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The usefulness of ‘realism’ in explaining Russia’s decision to invade Ukraine has become a keenly contested debate not only in International Relations but in wider public intellectual discourse since the onset of the war in February 2022. At the centre of this debate is the punditry of John J. Mearsheimer, a prominent offensive realist who is a Professor of International Relations at the University of Chicago. This article argues that although Mearsheimer is indeed a realist, his offensive realism is but one of many different realist theories that can forward an explanation of the Ukraine War. Beyond the apparent hegemony of structural realism (the branch of realism to which Mearsheimer’s offensive realism belongs), it is argued that classical and neoclassical realist frameworks can provide more nuanced and, ultimately, convincing arguments as to why Russian President Vladimir Putin decided to invade Ukraine. This is because both classical and neoclassical realism can incorporate insights from non-realist studies—such as the concepts of civilization and ontological security—and combine them into an overarching power politics framework. Although neither classical nor neoclassical realism is flawless in their explanations, they demonstrate that realism does not just have to be about international power structures but can offer multivariate accounts of why a state, like Russia, decided to act, such as invading Ukraine.

In-game advertisements have become a significant source of revenue for developers of freemium mobile games. Despite this, we are not aware of any published exploratory study looking into the effect of these advertisements on individual, user-level behavior. We consult existing literature on the psychology of advertising and interruption, and propose several metrics that could be used to measure user-level retention. Using a unique dataset representing 21 free-to-play mobile games, we create a simple model which attempts to determine the effect of advertisements on retention. We find only a weak relationship between advertisements and retention. More importantly we find that game-specific effects dominate all advertising effects, yielding important results for game development and design decisions. While the results presented have limitations, they provide a starting point for future research on individual level analysis.

The accession of the remaining six Western Balkan states into the EU is shrouded in much uncertainty. Despite Croatia finally traversing the difficult path to eventual membership in 2013, not one of the remaining Western Balkan countries can claim to be on a definite pathway to membership today. An increasingly prevalent argument is that the EU's engagement with its neighbourhoods has faltered because its strategies have been undermined by an inherent stability-democracy dilemma. This article examines the EU's engagement with the Western Balkans and finds that although the EU tried to transcend this dilemma, in reality, a tension between stability and democracy was present with the former generally receiving more attention in policymaking. This led to not only a lack of tangible democratization amongst the Western Balkan states, but further uncertainty about their accession prospects. By 2018, it was clear that the EU's engagement with the Western Balkans needed a rethink, resulting in a new approach: the 'Six Flagship Initiatives'. However, given the apprehensiveness of some member states (especially France) coupled with the presence of outsiders such as Russia and China in the area, the accession prospects of the six non-EU Western Balkan states remains blurred.

The aim of this multicenter retrospective study is to characterize the histopathologic features of initial/early biopsies of proliferative leukoplakia (PL; also known as proliferative verrucous leukoplakia), and to analyze the correlation between histopathologic features and malignant transformation (MT). Patients with a clinical diagnosis of PL who have at least one biopsy and one follow-up visit were included in this study. Initial/early biopsy specimens were reviewed. The biopsies were evaluated for the presence of squamous cell carcinoma (SCCa), oral epithelial dysplasia (OED), and atypical verrucous hyperplasia (AVH). Cases that lacked unequivocal features of dysplasia were termed "hyperkeratosis/parakeratosis not reactive (HkNR)". Pearson chi-square test and Wilcoxon test were used for statistical analysis. There were 86 early/initial biopsies from 59 patients; 74.6% were females. Most of the cases had a smooth/homogenous (34.8%) or fissured appearance (32.6%), and only 13.0% had a verrucous appearance. The most common biopsy site was the gingiva/alveolar mucosa (40.8%) and buccal mucosa (25.0%). The most common histologic diagnosis was OED (53.5%) followed by HkNR (31.4%). Of note, two-thirds of HkNR cases showed only hyperkeratosis and epithelial atrophy. A lymphocytic band was seen in 34.8% of OED cases and 29.6% of HkNR cases, mostly associated with epithelial atrophy. Twenty-eight patients (47.5%) developed carcinoma and 28.9% of early/initial biopsy sites underwent MT. The mortality rate was 11.9%. Our findings show that one-third of cases of PL do not show OED with most exhibiting hyperkeratosis and epithelial atrophy, but MT nevertheless occurred at such sites in 3.7% of cases.

Researchers using Electroencephalograms ("EEGs") to diagnose clinical outcomes often run into computational complexity problems. In particular, extracting complex, sometimes nonlinear, features from a large number of time-series often require large amounts of processing time. In this paper we describe a distributed system that leverages modern cloud-based technologies and tools and demonstrate that it can effectively, and efficiently, undertake clinical research. Specifically we compare three types of clusters, showing their relative costs (in both time and money) to develop a distributed machine learning pipeline for predicting gestation time based on features extracted from these EEGs.

New results from MAST are presented that focus on validating models in order to extrapolate to future devices. Measurements during start-up experiments have shown how the bulk ion temperature rise scales with the square of the reconnecting field. During the current ramp-up, models are not able to correctly predict the current diffusion. Experiments have been performed looking at edge and core turbulence. At the edge, detailed studies have revealed how filament characteristics are responsible for determining the near and far scrape off layer density profiles. In the core the intrinsic rotation and electron scale turbulence have been measured. The role that the fast ion gradient has on redistributing fast ions through fishbone modes has led to a redesign of the neutral beam injector on MAST Upgrade. In H-mode the turbulence at the pedestal top has been shown to be consistent with being due to electron temperature gradient modes. A reconnection process appears to occur during edge localized modes (ELMs) and the number of filaments released determines the power profile at the divertor. Resonant magnetic perturbations can mitigate ELMs provided the edge peeling response is maximised and the core kink response minimised. The mitigation of intrinsic error fields with toroidal mode number n > 1 has been shown to be important for plasma performance.

Cultural competency continues to gain increased attention in medicine. Not only does it play a significant role in the delivery of health care and patient outcomes, but it also remains a major determinant of patient satisfaction. This study investigated how patients in an urban dermatology clinic rated their satisfaction with cultural competency. Compared to White patients, satisfaction scores were greater for Hispanic or Latino patients and less for Asian patients, while there was no significant difference for Black or African American patients. There were clear differences in patient satisfaction rates of various dimensions of cultural competency. A follow-up study with a larger sample size is needed for closer examination into the conclusions.

The EU’s foreign policy response(s) to the unfolding Ukraine crisis has further illustrated its difficulty in making effective foreign policy decisions. Using a neoclassical realist analytical framework, this paper argues that although the EU did have tangible collective interests in pursuing its Ukraine foreign policy, it was unable to adequately filter these through its domestic setting. Three key constraints to the EU’s Ukrainian foreign policy> were identified: decision-makers ’ miscalculations; rigid normative demands; and a reliance on consensus politics. Ultimately, the Ukraine crisis illustrated that the EU, in current incarnation, cannot translate interests into effective foreign policies, even when making policy for their direct neighbourhood.

This paper complements the ongoing empirical discussion surrounding participative budgeting by comparing its economic merits relative to a top-down budgeting alternative. In both budgeting regimes, private information is communicated vertically between a principal and a manager. We show that top-down budgeting incurs fewer agency costs than bottom-up budgeting whenever the level of information asymmetry is relatively low. Although the choice between top-down and bottom-up budgeting ultimately determines who receives private information within the firm, we find that both the principal and manager's preferences over the allocation of private information remain qualitatively similar across the two budgeting paradigms. Specifically, while the principal always prefers either minimal or maximal private information, the manager prefers an interim or maximal level of private information regardless of who is privately informed. Last, we use our model to address empirical inconsistencies relating the firm's choice of budgeting process, the resulting budgetary slack, and performance.

Background: Malignant disease metastasising to the cranial dura is rare. Dural metastases manifesting as a subdural fluid collection and presenting as a chronic subdural hematoma is an uncommon entity with unknown pathophysiology. Case Description: We present a patient with known prostate cancer metastasising to the cranial dura masquerading as a chronic subdural hematoma. The patient presented with bilateral subdural collections manifesting with confusion and dysphasia. Initial drainage of the larger, symptomatic left side improved only temporarily patient's symptoms. A second drainage of the collection was performed on the same side 5 days later and dural biopsies taken during the same procedure revealed prostate metastases. The patient improved slowly and was discharged to a hospice for palliative care management. Conclusions: Prostate dural metastases should be suspected in patients with known prostate cancer presenting with a subdural collection in the absence of cranial trauma. If decision to drain the subdural collection is taken, then biopsies can be taken the same time as they can pose a diagnostic challenge.

Machine learning is a promising tool to reconstruct time-series phenomena, such as variability of active galactic nuclei (AGNs), from sparsely sampled data. Here, we use three Continuous Autoregressive Moving Average (CARMA) representations of AGN variability – the Damped Random Walk (DRW) and (over/under)Damped Harmonic Oscillator – to simulate 10-yr AGN light curves as they would appear in the upcoming Vera Rubin Observatory Legacy Survey of Space and Time (LSST), and provide a public tool to generate these for any survey cadence. We investigate the impact on AGN science of five proposed cadence strategies for LSST’s primary Wide-Fast-Deep (WFD) survey. We apply for the first time in astronomy a novel Stochastic Recurrent Neural Network (SRNN) algorithm to reconstruct input light curves from the simulated LSST data, and provide a metric to evaluate how well SRNN can help recover the underlying CARMA parameters. We find that the light-curve reconstruction is most sensitive to the duration of gaps between observing season, and that of the proposed cadences, those that change the balance between filters, or avoid having long gaps in the g band perform better. Overall, SRNN is a promising means to reconstruct densely sampled AGN light curves and recover the long-term structure function of the DRW process (SF∞) reasonably well. However, we find that for all cadences, CARMA/SRNN models struggle to recover the decorrelation time-scale (τ) due to the long gaps in survey observations. This may indicate a major limitation in using LSST WFD data for AGN variability science.

Hedging has become the strategic strategy de jure, particularly for smaller powers1 that find themselves in increasingly volatile regional settings. Both in practice and in literature, hedging has become somewhat mythologized as an ideal foreign policy for smaller powers; a strategy which avoids the costs of either balancing or bandwagoning. This paper argues that while hedging can indeed be a smart strategy for smaller powers to engineer more optimal outcomes, it is not only not a costless strategy but also a strategy which can be extremely difficult to effectively undertake. To shed light on the inherent limitations of smaller powers engaging in a hedge, this paper borrows from neoclassical realism. Neoclassical realism is a useful starting point here because it assumes that ideal foreign policy-making is impossible. In addition, in the context of smaller power hedging in the contemporary international setting, neoclassical realism’s understanding of systemic stimuli (aided by the literature on regional security complexes) and the domestic impact of strategic culture and leader images enables it to be a good analytical tool for gauging the likely challenges of attempting to hedge. Two historical examples, one of an ostensibly successful hedge (Tito’s non- alignment during the Cold War) and one of an ostensibly unsuccessful hedge (Yakub Beg’s failure to hedge the British and Russian Empires), are used to demonstrate how successful hedging requires adept understanding of the structural environment as well as a keen use of statecraft.

Work towards the development of a new computer-assisted methodology for psychological study and intervention is described. This is referred to as the Personal Knowledge Methodology since it focuses on the elicitation and presentation of personal knowledge. Personal knowledge includes the knowledge individuals have of their life history, their behaviours, their moods, their relationships, their ambitions, and so on. Principles and techniques used in Knowledge Engineering form the basis of the design of the Personal Knowledge Methodology. At the heart of the methodology is the use of a suite of knowledge acquisition and modelling techniques. These are referred to as Personal Knowledge Techniques. Based on a review of a wide-range of literature, eight techniques were selected to be assessed for their possible use as Personal Knowledge Techniques. These included interview-based techniques, repertory grid techniques and diagram-based techniques. Two in-depth studies took place involving 18 participants and a total of 100 knowledge acquisition sessions. The results revealed that each of the eight techniques showed promise at efficiently capturing and structuring aspects of an individual’s personal knowledge. In addition, the techniques showed potential for providing help in allowing reflection and revealing insights. In particular, a technique based on the construction and use of a state transition network was found to be the most highly rated by the participants. A content analysis of the knowledge acquired formed the basis of an ontology of personal knowledge that would underpin many uses of the Personal Knowledge Methodology. The empirical work and analysis led to a number of ideas for future developments of the methodology and uses for the Personal Knowledge Techniques.

This paper investigates the effect of the plasma background, including neutrals in a self-consistent way, on filaments in the scrape-off layer (SOL) of fusion devices. A strong dependency of filament motion on background density and temperature is observed. The radial filament motion shows an increase in velocity with decreasing background density and increasing background temperature. In the simulations presented here, three neutral-filament interaction models have been compared, one with a static neutral background, one with no interaction between filaments and neutrals, and one co-evolving the neutrals self consistently with the filaments. With the background conditions employed here, which do not show detachment, there are no significant effects of neutrals on filaments, as by the time the filament reaches maximum velocity, the neutral density has not changed significantly.