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Unveiling open-set noise: theoretical insights into label noise
No full textLearning with Noisy Labels (LNL) reduces reliance on high-quality labeled data but often overlooks open-set noise, where noisy samples belong to unknown classes, unlike closed-set noise within known categories.This paper advances LNL by reformulating the problem to incorporate open-set noise through a complete noise transition matrix, enabling a theoretical comparison of its impact on classification error rates against closed-set noise. Our analysis reveals that open-set noise induces smaller error increases, with distinct effects from 'hard' (semantically similar to inliers) and 'easy' (dissimilar) variants. We evaluate entropy-based detection, finding it effective only for easy open-set noise, and propose solutions leveraging vision-language models and self-supervised learning to address hard noise challenges. For empirical validation, we introduce CIFAR100-O, ImageNet-O, and a WebVision open-set test set, enabling robust benchmarking of LNL methods under open-set noise conditions. Recognizing classification accuracy's limitations in capturing model robustness, we advocate out-of-distribution (OOD) detection as a complementary metric. Our theoretical and empirical results highlight the unique challenges of open-set noise, offering new tools and evaluation frameworks to enhance LNL robustness in real-world scenarios.<br/
Gen4Track: a tuning-free data augmentation framework via self-correcting diffusion model for vision-language tracking
No full textThe performance of current Vision-Language Tracking (VLT) models is constrained by the limited diversity and quantity of labeled data. Compared to constructing large-scale datasets, data augmentation offers a more cost-saving strategy for VLT by synthesizing new samples from existing data, rather than generating them from scratch. However, conventional techniques like rotation and flipping may disrupt scene composition, causing conflicts between visual layouts and textual annotations. Recent advances in generative models have inspired the use of synthetic videos for data augmentation. Yet, existing approaches fail to address the core concerns of data augmentation in VLT (shown in Fig. 1)-target location accuracy, text-video consistency, and video content coherency. To bridge the gap, we propose Gen4Track, a tuning-free data augmentation framework that leverages the self-correcting mechanism to dynamically generate high-quality video data with annotations. Our approach involves (1) optimizing the attention calculations in a frozen text-to-image diffusion model to synthesize coherent videos that satisfy specific conditions (e.g., spatial location, category, color, and style), and (2) implementing a self-correcting mechanism based on a Large Language Model (LLM) to improve text-video consistency. During video augmentation, we propose content-coherent self-attention and location-enhanced cross-attention mechanisms, ensuring that image-level editings are accurately and coherently propagated throughout the video. Then, with the goal of maximizing text-video consistency, we iteratively refine the augmentation instruction with our designed self-correcting mechanism for a more aligned video. Extensive experiments validate that Gen4Track significantly boosts the performance of SOTA VLT models (achieving improvements of up to 3.2% in SUC and 3.5% in PRE), opening a new chapter of training Vision-Language trackers with synthetic videos rather than manually annotated data
Distribution locational marginal emission for carbon alleviation in distribution networks: formulation, calculation, and implication
No full textRegulating the proper carbon-aware intervention policy is one of the keys to emission alleviation in the distribution network, whose basis lies in effectively attributing the emission responsibility using emission factors. This paper establishes the distribution locational marginal emission (DLME) to calculate the marginal change of emission from the marginal change of both active and reactive load demand for incentivizing carbon alleviation. It first formulates the day-head distribution network scheduling model based on the second-order cone program (SOCP). The emission propagation and responsibility are analyzed from demand to supply to system emission. Considering the complex and implicit mapping of the SOCP-based scheduling model, the implicit theorem is leveraged to exploit the optimal condition of SOCP. The corresponding SOCP-based implicit derivation approach is proposed to calculate the DLMEs effectively in a model-based way. Comprehensive numerical studies are conducted to verify the superiority of the proposed method by comparing its calculation efficacy to the conventional marginal estimation approach, assessing its effectiveness in carbon alleviation with comparison to the average emission factors, and evaluating its carbon alleviation ability of reactive DLME. Note to Practitioners—This paper proposes the novel distribution locational marginal emission (DLME) to calculate the marginal change of emission from the marginal change of both active and reactive load demand for incentivizing carbon alleviation in the distribution network. The proposed SOCP-based implicit derivation approach calculates the DLMEs effectively in a model-based way. The DLME can incentivize effective demand response for carbon alleviation in the distribution network. The proposed method can be applied to the distribution network management for carbon alleviation and emission reduction. We conduct case studies to verify the effectiveness of the proposed method in various distribution networks under various scenarios. Numerical results show that the proposed DLME can enhance 10%-200% of the carbon alleviation effectiveness compared to the average emission factors
The resistance of Salmonella enterica serovar Typhimurium to zinc oxide nanoparticles
No full textZinc oxide nanoparticles (ZnO NPs) serve as promising antibiotic alternatives owing to their exceptional antibacterial properties. However, it is inconclusive whether bacteria can develop resistance to ZnO NPs under chronic exposure. In this study, we identified an acquired and irreversible resistance to sublethal concentrations of ZnO NPs, but not to Zn (II) ions, in a strain of Salmonella enterica serovar Typhimurium CVCC541 (S. Typhimurium) following prolonged exposure. Whole-population genome sequencing authenticated a phoQ mutation pertained to this heritable resistance. The phoQ G33A mutation was accompanied by a downregulation of phoQ expression, triggering a remodeling of the outer membrane (characterized by increased production of OmpF and lipopolysaccharides, as well as altered lipid properties) and enhanced biofilm formation. Accordingly, we propose that S. Typhimurium adapts to ZnO NPs exposure by fortifying its outer membrane and biofilm, thereby evolving resistance. Our findings provide an innovative paradigm for an in-depth knowledge of the antimicrobial resistance crisis
Intermedia agenda-setting at the network level: Turkish women's volleyball team in the media and on Instagram
No full textMcCombs (1992) highlighted the evolution of the agenda-setting concept, which has expanded from public issues to encompass gender-related topics, particularly in sports media. Research indicates that male athletes receive significantly more coverage than female athletes, often portrayed in ways that emphasize power and dominance, while female athletes are depicted through the lens of femininity and family life. This disparity influences audience perceptions of female athletes' importance. In Türkiye, media coverage of female athletes is similarly limited, with negative portrayals and objectification prevalent, especially in football. However, Turkish women's volleyball presents a notable exception, as female athletes have surpassed male counterparts in elite competitions. Their achievements in 2023 gained significant attention from both national and international media (e.g., Anadolu Ajansı, The New York Times). This study employs McCombs' agenda-setting theory to analyse the influence of Instagram on mainstream media coverage of the Turkish Women's Volleyball Team's triumphs in 2023. While traditional agenda-setting theory has demonstrated that media shapes public perceptions, the rise of social media has altered this dynamic, allowing citizens to influence mainstream narratives. Utilizing a network agenda-setting (NAS) framework, the study will explore whether Instagram content about the volleyball team's success influenced mainstream media coverage or vice versa. The NAS model posits that media connects different issues in news stories as bundles, transferring the salience of these bundled messages to the public. Given that Instagram boasts over 2 billion users globally, including 58.7 million in Türkiye, this study aims to assess the correlation between Instagram and traditional media agendas. It hypothesizes that mainstream media anticipates the public's Instagram agenda (Hypothesis 1) and that Instagram posts predict the content of newspapers (Hypothesis 2).<br/
Decoding oncogenic secrets of regulator of chromosome condensation 1: A breakthrough mechanistic evidence from breast and lung cancer models
No full textThe Regulator of Chromosome Condensation 1 (RCC1), a master regulator of cell cycle progression, chromatin structure, and nuclear transport, emerges as a powerful driver of cancer progression. Elevated RCC1 expression in breast and lung cancers is closely tied to enhanced tumor cell survival, proliferation, and metastasis, positioning it as a promising therapeutic target. This study unveils RCC1's pivotal role in cancer biology by silencing its expression in MDA-MB-231 (breast cancer) and A549 (lung cancer) cell lines using shRNA. RCC1 knockdown dramatically reduced cell viability, colony formation, and motility, while inducing apoptosis, as evidenced by increased apoptotic markers and reduced anti-apoptotic Bcl2 expression. Gene expression analysis revealed downregulation of cell cycle and DNA repair pathways, highlighting RCC1's critical role in sustaining oncogenic mechanisms. These findings underscore RCC1 as a gatekeeper of tumor survival, capable of resisting apoptosis and promoting metastasis. Targeting RCC1 offers a dual advantage: disrupting cancer growth and enhancing apoptotic pathways, creating an exciting opportunity for precision therapies. By illuminating RCC1's integration into survival networks, this study not only advances our understanding of cancer biology but also lays the groundwork for innovative treatments aimed at halting cancer progression and metastasis
General Dental Practitioners’ views of managing dental disease in adults who have been previously treated with head and neck radiotherapy: a qualitative study
No full textObjectivesTo determine the views of General Dental Practitioners on management of head and neck cancer patients in primary care, following radiotherapy treatment.MethodsA sample of fifteen general dental practitioners (GDPs) were recruited to undergo a semi-structured interview with a qualitative researcher using a topic guide. The collected data was then analysed using a thematic analysis.ResultsData was categorised into four major themes- 'Experience and expectations', 'Importance of Communication', 'Preventive Care' and 'Concerns around Dental Extractions'. Providing preventative care and undertaking dental extractions were of most concern to the GDPs. Participants reported feeling isolated and emphasised the importance of effective communication regarding the care of this patient group. A lack of awareness of clinical guidelines and variability in preventative care further compound these difficulties.ConclusionGDPs highlighted barriers to caring for post radiotherapy patients including limited experience, financial disincentives, and inadequate communication from the multidisciplinary hospital-based teams. Addressing these issues through improved communication pathways, enhanced clinical training, and systemic workforce reforms may optimise care delivery for this high-risk patient population. Clinical significance: The findings of this study underscore the need for enhanced clinical training and clearer guidelines to equip GDPs with the skills required for the effective management of post radiotherapy patients in primary care. These resources may help mitigate barriers to care, ultimately reducing the risk of dental complications such as osteoradionecrosis and improving patient outcomes