搜索结果：rewrite

With many governments regulating the handling of user data-the General Data Protection Regulation, the California Consumer Privacy Act, and the Saudi Arabian Personal Data Protection Law-ensuring systems comply with data privacy legislation is of high importance. Checking compliance is a tricky process and often includes many manual elements. We propose that formal methods, that model systems mathematically, can provide strong guarantees to help companies prove their adherence to legislation. To increase usability we advocate a diagrammatic approach, based on bigraphical reactive systems, where privacy experts can explicitly visualise the systems and describe updates, via rewrite rules, that describe system behaviour. The rewrite rules allow flexibility in integrating privacy policies with user-specified systems. We focus on modelling notions of providing consent, withdrawing consent, purpose limitations, the right to access and sharing data with third parties, and define privacy properties that we want to prove within the systems. Properties are expressed using the computation tree logic and proved using model checking. To show the generality of the proposed framework, we apply it to two examples: a bank notification system, inspired by Monzo's privacy policy, and a cloud-based home healthcare system based on the Fitbit app's privacy policy.

The existing video anomaly detection (VAD) methods based on the contrastive language-image pre-training (CLIP) framework primarily rely on spatial-temporal features and label prompts, often overlooking high-level semantic information, such as text descriptions of abnormal behavior. Moreover, while data augmentation techniques are commonly used to expand video frames, text inputs typically remain unchanged throughout the training process, limiting the exposure of different texts to the same image. In this paper, we propose a text rewriting based CLIP model called TrCLIP-VAD. It first generates source caption descriptions for each video and then utilizes the In-Context Learning (ICL) capabilities of large language models (LLMs) to rewrite these captions, thereby enhancing semantic expression. Subsequently, we randomly select a caption and fuse it with visual features to detect anomalies. In addition, we introduce the Local-Global Multi-scale Mamba (LGM-Mamba) module. The LGM-Mamba module aims to capture the local-global temporal dependence of frame sequence and promote the deep fusion of visual and caption features to improve the detection performance. The experimental results show that TrCLIP-VAD achieves state-of-the-art performance on two widely used datasets, XD-Violence and UCF-Crime. Specifically, TrCLIP-VAD achieves 86.05% AP scores on XD-Violence dataset and 88.59% AUC scores on UCF-Crime dataset. The code is released at https://github.com/vpsg-research/TrCLIP-VAD.

Vector-borne diseases have long played a significant role in human mortality and public health crises in Brazil. Among these, neglected tropical diseases such as Leishmaniasis and Chagas disease require urgent attention. This paper develops a deterministic mathematical dynamical model to study the dynamics of mono and co-infection with Leishmaniasis and Chagas disease. We begin with a rigorous mathematical analysis of the model, including the computation of the basic reproduction number R0LC and its sensitivity indices, which help identify key parameters driving disease dynamics. The population's equilibrium states are studied in relation to this threshold parameter. Furthermore, we incorporate four control prevention into the model to evaluate the best intervention policy. Using a reliable data set from Brazil over a specified time period, we estimate model parameters and fit the data, demonstrating strong agreement between the model predictions and the actual data. Our graphical simulations further support the findings. Additionally, we compute and analyze the controlled reproduction number, confirming that the proposed policy 5 is the most effective in reducing the disease burden in Brazil. Finally, we rewrite the fractional version of the model and perform numerical simulations for different values of α. The fractional-order model is conceptually suitable for capturing memory effects and delay response in disease transmission dynamics. This study provides valuable insights for public health stakeholders and health care centers aiming to design efficient prevention and control programs for neglected vector-borne diseases.

ConspectusAvalanches within nanoparticles seem like science fiction, but if they are avalanches of photons, they open up real-world innovations in imaging, sensing, optical computing, and other unexplored light-driven technologies. Avalanches are outsized events arising from the integration of many smaller inputs, and photon avalanching (PA) was first reported in bulk crystals in 1979 as an unexpectedly large jump in luminescence as excitation intensity was slowly increased. It would be 41 years before PA would be observed at the nanoscale in photon avalanching nanoparticles (ANPs), Tm3+-doped upconverting nanoparticles that show excited-to-ground state absorption inversion greater than 10,000:1 and emission that scales nonlinearly up to the 32nd power of the pump intensity. This extreme nonlinearity enables a real-time 5-fold improvement in the 150-year-old Abbe limit of spatial resolution, achieving 70 nm resolution using only simple scanning confocal microscopy. This extreme nonlinearity also gives rise to a series of highly unusual optical and sensing properties. Tm3+ ANPs show NIR-controlled bidirectional photoswitching, lasting over 1000 cycles in ambient or aqueous conditions with no measurable sign of photodegradation. This enables 2- and 3-dimensional optical nanoscale patterning with full erase and rewrite capabilities. Unlimited photoswitching also underlies the super-resolution technique INPALM, which is capable of sub-Ångstrom localization precision and resolving individual ANPs within tightly packed clusters. Nd3+-based ANPs show the peculiar property of intrinsic optical bistability (IOB), a form of memory in which emission depends on whether the ANPs have previously undergone PA. This stable, history-dependent contrast makes these ANPs analogous to optical transistors and promising materials for optical computing, neuromorphic circuitry, and related photonic technologies. The steep nonlinearity of PA also makes ANPs exceptional sensors of external perturbations, as tiny environmental changes may be amplified into large changes in optical output. As force sensors, Tm3+ ANPs are able to detect forces over a dynamic range of 4 orders of magnitude, from piconewtons to micronewtons, a range that will enable force sensing in complex systems across scales. Application of current ANP designs to imaging and devices, discovery of new PA-associated phenomena, and design of new ANPs with unique properties are all underway as the novelty of this technology cascades toward new fundamental discoveries and applications.

Cellular senescence functions as a pivotal stress response with dual roles; it serves as a barrier against early tumorigenesis while paradoxically driving late-stage tumor progression and the pathogenesis of many other age-related diseases, including cardiovascular, neurodegenerative, metabolic, and fibrotic disorders. This review comprehensively elucidates how the senescent phenotype is orchestrated by a dynamic epigenetic landscape. We detail how dysregulation in chromatin remodeling (e.g., heterochromatin loss), histone modifications, DNA methylation , and the epitranscriptome rewrites genome architecture to govern the initiation and maintenance of the senescent phenotype within these specific disease contexts. Crucially, we highlight the profound heterogeneity of senescence across different pathologies, contrasting its detrimental role in driving tissue degeneration in organs like the lung and kidney against its context-dependent beneficial effects, such as limiting fibrosis in the liver. Furthermore, we evaluate the translational potential of epigenetic drugs-categorized by targets such as DNA methyltransferases (DNMTs), histone methyltransferases (HMTs), and histone deacetylases (HDACs)-as dual-purpose therapeutics. Unlike genetic mutations, epigenetic alterations are reversible. We discuss strategies to either enforce senescence barriers for cancer suppression (pro-senescence) or reverse epigenetic aging signatures for tissue rejuvenation (anti-senescence). This review proposes a roadmap for leveraging epigenetic plasticity, offering a precision medicine approach to target specific senescent cell populations and extend health span.

I wrote this paper based upon my psychoanalytic training and the psychoanalytic literature at that time. However, after finishing the paper a book was published that described the training experience of mostly European candidates that was very different. Rather than rewrite the entire paper I have left it as it was originally written, but included the perspective of the candidates and the report from Department of Psychoanalytic Education of the American Psychoanalytic Association.

Purpose Patient education materials (PEMs) enhance healthcare access and inclusivity, particularly for individuals without clinical backgrounds. However, many PEMs exceed recommended readability levels. This study evaluated whether artificial intelligence (AI)-assisted editing using ChatGPT-4o (OpenAI, San Francisco, CA, USA) could improve the readability of endourology PEMs related to prostate cancer, nephrolithiasis, bladder cancer, and kidney cysts. Methods Twenty-one publicly available PEMs from the American Urological Association (AUA) were analyzed. Each document was uploaded into ChatGPT-4o with instructions to rewrite the text to an eighth-grade reading level or lower while preserving content and word count. Readability of original and AI-modified PEMs was assessed using ReadabilityFormulas.com across six validated indices: Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), Gunning-Fog Index (GFI), Coleman-Liau Index (CLI), Automated Readability Index (ARI), and Flesch Reading Ease (FRE). Pre- and post-AI readability scores were compared using paired two-tailed t-tests. Results Across all indices and disease categories, AI modification significantly improved readability. Unmodified PEMs were written at approximately the ninth to 11th grade level, whereas AI-modified versions were reduced to the fourth to sixth grade range (p < 0.001 for all comparisons). AI-modified PEMs also demonstrated reduced variability across readability scores, indicating improved standardization. Conclusions ChatGPT-4o significantly improved the readability of AUA endourology PEMs, aligning them with established health literacy recommendations. AI-assisted editing represents a scalable and standardized approach to improving patient comprehension and accessibility of urologic education materials.

With the increasing prominence of mental health issues, automated psychological support dialogue systems have gradually gained attention. However, existing Chinese corpora mostly remain at the level of single-turn Q&A or lack psychological counseling theoretical grounding, making it difficult to cover the progressive interactions common in psychological counseling. Meanwhile, collecting and releasing large-scale real multi-turn dialogues faces challenges related to privacy protection and high costs. To address this, this paper proposes the Helping Skills Chain-of-Thought (HCoT) method, which integrates Helping Skills Theory with Chain-of-Thought prompting. We utilized GPT-4o to rewrite CD-CN single-turn data into a Chinese multi-turn psychological support corpus, HCoT-Corpus. This corpus contains 22,341 dialogues and 211,473 strategy annotations, achieving a systematic expansion in scale, structural depth, and theoretical grounding. Analysis results indicate that HCoT-Corpus demonstrates high structural coherence and multi-strategy collaborative characteristics under the "Exploration-Comfort-Action" three-stage framework. Experimental evaluations show that, compared to baselines like SMILE, the HCoT method achieves the most balanced performance in emotional resonance, strategy application, and structural integrity. Furthermore, HCoT-Chat, fine-tuned on Qwen2.5-7B-Instruct, achieved significant advantages in both automatic metrics and cross-model evaluations. This study demonstrates the HCoT method as a promising path for constructing large-scale, theoretically grounded psychological support dialogue datasets.

Tool learning has emerged as a promising paradigm for large language models (LLMs) to address real-world challenges. Due to the extensive and irregularly updated number of tools, tool retrieval for selecting the desired tool subset is essential. However, current tool retrieval methods are usually based on academic benchmarks containing overly detailed instructions (e.g., specific API names and parameters), while real-world instructions are more vague. Such a discrepancy would hinder the tool retrieval in real-world applications. In this paper, we first construct a new benchmark, VGToolBench, to simulate human vague instructions. Based on this, we conduct a series of preliminary analyses and find that vague instructions indeed damage the performance of tool retrieval. To this end, we propose a simple-yet-effective Tool Retrieval Bridge (TRB) approach to boost the performance of tool retrieval for vague instructions. The principle of TRB is to introduce a bridge model to rewrite the vague instructions into more specific ones and alleviate the gap between vague instructions and retriever preferences. We conduct extensive experiments under multiple commonly used retrieval settings, and the results show that TRB effectively mitigates the ambiguity of vague instructions while delivering consistent and substantial improvements across all baseline retrievers. For example, with the help of TRB, BM25 achieves a relative improvement of up to 111.51%, i.e., increasing the average NDCG score from 9.73 to 19.59. The source code and models are publicly available at https://github.com/kfchenhn/TRB.

Bladder cancer (BCa) represents the most frequently malignancies of the urinary system with high recurrence rates and heterogeneous outcomes. While peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1) is recognized as an oncogene in multiple cancers, its expression pattern, biological function, and the molecular basis of bladder tumorigenesis is still poorly understood. We performed comprehensive single-cell RNA sequencing (scRNA-seq) analysis to characterize the cellular heterogeneity of BCa tumor microenvironment and identify malignant epithelial cells. Through integrative bioinformatics approaches combining differential expression analysis, survival correlation, and cellular senescence association, PIN1 was identified as a key downregulated gene. We systematically validated PIN1 expression in clinical specimens and cell lines using immunohistochemistry, Western blot, and qRT-PCR. Functional consequences of PIN1 manipulation were assessed through in vitro assays measuring proliferation, apoptosis, migration, invasion, and cellular senescence. A xenograft mouse model was established to evaluate tumor growth and senescence induction in vivo. RNA sequencing and pathway enrichment analysis were conducted to explore the molecular mechanisms. PIN1 was significantly downregulated in malignant epithelial cells of BCa tissues compared to normal counterparts. Low PIN1 expression correlated strongly with poor overall survival (HR&#xa0;=&#xa0;0.693, p&#xa0;=&#xa0;0.0265) and progression-free survival (HR&#xa0;=&#xa0;0.698, p&#xa0;=&#xa0;0.0471). Elevated PIN1 expression markedly reduced the proliferative, clonogenic, migratory, and invasive capacities of bladder cancer cells, while concurrently driving apoptosis and senescence. Conversely, PIN1 depletion intensified malignant behavior. In vivo studies further showed that PIN1 up-regulation restrained tumor expansion and elevated senescence-associated &#x3b2;-galactosidase activity. Mechanistically, PIN1 overexpression activated the interferon response pathway, upregulating key components including IFNAR1, IRF7, and IRF9. Rescue experiments confirmed that blockade of the interferon pathway partially reversed PIN1-induced growth suppression and senescence, indicating that interferon signaling is a critical downstream mediator of PIN1's tumor-suppressive effects. Our study reveals PIN1 as a previously unrecognized bladder-cancer tumor suppressor that halts progression by provoking senescence and re-awakening interferon signaling. This work rewrites the molecular landscape of the disease and positions PIN1 as both a prognostic indicator and a druggable node for future therapies.

Sarcopenia, loss of muscle mass is a considerable health burden that demands immediate societal attention. Direct myogenic somatic cell reprogramming, a potential muscle regeneration method is constrained by an inability to control the signaling logic that governs cell fate. Here, we show that this barrier can be overcome using AI-designed receptor modulators. Screening de novo minibinders, we identify a synthetic protein cocktail, C6-DPC, that drives efficient human fibroblast-to-muscle transdifferentiation with robust structural and metabolic maturation. C6-DPC reprograms extracellular signaling by activating pro-myogenic FGFR1/2c pathways while suppressing anti-myogenic inputs through ALK1 and TGFBR2; targeted depletion of ALK1 is sufficient to lower the reprogramming barrier. Inflammatory signaling via gp130 emerges as a dominant checkpoint, and its inhibition further enhances conversion. Engineered tissues generate high twitch and tetanic forces in both wild-type and dystrophin-deficient human cells. These findings demonstrate that programmable synthetic ligands can rewrite receptor-level signaling to direct cell fate and enable functional tissue regeneration.

For 2 years, the people of Gaza have been killed, maimed and displaced in a devastating war that is an affront to humanity. It is one of the ongoing wars, some of which have been going on for years, and many of which are submerged or ignored by the international community. Once again, and more than ever, the victims are civilians, especially children. In the Gaza Strip, 64&#x2009;000 children have reportedly been killed or maimed, including at least 1000 babies. It is highly likely that the number of deaths is much higher, due to preventable illnesses or bodies remaining buried under rubble. What will happen to the surviving children once hostilities are suspended? What has happened under other circumstances? Every war is different in its motivations, methods, duration and (always dire) outcomes, but what can we expect for Gazan children?An analysis of three historical conflicts (Iraq, Democratic Republic of Congo and Haiti) indicates that, after the acute phase of an armed conflict, it takes approximately 10 years to restore, maintain and resume the trends in improvement in the under-5 mortality rate, in rates of vaccination coverage, wasted children and completion of primary education to preconflict levels. These results may be useful for monitoring future interventions to re-establish, or guarantee for the first time, the rights denied to children and the entire population. It would also be helpful to rewrite treaties and agreements for the suspension of conflict that go beyond the reconstruction of buildings and economic aid, but that also define specific objectives and timelines based on health determinants, which are nothing other than indicators of the implementation of human rights.