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Gender and Politics in the EU
No full textThe European Union (EU) frequently presents itself as a champion of gender equality and women's rights. While this narrative is contested and has been subject to critique, the EU has instituted an equality framework that is more gender-aware than the individual member states. In this chapter, we consider a cross-section of gender equality measures and ask how these have to come to be included on the EU's agenda, which actors have contributed to the inclusion of equality in the EU's legal framework, and which ones responsible for helping to keep equality on the agenda of the EU institutions, even as anti-gender initiatives rise in individual member states
Hyginus:Fabulae (or Genealogiae)
No full textThe chapter succinctly presents the results of a new survey on the transmission of Hyginus' Myths (the original title of which was "Fabulae" or "Genealogiae")
Curve equations from expansions of 1-forms at a nonrational point
Full text linkWe exhibit an algorithm to compute equations of an algebraic curve over a computable characteristic 0 field from the power series expansions of its regular 1-forms at a nonrational point of the curve, extending a 2005 algorithm of Baker, Gonz\'alez-Jim\'enez, Gonz\'alez, and Poonen for expansions at a rational point. If the curve is hyperelliptic, the equations present it as an explicit double cover of a smooth plane conic, or as a double cover of the projective line when possible. If the curve is nonhyperelliptic, the equations cut out the canonical model. The algorithm has been used to compute equations over for many hyperelliptic modular curves without a rational cusp in the L-functions and Modular Forms Database
Reevaluating Meta-Learning Optimization Algorithms Through Contextual Self-Modulation
No full textContextual Self-Modulation (CSM) (Nzoyem et al., 2025) is a potent regularization mechanism for Neural Context Flows (NCFs) which demonstrates powerful meta-learning on physical systems. However, CSM has limitations in its applicability across different modalities and in high-data regimes. In this work, we introduce two extensions: iCSM which expands CSM to infinite-dimensional variations by embedding the contexts into a function space, and StochasticNCF which improves scalability by providing a low-cost approximation of meta-gradient updates through a sampled set of nearest environments. These extensions are demonstrated through comprehensive experimentation on a range of tasks, including dynamical systems, computer vision challenges, and curve fitting problems. Additionally, we incorporate higher-order Taylor expansions via Taylor-Mode automatic differentiation, revealing that higher-order approximations do not necessarily enhance generalization. Finally, we demonstrate how CSM can be integrated into other meta-learning frameworks with FlashCAVIA, a computationally efficient extension of the CAVIA meta-learning framework (Zintgraf et al., 2019). Together, these contributions highlight the significant benefits of CSM and indicate that its strengths in meta-learning and out-of-distribution tasks are particularly well-suited to physical systems. Our open-source library, designed for modular integration of self-modulation into contextual meta-learning workflows, is available at https://github.com/ddrous/self-mod
The multispecies hospital:How the past can inform the future
No full textWhen many, including the World Health Organisation (2025), have argued that we are facing a biodiversity crisis alongside the climate crisis that has huge implications for our health we need radical solutions and ideas to face this uncertain future. In the UK the NHS offers a unique opportunity to lead on creative nature recovery solutions given the sheer size of its estate; according to recent blog for NHS England (Corben, 2024), the current estate in total spans 25 million m2 or over 3500 football pitches. Although there are many limitations and challenges with the current estate, as historians we argue that we could look to the past to help find ambitious responses to the challenges facing us. Here we will focus on hospital estates (broadly conceived to include sanatoria and other residential institutions), which historically have facilitated a much closer relationship with nature to help find a path to the future
Deviation Dynamics in Cardinal Hedonic Games
No full textComputing stable partitions in hedonic games is a challenging task because there exist games in which stable outcomes do not exist. Even more, these No-instances can often be leveraged to prove computational hardness results. We make this impression rigorous in a dynamic model of cardinal hedonic games by providing meta theorems. These imply hardness of deciding about the possible or necessary convergence of deviation dynamics based on the mere existence of No-instances. Our results hold for additively separable, fractional, and modified fractional hedonic games (ASHGs, FHGs, and MFHGs). Moreover, they encompass essentially all reasonable stability notions based on single-agent deviations. In addition, we propose dynamics as a method to find individually rational and contractually individual stable (CIS) partitions in ASHGs. In particular, we find that CIS dynamics from the singleton partition possibly converge after a linear number of deviations but may require an exponential number of deviations in the worst case
Synthesis Theorisation
No full textFinding a space for reproductive rights within constitutions that are silent on them has been a perennial challenge. Most common responses fall into one of three categories. First, reading them into the right to privacy (or liberty). Second, and more recently, eschewing privacy and turning to the right to equality. And third, and most comprehensively, adding or combining privacy and equality. I argue that while rights addition avoids the need to choose between privacy and equality in framing reproductive rights, it falls short of capturing the intertwined lived reality of rights infringement. I source from within Indian constitutional law a fourth alternative: a method of rights analysis that responds to this reality, called rights synthesis. The synthesis however remains underdeveloped and underused within Indian constitutional doctrine. To theorise it, I turn to international human rights law (‘IHRL’). Drawing upon the overall framing of mutually supporting relationships between rights within IHRL but distinguishing the synthesis from existing categories of such relationships, I define the synthesis as involving permeability, interaction and dynamism. I distill the contributions of the synthesis within the experiential, conceptual and adjudicative registers to conclude that the synthesis enhances the protection of constitutional reproductive rights while offering insights for broader human rights analysis, in India and beyond
Pre-Injury, injury and post-injury factors leading to death in children and young people who were victims of knife crime in England between 2019-2024:a review of the National Child Mortality Database
No full textBackground:Knife-related deaths in children present a serious public health challenge. This study reports the demographics and pre-injury, injury and post-injury factors associated with death in children and young people (CYP), under the age 18 years, who died of knife wounds in England between 2019-2024.Methods:A retrospective cohort review of the English National Child Mortality Database between April 2019 and March 2024. Rates of death were corrected for population size using the 2021 census. Pre-injury, injury and post-injury factors associated with death are reported descriptively. Results:145 CYP died of knife wounds. The mean age was 14.4 years (SD 4.2) and 90.3% (n=131) were male. The rates of death per 100,000 CYP, per year were highest in children of ‘Black/Black British’ ethnicity (1.40 (95% CI 1.03-1.86)), with an Incidence Rate Ratio of 13.29 (95% CI 8.23-20.00), compared to CYP of ‘White’ ethnicity. Of the 57 cases available for detailed analysis, injuries to the chest and neck were responsible for the fatal injuries in 75.9% of cases (n=44) and 60.3% (n=35) died before reaching hospital. A thoracotomy was performed in 56.9% (n=33) of cases. Prior to death, 75.4% (n=43) had been known to social-services and 57.9% (n=33) had experienced Domestic Violence and Abuse. Neurodiversity or mental health concerns were reported in 50.9% (n=29) of CYP.Conclusions:Death of CYP secondary to knife wounds occurred in all regions of England. Many children are exposed to adverse childhood experiences before death and known to statutory services. The identification of interventions to decrease the risk to children from knife violence remains a priority
Impact of RIS Inter-Element Spacing on Array Gain and Energy Efficiency
No full textReconfigurable Intelligent Surfaces (RIS) have emerged as a promising technology for enabling seamless wire-less connectivity, particularly in environments characterized by non-line-of-sight (NLoS) propagation and signal blockages. To enhance performance in such scenarios, densely deployed RIS configurations is a promising solution. In this context, this paper investigates the impact of inter-element spacing on the gain and the energy efficiency (EE) of RIS-assisted communication system. Unlike previous works, we formulate the received signal model that incorporates the array directivity and show how the array gain varies with the change in the inter-element spacing. The performance of the standard (where the spacing is half of the wavelength) and dense RIS (where the spacing is less than half of the wavelength) configurations is compared in terms of, 1)beam pattern and array gain while considering quantized and unquantized phase shifts, 2) variation in the number of RIS elements, and 3) the trade-off between EE and array gain. Results reveal that while dense RIS offers slightly improved array gain compared to standard RIS, it incurs higher power consumption and reduced EE
Open-Source Data for Multi-Domain Network Monitoring and Sensing in Optical and Wireless Networks
No full textWe propose a cross-domain telemetry architecture for optical and wireless networks, and collect multi-source datasets, supporting AI engines and network DTs. The released datasets provide insights for QoT estimation, fibre sensing and multi-domain network optimisation