53417 research outputs found
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Top Management’s Financial Experience, Backgrounds in Regulatory and Non-Regulatory Financial Institutions, and Corporate Tax Aggressiveness
Full text linkPurpose: We investigate how top management team (TMT) members with experience in regulatory financial institutions (e.g., insurance companies, commercial and investment banks, fund management firms, securities depositories, futures and trust, and investment management entities) or non-regulatory financial institutions (e.g., stock exchanges, policy banks, and regulatory commissions) influence tax aggressiveness. We further examine how institutional investors and regulatory violation pressure moderate this relationship and explore the firm value implications of strategic tax planning led by financial executives. Findings: Firms led by top executives (e.g., CEOs) with financial expertise tend to exhibit lower effective tax rates (ETRs) and larger book–tax differences. Notably, executives with experience in non-regulatory financial institutions are more likely to pursue aggressive tax strategies, whereas those with backgrounds in regulatory institutions show no significant effect. Furthermore, we find that institutional investors amplify the tax aggressiveness of financially expert executives, and that these executives become more aggressive in tax avoidance following regulatory sanctions. Finally, these tax strategies are highly associated with higher future firm value when led by financially expert executives. Design/methodology/approach: We analyse 21,912 firm-year observations from 3,186 Chinese listed firms. Baseline OLS models include industry, year, and province fixed effects. Robustness and endogeneity are addressed using weighted least squares, propensity score matching, entropy balancing, dynamic system GMM, executive-turnover event analyses, Granger causality tests, instrumental-variable (2SLS) estimations, and firm fixed effects. Originality/value: We contribute new insights to the literature by examining how top executives with prior experience in both regulatory-oriented and non-regulatory financial institutions influence future tax planning and firm value, drawing on upper echelons and imprinting theories
Adapter-RL: Adaptation of Any Agent Using Reinforcement Learning
No full textThis study introduces Adapter-RL, a novel architecture aimed at improving the performance of existing agents in reinforcement learning tasks. The approach integrates human-knowledge-based systems with deep reinforcement learning, combining the interpretability and rule-based logic of the former with the adaptive learning capabilities of the latter. A crucial aspect of this method is the use of 'adapters' - concise modules integrated with a base-agent, designed to adjust the policy for specific tasks. The Adapter-RL framework comprises a base-agent responsible for initial decision-making and an adapter module that refines these decisions to meet task-specific requirements. The adapter facilitates efficient training, reduces parameter requirements, and mitigates catastrophic forgetting, enhancing overall performance and adaptability. This architecture enables agents to be fine-tuned effectively, allowing them to adapt to complex tasks with rapidly changing or uncertain conditions. The research demonstrates the efficacy of Adapter-RL through experiments in microRTS, a challenging real-time strategy game. The results demonstrate that Adapter-RL significantly accelerates the training process and outperforms base-agents across various tasks, highlighting its efficiency and robustness. In addition, the study investigates the temperature coefficient tradeoff in adapter training, finding that optimal performance is achievable within a broad range of coefficients. This underscores the stability of the method. The Adapter-RL method enables the specialization of base AI for specific characters or scenarios
Establishing a set of acceptable demographic questions for use in health research through public consultation.
Full text linkBACKGROUND: The importance of inclusivity in health care and health research is increasingly recognised in the UK. However, there are currently no UK standards for collecting self-reported demographic data from research participants. To address this gap, we undertook a public involvement activity. We worked with patient and public involvement partners and members of the public to establish an acceptable set of demographic questions for adult participants, taken from national survey questions to ensure comparable data. METHODS: Our project team, which included two patient and public involvement partners, selected demographic questions that covered characteristics protected by the UKs Equality Act 2010 or groups identified as potentially underserved in research. These questions covered health, disability, and unpaid care; education and employment; sexual orientation and gender identity; and ethnicity, language, and religion. We conducted four discussion groups to review the proposed questions with diverse members of the public. We explored their views on questions, the explanatory text for the purpose of data collection, data storage (i.e. pseudonymised or anonymous), the length of the question set and any missing topics. RESULTS: Twenty-nine public contributors took part. Of these, at least ten were from a minority ethnic background and eleven had one or more disabilities or long-term health conditions. Five contributors were people of faith, three were members of the LGBTQIA+ community, and seven had experience of providing unpaid care. Of the 18 questions, three were removed and ten were modified. This resulted in a revised question set of 15 items. CONCLUSIONS: The implementation of this question set will help to standardise data collection across studies, increasing comparability and researchers' ability to evaluate inclusivity. The demographic question set is now available to non-commercial researchers across the UK as part of a pilot study to evaluate and improve its utility and performance
An epigenomic investigation of atrial fibrillation in a matched left and right atrial human cohort
No full textKilling for control: How drug traffickers capture the state and expand their criminal economies
No full textThis chapter develops and tests a theory of criminal governance, examining how drug trafficking organizations (DTOs) use bribery and violence to dominate resource-rich regions and counter state interventions. The study draws on data on over 500 political assassinations and 156 lethal attacks on politicians’ relatives in Mexico since 2000. Using an instrumental variable approach, the causal effects of government actions on criminal strategies are identified. The findings reveal that DTOs use rent-seeking violence to influence the pool of political candidates in high-value areas. These are primarily oil pipelines, which are central to large-scale oil theft. Government crackdowns intensify political violence against incumbent mayors while paradoxically increasing voter turnout and the probability of the incumbent party’s re-election, reflecting public approval of anti-crime measures. Supporting the crime diversification hypothesis, DTOs adapt by expanding into high-profit crimes such as extortion and retail drug distribution. These shifts are geographically strategic, with oil pipelines becoming centres of criminal innovation. Meanwhile, crimes like car theft are suppressed in fuel-theft zones, which helps preserve gasoline demand. Instead, these crimes are displaced to international borders and selected urban centres. The findings reveal the full cycle of criminal governance, illustrating how organized crime reshapes governance, drives violence—including disappearances—and leaves civilians struggling with rising crime and co-opted governments
LLMs can read music, but struggle to hear it. An evaluation of core music perception tasks
Full text linkMultimodal Large Language Models (MLLMs) claim “musical understanding,” yet most evaluations conflate listening with score reading. We benchmark three SOTA LLMs (Gemini 2.5 Pro, Gemini 2.5 Flash, and Qwen2.5-Omni) across three core music skills: Syncopation Scoring (rhythm perception), Transposition Detection (melody perception), and Chord Quality Identification (harmony perception). Moreover, we separate three sources of variability: (i) perceptual limitations (by contrasting audio recordings vs. symbolic MIDI inputs), (ii) exposure to prior examples (zero- vs. few-shot manipulations), and (iii) reasoning strategies (Standalone, Chain of Thought, LogicLM). For the latter we adapt LogicLM, a framework combining LLMs with symbolic solvers to perform structured reasoning. In LogicLM, LLMs act as perceptual formulators, generating strict, machine-checkable schemas (onset grids, interval sequences) that deterministic solvers execute with self-refinement. Our results reveal a clear perceptual gap: models perform near ceiling on MIDI but show substantial accuracy drops on audio. Reasoning and few-shot prompting offer minimal gains. This is expected for MIDI, where performance reaches saturation, but more surprising for audio, where LogicLM, despite near-perfect MIDI accuracy, remains notably brittle. Among models, Gemini Pro achieves the highest performance across most conditions. Transposition yields the highest accuracies across models, while Chord Identification scores slightly below Syncopation. Overall, current systems reason well over symbols (MIDI) but do not yet “listen” reliably from audio, with reasoning strategies having little impact over accuracy. Our method and dataset make the perception–reasoning boundary explicit and offer actionable guidance for building robust, audio music systems
Witnessing health and place: Sebastião Salgado and the photographic legacy of polio eradication
No full textThe death of Brazilian photographer and photojournalist Sebastião Salgado in May 2025 invites renewed reflection on photography’s role in shaping global health narratives. Celebrated for his evocative black-and-white images that document human suffering and resilience, Salgado’s work has addressed international issues such as labour, migration, indigeneity, and environmental degradation. Among an extensive portfolio, his documentation of global polio eradication efforts stands out as a significant yet often overlooked contribution, providing vital insights into the spatial dynamics of a global health campaign. This paper situates Salgado’s polio photographs within the context of health geography and visual geography, arguing that these images function not only as humanitarian testimony but also as a visual cartography of care. By analysing the spatial, embodied, and ethical dimensions of this work, I examine how visual methodologies can enhance geographies of health, vulnerability, and intervention. Salgado’s archive of polio photographs constructs a powerful visual grammar of place-based inequality and collective resilience, while also raising questions about power dynamics in image production, institutional commissioning, and the ethics of witnessing. The paper offers geographers a critical lens through which to understand global health as a situated, contested, and relational phenomenon
BUILDING A GREEN INTELLECTUAL PROPERTY REGIME: HOW PATENT LAW CAN FACILITATE TECHNOLOGY TRANSFER OF ENVIRONMENTALLY SOUND TECHNOLOGIES
No full textClimate change is the common concern of humankind which should be dealt efficiently through international cooperation. Innovations and transfer of environmentally sound technologies (“ESTs”) are one of the most effective ways to mitigate climate change which have been the prime focus of multiple multilateral agreements and negotiations. The access to such technologies is vital for all the countries, irrespective of their developmental needs, so as to build a legal regime surrounding technology transfer (“TT”) of ESTs where ESTs are classified as global public good. However, the current claim is that such access is difficult for two reasons: firstly, there is a negligible and inefficient TT of ESTs due to the dearth of international legal instruments; and secondly, the concentration of ESTs lies in the hands of a few countries and/or corporations.This thesis explores the potential for a differentiated patent regime tailored to ESTs, integrating competition law flexibilities and alternative mechanisms, such as open-source frameworks, to balance innovation incentives with the public interest in mitigating climate change. Through a multi-layered analysis, the thesis investigates ESTs’ unique status as quasi-public goods and the inadequacies of current international frameworks – specifically under the UNFCCC, WTO, and WIPO – in facilitating effective TT. It critiques existing global patent systems, highlighting misalignments between patent protections and the urgent need for climate action. As there is a lack of sector and geographic specific empirical research, the thesis will contribute by focusing on the relationship between IPRs, innovation and TTs within sector and geographic specific ESTs. Employing empirical patent landscape analyses and doctrinal legal research, the thesis identifies strategic trends in EST ownership and proposes actionable reforms to overcome barriers to innovation diffusion. A Green Intellectual Property regime is proposed, structured to harmonise IPRs with climate objectives. This regime prioritises heightened patentability standards, tailored durations, and narrowed scopes for EST patents, ensuring a targeted approach to innovation and accessibility. Complementary strategies, including leveraging TRIPS flexibilities and adopting alternative mechanisms like patent pooling and open-source models, are explored to address the limitations of market-driven solutions. The thesis underscores the importance of international collaboration, recommending the involvement of key organisations such as WIPO, WTO, and UNFCCC in fostering an inclusive and sustainable IP framework. By aligning patent law with environmental priorities, the thesis aims to facilitate the equitable dissemination of ESTs, bridging global disparities and promoting sustainable development
