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Multi-Person Interaction Generation from Two-Person Motion Priors
Get PDFGenerating realistic human motion with high-level controls is a crucial task for social understanding, robotics, and animation. With high-quality MOCAP data becoming more available recently, a wide range of data-driven approaches have been presented. However, modelling multi-person interactions still remains a less explored area. In this paper, we present Graph-driven Interaction Sampling, a method that can generate realistic and diverse multi-person interactions by leveraging existing two-person motion diffusion models as motion priors. Instead of training a new model specific to multi-person interaction synthesis, our key insight is to spatially and temporally separate complex multi-person interactions into a graph structure of two-person interactions, which we name the Pairwise Interaction Graph. We thus decompose the generation task into simultaneous single-person motion generation conditioned on one other’s motion. In addition, to reduce artifacts such as interpenetrations of body parts in generated multi-person interactions, we introduce two graph-dependent guidance terms into the diffusion sampling scheme. Unlike previous work, our method can produce various high-quality multi-person interactions without having repetitive individual motions. Extensive experiments demonstrate that our approach consistently outperforms existing methods in reducing artifacts when generating a wide range of two-person and multi-person interactions
“Nae problem here”: troubling race and racism in Scottish education
Get PDFThis article examines how Scottish schools perpetuate racism and uphold White normativity. It troubles frameworks which buttresses colour-evasive forms of racism in schools and calls for a more critical examination of how White normativity is embedded in educational policy, structures, and practices. Utilising Critical Race Theory and phenomenology of Whiteness, it offers priorities for practice that consider and advance knowledge for teaching an anti-racist curriculum. It calls attention to addressing the material and structural practices of White normativity, intersectional oppression and for schools to forge alliances with third-sector organisations that provide anti-racist advocacy and teaching support
Mode-locked DBR and DFB lasers with multiple phase-shifted gratings for THz generation
Get PDFWe propose mode-locked distributed Bragg reflector (DBR) and distributed feedback (DFB) lasers based on multiple phase-shift gratings (MPSGs) for terahertz (THz) signal generation, with the latter incorporating an equivalent π-phase shift. By integrating optimized MPSGs, we achieve multi-channel lasing with uniform reflectivity and dense channel spacing. Modelocked DBR lasers operating at THz frequencies of 150 GHz, 400 GHz, 800 GHz, and 1.2 THz have been demonstrated, as confirmed by second harmonic generation measurements. Additionally, a 200 GHz mode-locked DFB laser was realized. Amplified by an erbium-doped fiber amplifier (EDFA), the modelocked DFB laser output was injected into a photoconductive antenna (PCA) to generate THz signals, with the measured power reaching 19.6 μW. These results highlight the potential of MPSGbased mode-locked lasers for compact and efficient THz generation systems
Priming thermotolerance: unlocking heat resilience for climate-smart crops
Get PDFRising temperatures and heat waves pose a substantial threat to crop productivity by disrupting essential physiological and reproductive processes. While plants have a genetically inherited capacity to acclimate to high temperatures, the thermotolerance capacity of many crops remains limited. This limitation leads to yield losses, which are further intensified by the increasing intensity of climate change. In this review, we explore how thermopriming enhances plant resilience by preparing plants for future heat stress (HS) events and summarize the mechanisms underlying the memory of HS (thermomemory) in different plant tissues and organs. We also discuss recent advances in priming agents, including chemical, microbial and physiological interventions, and their application strategies to extend thermotolerance beyond inherent genetic capacity. Additionally, this review examines how integrating priming strategies with genetic improvements, such as breeding and genome editing for thermotolerance traits, provides a holistic solution to mitigate the impact of climate change on agriculture. By combining these approaches, we propose a framework for developing climate-resilient crops and ensuring global food security in the face of escalating environmental challenges.
This article is part of the theme issue ‘Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the ‘Resilience Revolution’?’
Access to public services and access to justice for refugees and asylum seekers in Northern Ireland
Get PDFNo abstract available
“We are here and we deserve it”: being an autistic teacher in Poland
Get PDFDespite an increasing focus on autism, neurodiversity and inclusion in the education sector, there remains limited awareness of the experiences, needs and strengths of autistic educators. This gap in understanding results in a failure to grasp the importance of this population in fostering inclusion and diversity across whole school communities. In this study, we explore the views and experiences of n = 10 autistic teachers in Poland via interpretative content analysis. Set within the context of the Polish education sector and informed by a neurodiversity and social model of disability framework, a number of difficulties are revealed by participants. These include significant sensory impacts, social and communication disconnections, the need to conceal autistic identity and difficulties navigating processes of promotion. However, attributes and strengths were also evident, especially in relation to autistic pedagogy. We argue that it is only by adopting a neurodiversity and rights-informed understanding of autism, instead of a charity and social care model, that the disadvantages autistic teachers experience can be reduced, and their skills facilitated. In so doing, and by addressing inclusion holistically, schools can be more welcoming to neurodivergent staff and pupils
Adaptive stylized image generation for traditional Miao batik using style-conditioned LCM-LoRA enhanced diffusion models
Get PDFAs a national intangible cultural heritage in China, traditional Miao batik has encountered obstacles in contemporary dissemination and design due to its reliance on manual craftsmanship and other reasons. Existing generative models are difficult to fully capture the complex semantic and stylistic attributes in Miao batik patterns, which limits their application in digital creativity. To address this issue, we construct the structured CMBP-9 dataset to facilitate semantic-aware image generation. Based on stable diffusion v1.5, Low-Rank Adaptation (LoRA) is used to effectively transfer the structure, sign, and texture features that are unique to the Miao people, and the Latent Consistency model (LCM) is integrated to improve the inference efficiency. In addition, a Style-Conditioned Linear Fusion (SCLF) strategy is proposed to dynamically adjust the fusion of LoRA and LCM outputs according to the semantic complexity of input prompts, thereby overcoming the limitation of static weighting in existing frameworks. Extensive quantitative evaluations using LPIPS, SSIM, PSNR, FID metrics, and human evaluations show that the proposed Batik-MPDM framework achieves superior performance in terms of style fidelity and generation efficiency compared to baseline methods
Artificial light at night weakens body condition but does not negatively affect physiological markers of health in great tits
Get PDFUrbanisation brings many novel challenges for wildlife through changes to the natural environment, one of the most unprecedented of these modifications is artificial light at night (ALAN). ALAN has been shown to have profound effects on the behaviour and physiology of many wildlife species which in turn have negative consequences for fitness and survival. Despite increasing knowledge of the mechanisms by which ALAN can affect health, studies that have investigated this relationship have found contrasting results. This study investigated the impact of ALAN on health biomarkers in 13-day old great tit (Parus major) nestlings including Malondialdehyde (a measure of oxidative damage), antioxidant capacity of plasma, feather corticosterone levels and scaled mass index. Immediately after hatching, broods were either exposed to 1.8 lux of ALAN until day 13 or left unexposed. ALAN treatment significantly reduced scaled mass index but there were no clear negative effects of ALAN on malondialdehyde, antioxidant capacity, or corticosterone. This demonstrates that only certain aspects of health are impacted by early life ALAN, highlighting the importance of future studies measuring several biomarkers of health when investigating this relationship. Nestlings that fledge the nest in poor body condition have a decreased chance of surviving into adulthood. As urbanisation continues to expand, the negative effects of ALAN on wildlife are likely to become more pronounced. Therefore, it is crucial to gain a better understanding of this relationship
Exploring risk and protective factors which distinguish suicidal and self-harm behaviours from suicidal and self-harm ideation in young people: a systematic review
Get PDFBackground:
Self-harm and suicidal thoughts and behaviours among young people are significant global public health concerns. Although most young people with thoughts of selfharm or suicide do not act on their thoughts, it is important to identify factors that distinguish thoughts of self-harm and suicide from behaviours. To date, there are no reviews distinguishing self-harm and suicidal behaviours from thoughts of self-harm and suicide in young people or that have synthesised factors distinguishing self-harm
behaviours from self-harm ideation. The current review addresses these gaps in the literature.
Methods:
We systematically searched: CINAHL, Embase, Medline, PsycINFO, Psychology and Behavioural Sciences Collection, and Web of Science Core Collection for articles published between 2011 and April 2024. Ninety-nine studies met inclusion criteria, with 92 articles examining risk and protective factors that distinguished suicide attempts from suicidal ideation and seven articles examining factors that distinguished self-harm behaviours from self-harm ideation. Using a narrative synthesis
approach, studies were grouped by their outcome variable (e.g., self-harm or suicide) and then by risk and protective factors.
Results:
While findings were inconsistent, the presence of non-suicidal self-injury, physical, emotional, or sexual abuse, violence, and family factors (e.g., family conflict) distinguished suicidal attempts from suicidal ideation. By contrast, the presence of parentalfactors (e.g., parental connectedness) and greater academic achievement were protective and distinguished suicidal ideation from suicide attempts. Being female, exposure to self-harm/suicide, and impulsivity distinguished self-harm behaviours from
self-harm ideation. There was no evidence of protective factors that distinguished self-harm behaviours from self-harm ideation.
Conclusions:
The current review highlights important risk and protective factors that distinguish suicidal and self-harm behaviours from suicidal and self-harm ideation in young people. Our review has important implications for intervention and prevention efforts as identifying key risk and protective factors can improve risk assessment for young people experiencing thoughts of self-harm and suicide and enable more targeted interventions
A conflicts-free, speed-lossless KAN-based reinforcement learning decision system for interactive driving in roundabouts
Get PDFSafety and efficiency are crucial for autonomous driving in roundabouts, especially mixed traffic with both autonomous vehicles (AVs) and human-driven vehicles. This paper presents a learning-based algorithm that promotes safe and efficient driving across varying roundabout traffic conditions. A deep Q-learning network is used to learn optimal strategies in complex multi-vehicle roundabout scenarios, while a Kolmogorov-Arnold Network (KAN) improves the AVs’ environmental understanding. To further enhance safety, an action inspector filters unsafe actions, and a route planner optimizes driving efficiency. Moreover, model predictive control ensures stability and precision in execution. Experimental results demonstrate that the proposed system consistently outperforms state-of-the-art methods, achieving fewer collisions, reduced travel time, and stable training with smooth reward convergence
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