Webster Vienna Private University

This paper argues that a focus on recognition helps in analysing a series of underlying- and salient- yet often under-studied aspects in the process of European integration. The first section revisits the debates in IR literature on recognition and introduces a complementary analytical framework developed around a functionalist typology of recognition in IR. This builds, first, on three models of recognition, that is, a struggle for ethical community (Hegel); a struggle for justice (Honneth) and a struggle for identity (Ringmar). Second, it involves three structuring mechanisms, that is, institutional biases; stigmatisation; and pecking orders (status hierarchies). The third section applies this framework and focuses on the dynamics of recognition struggles revolving around the notions of ethical community, justice and identity in the EU. The analysis operates on two levels: first, on the level of individual member states, it offers an illustrative case study of relations between Viktor Orbán’s government in Hungary and the EU’s institutions and governments of fellow member states. Second, on the polity-level, it assesses a number of recent crises in the EU in the last two decades and the shifting patterns of in-group/out-group recognition dynamics in the EU.

Abstract Regional disparities in mitigation capacity and the slow deployment of certain novel technologies pose significant challenges to achieving ambitious climate goals. We explore how accounting for technological and mitigation capacity considerations alters the regional distribution of mitigation efforts, and how these shifts relate to fairness considerations, all while staying within the scenario space aligned with the Paris Agreement’s goal of holding the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels. To do so, we use a new set of scenarios generated using eight global integrated assessment models (IAMs). These scenarios shift near-term mitigation efforts to regions with greater mitigation capacity by implementing differentiated carbon pricing and emission caps, deviating from the default assumption of a uniform carbon price in global IAMs. We examine the scale of regional emissions reductions and energy system transformations needed, highlighting the implications in the near term. Our findings from the most ambitious scenario, highlight that Organisation for Economic Co-operation and Development (OECD) countries could reduce total CO 2 emissions as reported in the models by approximately 85% (range: 81%–114%) by 2040 relative to 2020 levels and achieve net-zero CO 2 emissions around 2045—well beyond the 58% reduction (range: 33%–71%) projected under default 2 °C pathways with a globally uniform carbon price. Similarly, China could reduce CO 2 emissions by 78% (range: 55%–83%) by 2040 and reach net-zero by 2050, compared to a 50% reduction (range: 47%–72%) in default scenarios. In this ambitious scenario, other regions could aim to reach net-zero CO 2 by 2070. This redistribution of mitigation efforts involves an accelerated phase-out of fossil fuels—coal, oil, and gas—primarily within the OECD region and, to a certain extent, in China. It also includes an early—but, in line with our feasibility considerations, limited—scale-up of carbon capture and storage capacity, along with significant reductions in final energy demand that go beyond current pledges and ambition levels. Beyond feasibility considerations, the new scenarios assume more mitigation efforts in regions with higher mitigation capacity proxied through institutional capacity, consistent with a capacity-based conception of regional fairness. Integrating certain considerations of feasibility and fairness into scenario assessments enables the development of alternative pathways that are, in some respects, more policy-relevant and help expand the scenario space—thereby responding to some of the recent critiques of global IAMs.

The role of facial feedback in facial emotion recognition remains controversial, partly due to limitations of the existing methods to manipulate the activation of facial muscles, such as voluntary posing of facial expressions or holding a pen in the mouth. These procedures are indeed limited in their control over which muscles are (de)activated when and to what degree. To overcome these limitations and investigate in a more controlled way if facial emotion recognition is modulated by one’s facial muscle activity, we used computer-controlled facial neuromuscular electrical stimulation (fNMES). In a pre-registered EEG experiment, ambiguous facial expressions were categorised as happy or sad by 47 participants. In half of the trials, weak smiling was induced through fNMES delivered to the bilateral Zygomaticus Major muscle for 500 ms. The likelihood of categorising ambiguous facial expressions as happy was significantly increased with fNMES, as shown with frequentist and Bayesian linear mixed models. Further, fNMES resulted in a reduction of P1, N170 and LPP amplitudes. These findings suggest that fNMES-induced facial feedback can bias facial emotion recognition and modulate the neural correlates of face processing. We conclude that fNMES has potential as a tool for studying the effects of facial feedback.

ABSTRACT Does growing reliance on private military and security companies (PMSCs) lead to the re-configuration of the state as a security and defence actor in Europe? Building on the multiple-networks-approach in organisation theory (Padgett and Powell), the current paper develops an analytical approach for studying the rise of new organizational forms in interstitial spaces via mechanisms including extension and differentiation; fusion and hybridity; transposition and refunctionality; and multivocality. The empirical analysis focuses on the rules and practices of Vesper Group - a PMSC working closely with the Swedish government. Several findings are reported. First, a new organizational form seems to be emerging as a result of the ongoing multiple network dynamics – national defence entrepreneurial firm. This is a type of a firm different from mainstream PMSCs in that it is owned by venture capital companies from their home state and also in that it is closely associated with its respective state in terms of its personnel policies, expertise and operational goals and scope. Second, the case of Sweden’s Vesper Group and its cooperation with the Swedish government indicates that some EU member states may also be in the process of structural and institutional mutation as providers of defence and crisis management capabilities.

Abstract Cell-free (CF) synthesis with highly productive E. coli lysates is a convenient method to produce labeled proteins for NMR studies. Despite reduced metabolic activity in CF lysates, a certain scrambling of supplied isotope labels is still notable. Most problematic are conversions of 15N labels of the amino acids L-Asp, LAsn, L-Gln, L-Glu and L-Ala, resulting into ambiguous NMR signals as well as into label dilution. Specific inhibitor cocktails could suppress most undesired conversion reactions, while limited availability and potential side effects on CF system productivity need to be considered. As alternative route to address NMR label conversion in CF systems, we describe the generation of optimized E. coli lysates with reduced amino acid scrambling activity. Our strategy is based on the proteome blueprint of standardized CF S30 lysates of the E. coli strain A19. Identified lysate enzymes with suspected amino acid scrambling activity were eliminated by constructing corresponding single and cumulative chromosomal mutations in A19. CF lysates prepared from the mutants were analyzed for their CF protein synthesis efficiency and for residual scrambling activity. The A19 derivative “Stablelabel” containing the cumulative mutations asnA, ansA/B, glnA, aspC and ilvE was finally identified as giving the most useful CF S30 lysates. We demonstrate the optimized NMR spectral complexity of selectively labeled proteins CF synthesized in “Stablelabel” lysates. By taking advantage of the ilvE deletion in "Stablelabel", we further exemplify a new strategy for methyl group specific labeling of membrane proteins with the proton pump proteorhodopsin.