserving the historical content of its higher education, thus leading to a dichotomy between substance and structure. This mismatch between the organization of higher education and its content leads to an ineffective implementation of international norms but also to significant disruptions in the existing system. Attempts to levy the advantages of both systems have had opposite results. Indeed, the risks of sudden change are multifold: the sudden “catch-up” mode leads to resistance and to a decline in the overall quality of education in those universities lacking the institutions to support the fast tempo of change. The authors outline the benefits of an incremental adaptation to the international higher education system and the need to adjust international norms to local conditions, by building off the assets of the country’s Soviet heritage. The benefits of involving Transnational Experience and Experience Networks in the implementation of international norms are also reviewed

“That’ll Teach Them”: Investigating the Soft Power Conversion Model through the Case of Russian Higher Education

While the international environment remains characterized by the desire of states to strengthen their position, the literature has revealed a growing preference for soft power instruments over military intervention. Higher education has been repurposed as a tool to achieve foreign policy goals, with many states embracing the international norm on world-class universities in an attempt to improve their international competitiveness and their image abroad. This paper considers the soft power conversion model of higher education and attempts to determine its effectiveness through a case study devoted to Russian Higher Education. A survey of foreign students starting their studies and of another finishing their studies in three leading Russian universities reveals that receiving a higher education in Russia may contribute to aligning students’ positions with the Russian perspective on international issues diffused in these universities as was confirmed by surveying a control group of Russian students. These preliminary findings suggest that the benefits of internationalizing national higher education systems are not just reserved to the norm initiators (US, UK) but extend to second wave norm adopters (Russia, China)

Russian higher education under sanctions: a constructivist perspective

Constructivists have convincingly shown through norm theory and multiple case studies that ideas can be more influential than material conditions in determining political and social outcomes. This paper analyses the capacity of norms to resist shock events that bring about a radical change in material conditions and demonstrates that significant disruptions in the context of norm implementation can lead to normative U-turns. The authors theorise norm backtracking based on the case of the Russian higher education sector, revealing how the 2022 armed-conflict in Ukraine and Western sanctions have affected the implementation of the norm of world-class universities in Russia. The findings of the qualitative case study based on 24 expert interviews suggest that although internalised norms can survive shifts in material conditions, the need to readapt them to an evolving context and to new political goals results in their distortion. The international norm on world-class universities, implemented in Russia through Project 5-100 and the Priorities 2030 initiative, is facing exceptional challenges which have led so far not to the rejection of the norm but to its remodelling to meet new objectives. The impact of Russia’s normative “redesign” in the sphere of higher education also ushers in a new stage in the life of the international norm on world-class universities marked by a rejection of the Western-centric model

Transnational policy networks and change through internationalization (The Record of Project 5-100)

This article considers the ideational and political contexts in which Project 5-100, the Russian excellence in higher education initiative emerged, as well as the specificities of its organisational and behavioural model. While Project 5-100 has been studied in the academic literature as regards its efficiency and how it affected the performance and inner workings of the participating universities, the question of how the project came about and the characteristic traits of its internal set-up still remain largely overlooked. The study focuses on the involvement of local and international players, arguing that their successful and organic cooperation influenced both the architecture and the implementation of the project. This paper contributes to the literature on policy networks by showing that transnational actors do not necessarily undermine or challenge state power and can on the contrary help governments implement systemic change. Inspired by the international experience of establishing world-class universities, Project 5-100 was conceived and lobbied by a small but influential group of visionaries pushing for change who – acting in a concerted and purposive manner – acquired a novel and powerful capacity to use international expertise for the development of a key national project, capable of deeply transforming the country’s higher educational system

Chromatin Signature Identifies Monoallelic Gene Expression Across Mammalian Cell Types

Monoallelic expression of autosomal genes (MAE) is a widespread epigenetic phenomenon which is poorly understood, due in part to current limitations of genome-wide approaches for assessing it. Recently, we reported that a specific histone modification signature is strongly associated with MAE and demonstrated that it can serve as a proxy of MAE in human lymphoblastoid cells. Here, we use murine cells to establish that this chromatin signature is conserved between mouse and human and is associated with MAE in multiple cell types. Our analyses reveal extensive conservation in the identity of MAE genes between the two species. By analyzing MAE chromatin signature in a large number of cell and tissue types, we show that it remains consistent during terminal cell differentiation and is predominant among cell-type specific genes, suggesting a link between MAE and specification of cell identity

Deep Reinforcement Learning for Efficient Measurement of Quantum Devices

Deep reinforcement learning is an emerging machine learning approach which can teach a computer to learn from their actions and rewards similar to the way humans learn from experience. It offers many advantages in automating decision processes to navigate large parameter spaces. This paper proposes a novel approach to the efficient measurement of quantum devices based on deep reinforcement learning. We focus on double quantum dot devices, demonstrating the fully automatic identification of specific transport features called bias triangles. Measurements targeting these features are difficult to automate, since bias triangles are found in otherwise featureless regions of the parameter space. Our algorithm identifies bias triangles in a mean time of less than 30 minutes, and sometimes as little as 1 minute. This approach, based on dueling deep Q-networks, can be adapted to a broad range of devices and target transport features. This is a crucial demonstration of the utility of deep reinforcement learning for decision making in the measurement and operation of quantum devices

Sensitive radio-frequency read-out of quantum dots using an ultra-low-noise SQUID amplifier

Fault-tolerant spin-based quantum computers will require fast and accurate qubit readout. This can be achieved using radio-frequency reflectometry given sufficient sensitivity to the change in quantum capacitance associated with the qubit states. Here, we demonstrate a 23-fold improvement in capacitance sensitivity by supplementing a cryogenic semiconductor amplifier with a SQUID preamplifier. The SQUID amplifier operates at a frequency near 200 MHz and achieves a noise temperature below 600 mK when integrated into a reflectometry circuit, which is within a factor 120 of the quantum limit. It enables a record sensitivity to capacitance of 0.07 aF/ \sqrt{Hz}. The setup is used to acquire charge stability diagrams of a gate-defined double quantum dot in a short time with a signal-to-noise ration of about 38 in 1 μs of integration time

Quantum device fine-tuning using unsupervised embedding learning

Quantum devices with a large number of gate electrodes allow for precise control of device parameters. This capability is hard to fully exploit due to the complex dependence of these parameters on applied gate voltages. We experimentally demonstrate an algorithm capable of fine-tuning several device parameters at once. The algorithm acquires a measurement and assigns it a score using a variational auto-encoder. Gate voltage settings are set to optimise this score in real-time in an unsupervised fashion. We report fine-tuning times of a double quantum dot device within approximately 40 min