Greening the Path to Carbon Neutrality: The Role of Technical Factors in Reducing Carbon Emissions in South Asia Post‐COP 28

The rapid industrialization and economic growth of South Asia have improved living standards but also exacerbated CO2 emissions, intensifying the region's climate vulnerabilities. While existing literature has extensively examined green growth strategies in developed economies, few studies explore how green technological innovation, finance, and trade policies interact to shape emissions in South Asia, a region with distinct developmental challenges and high climate risks. This study investigates whether green energy adoption, technological innovation, and sustainable investments can decouple economic growth from emissions in South Asian economies from 1995 to 2022. Using second‐generation panel econometrics—accounting for cross‐sectional dependence and slope heterogeneity—along with AMG and CCEMG estimators, we assess long‐term relationships, supplemented by causal analysis, CuP‐FM and CuP‐BC for robustness. The results demonstrate that green technological innovation, green energy, and green finance significantly reduce CO2 emissions, while trade liberalization increases them, likely due to carbon‐intensive export structures and weak environmental regulations, a critical finding for regional policymaking. Furthermore, green investment mitigates emissions but requires stronger institutional support to align with COP28 mandates and SDGs (7, 9, 11–13). This study contributes to the literature by addressing the gap in South Asia–specific green growth analyses, integrating COP28 resolutions into empirical policy recommendations, and demonstrating the underutilized potential of green finance and innovation in achieving carbon neutrality. The findings urge policymakers to prioritize sustainable infrastructure, reform trade policies to reduce emissions leakage, and scale targeted green investments to reconcile economic and environmental goals

The influence of athletic profile on acute neuromuscular response to a repeated sprint protocol in youth females: a pilot study

Athletic profiles influence how athletes tolerate exposure to high-intensity activities and training-induced fatigue. Current understanding of athletic profiles has been derived primarily from adult male populations which limits the application of this potentially important training knowledge to females, and in particular youth females. Therefore, this study aimed to address this bias and examine the influence of athletic profiles on acute neuromuscular response in 118 female multisport athletes aged between 8 and 22 (age: 13.6 ± 2.9; stature: 155.9 ± 13.9; body mass: 50.2 ± 16.1). All participants completed sprint speed (5, 40 m, and maximal sprint speed [MSS]) and strength characteristics (Isometric mid-thigh pull) immediately pre- and post-a repeated sprint protocol. Anaerobic Speed Reserve was calculated from performance tests (MSS and maximal aerobic speed) with participants subsequently categorized (slow, hybrid or fast). Excluding relative peak force, there were significant differences in all sprint speed and strength characteristics between slow and hybrid and significant differences between slow and fast profile athletes before repeated sprinting. Dependent t-tests revealed significant (p = 0.001, d = 0.58) reductions in 40 m performance for fast athletes and a significant decrease in MSS for both hybrid (p = 0.003, d = 0.47) and fast athletes (p = 0.002, d = 0.58). This suggests that female athletes with hybrid, and fast athletic profiles may experience greater negative neuromuscular response following repeated sprints. Practitioners should therefore consider individualizing training and monitoring neuromuscular response to training to prevent athletic profile-related performance reductions, overreaching or injury accumulating over time

Pictures at an Exhibition—AI-Driven Surrealist Futures: The Case of Reimagining Higher Education through Aesthetic Critique

This chapter explores the problematic of critique in the era of human-AI interaction. Drawing on Benjamin’s conception of dialectics at a standstill, the research makes use of an AI image generative application to construct an ‘exhibition’ of six imaginations—previously published as part of an imminent critique of entrepreneurial capitalistic economics. The research aim is to explore the potential of AI as a critical tool to unlock, access, or make visible, the value of human imagination. It addresses the question: can we (collectively) cultivate the use of genAI as a tool for a more general aesthetic engagement with a critical understanding of our future potential as a society? The chapter adopts a methodology of Applied Negative Dialectics, drawing implications from a single-case method, using AI-generated images of the future of Business Schools in Higher Education. The conclusion drawn is that the use of AI to garner the intrinsic value of ‘an empirics of the imagination’, in relation to the immanent critique of a defined area of socio-economic activity, provides the excitement of an AI that has value in facilitating the curation, exploration and enhancement of—rather than merely the replication and imitation of—the human experience. The chapter may benefit critical scholars, social and cultural theorists, artists and AI researchers by offering a new approach to utilising AI and aesthetically-informed judgment in socio-economic knowledge production

AI-driven strategies for enhancing Mpox surveillance and response in Africa

Mpox, a zoonotic viral disease endemic to several African countries, has re-emerged as a significant public health concern, particularly in regions with limited healthcare resources. Current public health strategies in Africa fall short due to fragmented surveillance systems, delayed diagnostic capabilities, and inadequate resource distribution networks that cannot effectively respond to rapidly evolving outbreaks in remote and underserved areas. This narrative review explores the potential of Artificial Intelligence (AI) to enhance the management and control of Mpox in Africa. AI technologies, including machine learning and predictive analytics, can significantly improve early detection, surveillance, contact tracing, case management, public health communication, and resource allocation. AI-driven tools can analyze large datasets to identify outbreak patterns, automate contact tracing through mobile data, optimize treatment plans, and tailor public health messages to specific communities. However, the successful implementation of AI faces challenges, including limited digital infrastructure, data quality issues, ethical concerns, and the need for capacity building. Furthermore, ongoing research is essential to refine AI algorithms and develop culturally sensitive applications. This review emphasizes the need for investment in infrastructure, training, and ethical frameworks to fully integrate AI into public health systems in Africa. By addressing these challenges, AI can play a pivotal role in mitigating the impact of Mpox and enhancing the resilience of healthcare systems against future infectious disease outbreaks. This represents a novel comprehensive synthesis of AI applications specifically for African Mpox control, providing a critical framework for evidence-based implementation strategies in resource-limited settings

Supporting and encouraging authors to publish Open Access Monographs with no REF2029 mandate

This online webinar explored how libraries are making the case for Open Access Monographs in the absence of a REF mandate. In August of last year, REF confirmed that the 2029 Research Excellence Framework will not have a mandate for Open Monographs, instead open access requirement for submission of longform outputs will be in place for the next assessment exercise, with implementation from 1 January 2029. Whilst this has delayed a sector wide transition to OA Books, there is still a need to support and encourage authors to publish open access monographs to encourage culture of Open Research and ensure the sector is ready for the 1st of January 2029

Osteomyelitis in complicated bones: the role of FDG PET/CT

Osteomyelitis in infections encompasses heterogeneous group of condition that frequently have high morbidity and comes at a huge cost to healthcare system. Accurate and early diagnosis is important for the proper management of the condition. FDG PET/CT has been found useful in the osteomyelitis of complicated bones, including prosthetic joint infections, fracture related infections and sternal wound infections. The altered anatomy and the replacement of marrow in some cases of metallic implant makes the use of anatomic-based methods less optimal. FDG PET/CT has been found to be useful under these circumstances, however, it also has its own limitation of lack of specificity especially due to inflammation. Recent meta-analysis of the role of FDG PET/CT in complicated osteomyelitis have result in the validation defined the indications for its use. This has led to the publication of best use criteria and recommendations of by joint committees of major nuclear medicine societies. KEY WORDS: Positron emission tomography computed tomography; Fluorodeoxyglucose F18; Bone fractures; Osteomyelitis; Joint prosthesi