allenai/openscilm_queries huggingface dataset:
Query: A 9-year-old girl with respiratory distress, dry cough exacerbated at night and triggered by exercise, and fever for about 48 h before admission was admitted to our department. In her past medical history, she was diagnosed of previous childhood asthma at 3 years of age. Atopy history and skin prick test of aeroallergens in past medical history and records were negative. Asthma control was achieved with inhale corticosteroid and asthma treatment stopped after two years. The patient had neither had an asthma attack nor needed asthma related medication in the last 4 years of her life. Latest pulmonary function test was one year before admission, which revealed FEV1: 85%, FEV1/FVC: 91%, FVC: 93%, and PEF: 78%. The initial physical examination revealed diffuse rales and wheezing. Her vitals revealed tachypnea (respiratory rate: 32), tachycardia (pulse rate: 135), temperature of 38, and oxygen saturation levels of 80% in room air.
Subject: medicine
Intent: Other
Query: what is the effect of NK cells on the upregulation of the following genes.NTSR1
HLA-F
LSMEM1
PPP1R11
CDH5
UTS2
TBX18
MASP1
PINX1
SLC24A4
CMTM1
KISS1R
NECAB2
MYO7B
RAD17
CD33
EDNRB
MARVELD2
FGF11
AL591806.3
TDRD9
BMP6
C17orf50
IER3
CHI3L2
LAIR1
HLA-DRB1
AMTN
LONRF3
GJA1
CEMIP
SLC46A2
ZNF257
PDE6A
CRPPA
IL22RA2
DHRS4
SLFN12
CPED1
PAQR5
ASGR2
KRT6C
GAREM2
STRIP2
PPP1R3G
PPFIA4
SOWAHD
CDC14C
CEP295NL
PCDHB2
Subject: immunology
Intent: Literature Understanding
Query: I am planning to conduct a litterature review on LLM security and privacy, please discuss the similarities and difference between the following survey paper on the topic and give me potential idea to refine these surveys : 1) A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly 2) Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks 3) Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents 4) Exploring Vulnerabilities and Protections in Large Language Models: A Survey 5) Risks, Causes, and Mitigations of Widespread Deployments of Large Language Models (LLMs): A Survey 6) Can LLMs be Fooled? Investigating Vulnerabilities in LLMs 7) Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications 8) Security and Privacy Challenges of Large Language Models: A Survey 9) When LLMs Meet Cybersecurity: A Systematic Literature Review
Subject: computer science
Intent: Literature Understanding
Query: . Introduction to Organoids
Organoids are essentially tiny, simplified versions of our organs, grown in the lab. Originally, the term "organoid" was used to describe 3D clusters of cells that formed in a dish without any solid surface to stick to. Today, organoids are defined as 3D structures grown from stem cells that:
•	Retain the organ’s cellular identity: They include both the stem cells and the specialized cells you’d find in the actual organ.
•	Mimic the source organ’s architecture: They bring together multiple cell types and even show some aspects of how the organ functions.
•	Self-organized: They follow natural developmental rules, much like the real organ they represent.

Subject: biology
Intent: Other
Query: Since late 2022, generative AI has taken the world by storm, with widespread use of tools including ChatGPT, Gemini, and Claude. Generative AI and large language model (LLM) applications are transforming how individuals find and access data and knowledge. However, the intricate relationship between open data and generative AI, and the vast potential it holds for driving innovation in this field remain underexplored areas. This white paper seeks to unpack the relationship between open data and generative AI and explore possible components of a new Fourth Wave of Open Data: Is open data becoming AI ready? Is open data moving towards a data commons approach? Is generative AI making open data more conversational? Will generative AI improve open data quality and provenance? Towards this end, we provide a new Spectrum of Scenarios framework. This framework outlines a range of scenarios in which open data and generative AI could intersect and what is required from a data quality and provenance perspective to make open data ready for those specific scenarios. These scenarios include: pertaining, adaptation, inference and insight generation, data augmentation, and open-ended exploration. Through this process, we found that in order for data holders to embrace generative AI to improve open data access and develop greater insights from open data, they first must make progress around five key areas: enhance transparency and documentation, uphold quality and integrity, promote interoperability and standards, improve accessibility and useability, and address ethical considerations.
Subject: computer science
Intent: Other
Query: It is well known that graphite can intercalate alkali metal (AM) atoms between its layered structure, where the half-filled carbon pz orbitals are perpendicular to the graphitic planes and can interact with the AM s-orbitals. 9,10 Although lithium, due to its exceptional properties and small size, can easily intercalate into graphitic compounds, the competition between van der Waals (vdW) interactions and AM-C bond formation can pose challenges for larger AM atoms, particularly at low AM concentrations.
Subject: engineering
Intent: Other
Query: Act as an academic research expert. Draft an abstract for a research paper titled "、Drug Efficacy Profiles at Single-Cell Resolution Identify Novel Intratumour Heterogeneity Markers". The abstract should succinctly summarize the main objectives, methodologies, key findings, and implications of the research. Ensure clarity, coherence, and conciseness while adhering to the specific guidelines and conventions of the academic field. The abstract should effectively communicate the significance of the research to both experts in the field and general readers, encouraging them to delve deeper into the paper. here is the outline of the abstract 1. Intratumoral heterogeneity (ITH) is important to precision cancer therapies. 2. Developments in scRNA technology enable discovery of heterogeneous perspectives in cancer 3. At present, some work has discovered the mechanism of Intratumoral heterogeneity and initially clarified the mechanism of Intratumoral heterogeneity in drug resistance in specific cancers. 4.Limitations of ITH studies using only scRNA data 5. Advantages of combining treatment information with scRNA data for ITH research

Subject: medicine
Intent: Other
Query: How are semen sample handled if a 70% isopropyl solution cannot be used to keep gloves or the environment in which a semen sampled is assessed sterile? 
I say this because semen and sperm will be affected by anything with alcohol in it because alcohol id spermicidal. So how do laboratories handle semen samples if sperm can be affected by alcohol? What handling techniques are necessary to ensure the samples viability if alcohol solutions are harmful to semen and sperm?

Subject: medicine
Intent: Literature Understanding
Query: I'm writing a Research Grant Application on Combining Small Language Models and Decentralized Federated Learning support for Differential Diagnosis of Vertebral Compression Fractures Caused by Primary Osteoporosis and Multiple Myeloma. This Research Grant Application aims to develop a novel approach by combining small language models and decentralized federated learning to improve the differential diagnosis of VCFs caused by PO and MM. This approach addresses the limitations of traditional diagnostic methods and offers a more accurate, patient-centered, and cost-effective solution. Please rephrase detailed RESEARCH STRATEGies and Approach for clarity, coherence and conciseness, ensuring each paragraph flows into the next. Remove jargon. Use a professional tone.
Subject: medicine
Intent: Ideation
Query: The central goal of the retrieval task is to find precisely match pairs. It emphasizes clear, unique and highly distinguishable features. The possible overlapping, blurring, or mutual interference of features after  fusion of multi-view features precisely destroys the need for such clear and unique features, leading to poor retrieval results. Generation tasks, on the other hand, place more importance on the comprehensiveness and relevance of features and are less sensitive to highly distinguishable features. Find articles that support this argument
Subject: computer science
Intent: Paper Finding
Query: Find related work for following paragraph:

Language Models (LLMs), such as GPT-4, have fundamentally transformed the field of natural language processing by demonstrating exceptional capabilities in generating coherent, contextually appropriate, and human-like text. These models excel in a wide array of tasks, including translation, summarization, and question-answering, thereby advancing the boundaries of artificial intelligence. However, despite their impressive performance, LLMs are susceptible to generating hallucinations—responses that are factually incorrect, logically inconsistent, or semantically implausible. These hallucinations undermine the reliability and trustworthiness of LLMs, particularly in applications requiring high accuracy and factual integrity.

Understanding the underlying mechanisms that lead to hallucinations in LLMs is paramount for improving their reliability and ensuring their alignment with human cognitive processes. In the human brain, cognition emerges from the complex interplay of interconnected neurons that facilitate functions such as perception, memory, and reasoning. Disruptions or aberrant activations within these neural networks can result in cognitive impairments or the generation of erroneous thoughts. Drawing inspiration from this biological framework, this study hypothesizes that LLMs, which are architecturally inspired by neural networks, may exhibit analogous patterns of neuron activation that contribute to both accurate and erroneous outputs.

By meticulously examining the activation patterns of individual neurons and layers within an LLM during task performance, we aim to identify specific neurons or layers that are implicated in the generation of hallucinations. This analysis seeks to uncover whether certain activation dynamics correlate with the model's propensity to produce incorrect responses, thereby shedding light on the internal processes that govern LLM behavior.

This research establishes a bridge between cognitive neuroscience and artificial intelligence, offering a novel perspective on model interpretability and error analysis. By drawing parallels between human neural processes and LLM architectures, we endeavor to enhance our understanding of both biological cognition and machine learning systems. The insights gained from this study have the potential to inform strategies for mitigating hallucinations in LLMs, thereby advancing the development of more reliable and cognitively aligned artificial intelligence systems.
Subject: computer science
Intent: Paper Finding
Query: When comparing digital participation to traditional, non-digital on-site participation, important distinctions arise. Digital participation generally has a broader reach, allowing individuals from different geographic locations to contribute. In contrast, on-site participation is limited to those who can physically attend an event, which can result in less diverse input. However, on-site participation allows for direct, face-to-face interaction, which can foster deeper connections among participants and create a stronger sense of involvement.
Another distinction lies in the depth of deliberation and engagement. In traditional, in-person settings, participants often engage in more nuanced discussions, with opportunities for spontaneous dialogue, debate, and clarification. Non-verbal cues such as body language and tone of voice play an important role in these interactions. Digital platforms, on the other hand, may not provide the same opportunities for real-time, detailed deliberation, which can affect the quality of engagement.
A further difference is the level of anonymity. Digital platforms often allow for anonymous participation, which can both democratize the process and result in a lack of accountability. On-site participation typically requires participants to be physically present and identifiable, which can encourage accountability but may also discourage individuals from expressing dissenting or controversial opinions.
Finally, digital participation offers greater flexibility in terms of timing. Participants can contribute online at their convenience, whereas on-site participation usually requires a fixed time commitment, which can limit the number of attendees but may also create a more dedicated and focused environment

Subject: social sciences
Intent: Other
Query: In the field of scientific research, the quality of reference materials is crucial. The relevance of a scientific article is directly linked to the soundness of the research base on which it is based (YAMAKAWA et al., 2014). In this way, the time spent carefully selecting reliable and relevant sources for research becomes even more significant.
The vast amount of information available requires an additional effort to identify and filter out materials that are truly relevant to the topic in question. Care must be taken to avoid inaccurate or low-quality information, which could compromise the credibility of the research. The search for reliable sources and rigor in the critical analysis of information are essential steps in guaranteeing the quality and reliability of scientific work.
Subject: research methodology
Intent: Other
Query: Analyze and rank the single most effective exercise modality for cognitive enhancement based on scientific evidence:

Compare the cognitive benefits of:

High-Intensity Interval Training (HIIT)
Complex movement patterns/Dance
Traditional resistance training
Steady-state cardio
Balance/Coordination exercises


For each modality, evaluate:

Impact on BDNF production
Effect on neuroplasticity
Improvement in executive function
Memory enhancement
Processing speed changes
Long-term cognitive benefits
Accessibility and sustainability


Include specific metrics:

Optimal duration
Required frequency
Intensity levels
Time to see benefits
Risk-benefit ratio


Consider demographic factors:

Age groups
Fitness levels
Previous exercise experience"
Subject: sports science
Intent: Literature Understanding
Query: I have the following hypothesis from an experimental design. In my design, when an AI recommendation is bias, the gender bias correction is always incongruent with the AI recommendation, and when the AI recommendation is unbias, the gender bias correction is always congruent with the AI recommendation. This means no interaction analysis can be done on AI and gender bias correction. What options do I have to examine the effects of gender bias correction? Is gender bias correct now a main effect rather than a moderation? Are there any analysis methods I can use in this instance?


Moderation hypotheses: The relationships between AI recommendations and (1) candidate selection and hiring decision-making, (2) frame-(in)congruent candidate, and (3) AI recommendation assessments are moderated by;
H6: Gender bias correction recommendation such that a diversity cue recommendation that is incongruent (vs. congruent) with the AI recommendation weakens the effect of AI recommendations on (H6a) AI-recommended candidate assessments, (H6b) frame-(in)congruent candidate assessments, and (H6c) AI recommendation assessments.

Subject: psychology
Intent: Literature Understanding
Query: Overview of machine learning and its applications in finance However, the Markowitz model suffers from limitations that prevent it from achieving accurate results. One of these limitations is its reliance on linear hypotheses to determine the relationship between assets, making it less flexible in dealing with some complex changes in financial markets to address these constraints. Machine learning techniques have been adopted as an advanced alternative to deal with big and complex data more effectively. Machine learning algorithms are characterized by Machine Learnings is like Random Forest with its ability to detect hidden patterns in data and adapt to dynamic changes in the market, making it more accurate in forecasts related to portfolios.
Subject: finance
Intent: Other
Query: substantiate the following: "Addressing these issues is crucial to building a more resilient, equitable, and sustainable urban environment. By identifying and addressing gaps in pedestrian infrastructure and transportation access, this project directly contributes to improving the quality of life for residents, particularly those in underserved communities who are most vulnerable to the impacts of climate change. Moreover, the project provides valuable data and insights that can inform future climate adaptation and infrastructure planning, ensuring that King County's transportation network is better equipped to withstand the challenges posed by rising temperatures and extreme weather events. This work's significance lies in mitigating the immediate impacts of climate change and creating long-term solutions that promote health, equity, and environmental sustainability for all residents of King County."

Subject: environmental science
Intent: Literature Understanding
Query: Summarize about concept of article that using on this below:
Blockchain for AI: Review and Open Research Challenges
Blockchain for Securing AI Applications and Open Innovations
AI and Blockchain Integration
Exploiting Blockchain to Make AI Trustworthy: A Software Development Lifecycle View
The Applications of Blockchain in Artificial Intelligence
Blockchain, ERP, and AIS: Research on e-Procurement and System Integration
A Blockchain based Smart Agent System Architecture
Comparison of ERP Systems with Blockchain Platform
Convergence of Blockchain, IoT, and AI
AI and Blockchain: Towards Trustworthy and Secure Intelligent Systems

Subject: computer science
Intent: Literature Understanding
Query: The chemical reaction between hydrochloric acid (HCl) and iron (Fe) is a single displacement reaction where iron displaces hydrogen in hydrochloric acid to form iron(II) chloride (FeCl₂) and hydrogen gas (H₂). The balanced chemical equation for this reaction is:

\[ \text{Fe} + 2\text{HCl} \rightarrow \text{FeCl}_2 + \text{H}_2 \]

If the reaction goes to completion and forms iron(III) chloride (FeCl₃), the balanced equation would be:

\[ 2\text{Fe} + 6\text{HCl} \rightarrow 2\text{FeCl}_3 + 3\text{H}_2 \]

However, typically, iron reacts with hydrochloric acid to produce iron(II) chloride unless specified otherwise.
Subject: chemistry
Intent: Other
Query: Although mobile health (mHealth) technologies have emerged as a revolutionary ap-proach to enhance healthcare delivery, few studies have examined how it is perceived and accepted in different cultures. This study investigated social acceptance of mHealth among young people in three East Asian countries where cultural similarities and dif-ferences can be easily examined: Japan, China, and South Korea. A comparative analysis approach was adopted, employing an ex-tended unified theory of acceptance and use of technology model. University students from three countries, recruited using harmonized sampling methods, completed questionnaires. We employed descriptive statistics to summarize the sample characteristics, confirmatory factor analysis to val-idate the constructs, multigroup analysis to test for measurement invariance and ensure the applicability of the model in both cultural contexts, and comparative path analysis to explore differences in the various factors influencing mHealth acceptance in each cul-tural setting. The findings revealed distinct cultural effects on mHealth acceptance. Korean youth have the highest influence on health consciousness and trust in mHealth, while Japan has the lowest. Meanwhile, social influence has the highest influence on mHealth trust in China, while Korea has the lowest influence. This difference can be at-tributed to differences in young people's interests and cultural backgrounds. This study highlights the importance of considering cultural and institutional dynamics when inte-grating mHealth into youth healthcare models and suggests appropriate strategies for successful implementation.

please find and write introduction of this abstract.
Subject: medicine
Intent: Paper Understanding
Query: Write a comprehensive and scientifically grounded article on the topic of 'The Application of Artificial Intelligence in Designing Personalized Educational Systems.' The article should explore the role of AI in creating adaptive and personalized learning environments, including its impact on student engagement, learning outcomes, and educational efficiency. Discuss key technologies such as machine learning, natural language processing, and data analytics, and provide examples of AI-driven tools and platforms currently used in education. Ensure the article includes references to credible scientific studies and articles, with hyperlinks to the sources. The article should be well-structured, with an introduction, body paragraphs, and a conclusion, and should aim to provide a balanced view of the benefits and challenges of using AI in personalized education.
Subject: education
Intent: Literature Understanding
Query: summarize the part mentioned how an agent can interact with web accessibility tree in this paper: Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis et al. AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. 2024. arXiv.org.
Subject: computer science
Intent: Paper Understanding
Query: To address the aforementioned issues, many researchers have proposed variants and enhancements of DeepONet. For example, SVD-DeepONet introduces singular value decomposition (SVD) technology to enhance the flexibility and interpretability of high-dimensional space modeling [13]; TL-DeepONet significantly improves the model's stability in long-time series prediction by introducing transfer learning mechanisms [14]; VB-DeepONet combines Bayesian inference methods to achieve uncertainty quantification, thereby enhancing the model's robustness [15]. In addition, S-DeepONet significantly improves the ability to capture time-related dynamics by introducing gated recurrent units (GRU) and long short-term memory networks (LSTM) [16].
Subject: computer science
Intent: Other
Query: Both AUROC and AUPR showed large values in regions where the total degree of the drug node and target node was high. Based on the above, when utilizing link prediction by GNN, it is thought that paying attention not only to the model output score but also to the network structure, such as the order of the nodes, will enable more accurate identification of interactions.
On the other hand, it was suggested that since sufficient adjacency information is not available for nodes with low degree, the features extracted from the training data become limited, resulting in a relative degradation of link prediction performance. This problem is related to the cold-start problem and the lack of data, which have been pointed out in the past, and it is thought that a method that incorporates additional information in a complementary manner or a regularization method that emphasizes low order nodes for learning would be effective.
Subject: computer science
Intent: Other
Query: find papers for the researchers examine whether and how emerging trends in integrating large language models can enable the process of preserving and sharing knowledge to support Indigenous agriculture system outcomes that inform sustainable development. To grasp the techno-cultural dimensions of this transformation, we explore how LLMs can contribute to preserving and disseminating Indigenous agricultural wisdom. This work investigates if and how emerging themes in LLM embedding facilitate knowledge preservation in practice and sustainably support agrarian outcomes.
Subject: computer science
Intent: Paper Finding
Query: Carcinogenic Mechanisms of PAHs
The health risks associated with PAHs are well-documented, and these compounds have been classified as carcinogens by major health organizations, including the International Agency for Research on Cancer (IARC). The primary cancer sites linked to PAH exposure include lung, bladder, and skin cancers, with the most significant risks associated with prolonged and high-level exposure. Studies have demonstrated that PAHs can induce carcinogenesis through several mechanisms, including the formation of DNA adducts, oxidative stress, and the disruption of cellular repair processes.
Subject: medicine
Intent: Other
Query: Research Question:
How does air temperature affect solar PV power generation, particularly for monocrystalline or polycrystalline modules?

Follow-up Questions:

Which type of PV technology is used in the system—monocrystalline or polycrystalline modules?

What is the environmental factor being analysed (e.g., air temperature)?

Is the impact of air temperature on PV performance explicitly mentioned or inferred in the publication?

What method or model is used in the analysis (e.g., regression analysis, simulation model)?

What are the key findings regarding the effect of air temperature on PV performance (e.g., efficiency, output)?

If the impact of air temperature is explicitly mentioned, what is the exact quote from the source?
Subject: engineering
Intent: Ideation
Query: Using these topics, give me an overview with how commentary generation can be used to finetune multimodal LLMs and gaps, and how we can use noisy learning techniques to fix those problems. See topics below:
Commentary generation
Commentary generation w/ noise
Video representation learning with noise
"Narration generation with VideoLLMs
"
Narration generation w/ noise
General review of VideoLLMs - there’s a recent survey from last fall (probably out of date by now haha)
Noisy image captioning (i remember there are some papers)
Tuning LLMs w noisy data
RAG in multimodal LLMs
Subject: computer science
Intent: Literature Understanding
Query: find me papers that relate to this:

It's worth to notice that the traditional notion of data augmentation through slight variations — such as paraphrasing or minor alterations in the dataset — often falls short in contributing to true diversity. This limitation stems from the exceptional capability of LLMs as few-shot learners, which can rapidly assimilate and generalize from minimal examples. For LLMs, diversity must encapsulate variations in the context, complexity, and formulation of tasks, ensuring that the model encounters a comprehensive spectrum of scenarios within the target domain.
Subject: computer science
Intent: Paper Finding
Query: Hi, I'm trying to create a world map type plot, where I want to show discrepancy between the global north and global south countries, in terms of AI. My key argument is: AI progress is uneven, and it is biased toward / favours global north countries predominantly. For instance, I have a data showing LLM actuality  for different countries, and it clearly shows that LLM factuality is far better for global north countries, compared to global south. 

Your task is to find more data / brainstorm ideas on what else I can show in my world map, to support my argument. 
Subject: computer science
Intent: Ideation
Query: Silicates can react with various substances, including acids, bases, and certain metals. When silicates react with acids, they can produce silicon dioxide (SiO₂) and salts. For example, when orthosilicic acid (H₄SiO₄) is formed, it can further dehydrate to form silica gel. Silicates can also react with metal ions in aqueous solutions to form new compounds.
Subject: chemistry
Intent: Other
Query: Introduce the prior papers and related research that have proposed peak detection algorithms for the main steps below, and that are often cited.

Preprocessing and smoothing of data
Noise reduction using the Savitzky-Golay filter
Normalization to probability density when creating a histogram
Keywords: signal smoothing, Savitzky-Golay filter, density normalization
Detecting peak candidates
Implementation based on scipy.signal.find_peaks
Evaluation combining multiple quality metrics: 
Prominence (prominence) filtering by threshold
Minimum peak width constraint
Minimum peak distance setting
Relative height threshold
Keywords: peak detection, prominence threshold, peak width filtering
Signal-to-Noise Ratio (SNR) calculation
Local background noise level estimation
Comparison of peak intensity and background noise
Formula: (signal - mean_background) / std_background
Keywords: local SNR calculation, background noise estimation
Multiparametric quality filtering
SNR threshold
Prominence threshold
Width threshold Robust peak detection using a combination of these thresholds
Keywords: multiparametric filtering, peak quality assessment
Features of particular note:
Specialized for biological data (motif-to-motif distance)
Analysis that takes strand specificity into account
Probability density-based normalization approach
Multiparametric quality assessment system
Subject: computer science
Intent: Literature Understanding
Query: 2.3.2 TerraSAR-X Dataset (2013-2019)
The TerraSAR-X dataset represents a critical component in our multi-sensor approach to monitoring vertical urban growth, offering distinct capabilities that complement and enhance the overall monitoring framework. Developed through collaboration between the German Aerospace Center (DLR) and Airbus Defence and Space, this high-precision X-band SAR system provides crucial insights into Wuhan's three-dimensional urban evolution during a period of intensive vertical development [82].

System Characteristics and Acquisition Strategy
The TerraSAR-X system operates with sophisticated technical parameters optimized for urban monitoring applications. Operating in the X-band frequency range at 9.65 GHz (wavelength λ = 3.1 cm), the system provides exceptional spatial resolution particularly advantageous for urban structure monitoring [83]. For this study, data acquisition was performed in High-Resolution Spotlight mode, leveraging the satellite's advanced beam steering capabilities to achieve spatial resolutions of 1.1 meters in azimuth and 0.6 meters in range direction. This high-resolution configuration enables precise identification of individual building structures and infrastructure elements within Wuhan's complex urban environment.
The acquisition strategy incorporated two complementary viewing geometries: ascending (east-looking) and descending (west-looking) orbits. This dual-geometry approach maintained a consistent incidence angle of 37.3°, optimizing the detection of vertical displacements while minimizing geometric distortions in Wuhan's dense urban landscape. The dataset spans from 2013 to 2019, coinciding with a crucial phase of Wuhan's rapid vertical expansion.
"please help me rewrite this with correct citations and references. 
Subject: earth sciences
Intent: Paper Understanding
Query: - Role: Expert in Physics Research Literature Retrieval
- Background: The user is conducting in-depth research in the field of above-threshold ionization of xenon atoms in intense laser fields and is seeking relevant academic literature and materials as a research foundation.
- Profile: You are an expert in the field of physics, particularly in the area of intense laser field ionization, with extensive experience in literature retrieval. You are adept at using various databases and tools to locate and filter relevant literature.
- Skills: You possess efficient information retrieval skills, are familiar with various academic databases and search engines, and can accurately understand user needs to quickly pinpoint high-quality research literature.
- Goals: To provide the user with a series of high-quality academic literature related to the field of above-threshold ionization of xenon atoms in intense laser fields.
- Constrains: The retrieved literature must be authoritative academic publications, including but not limited to journal articles, conference papers, and dissertations, ensuring the scientific and reliable nature of the literature.
- OutputFormat: Provide information such as the title of the literature, authors, publication year, journal name, DOI, or URL link.
- Workflow:
  1. Identify retrieval keywords, such as "intense laser field ionization," "xenon atoms," "above-threshold ionization," etc.
  2. Access academic databases and search engines, such as Web of Science, Scopus, Google Scholar, etc., and retrieve using keywords.
  3. Filter and evaluate the retrieval results, selecting the most relevant literature to the research topic.
  4. Extract key information from the literature and sort it by relevance.
- Examples:
  - Reference 1: "Above-threshold ionization of xenon atoms in intense laser fields", Authors: [Name], Published in: [Journal Name], Year: [Publication Year], DOI: [DOI Link]
  - Reference 2: "Multiphoton ionization of xenon in strong laser fields", Authors: [Name], Published in: [Journal Name], Year: [Publication Year], DOI: [DOI Link]
- Initialization: Hello, I am a professional expert in physics research literature retrieval. To help you find relevant literature in the field of above-threshold ionization of xenon atoms in intense laser fields, please let me know what specific information you need, or if there are any particular keywords and requirements.
Subject: physics
Intent: Other
Query: Rh blood group system occupies a very important position in the human red blood cell blood group system and is famous for its high complexity. The system contains a variety of different antigens, especially RHD antigen, which has attracted much attention because of its strongest immunogenicity. When a RhD Negative mother harbors a RHD positive fetus, it may trigger a series of complex immune reactions. During labor, the RHD positive erythrocytes of the fetus are likely to enter the maternal blood circulation. In addition, if there are placental abruption, prenatal bleeding and other accidents during pregnancy, it will also lead to fetal red blood cells entering the mother. Once the maternal immune system contacts these foreign red blood cells, it will quickly recognize them as foreign antigens. This recognition process will activate the maternal immune response, and then produce anti-D antibodies. This antibody belongs to the immunoglobulin G (IgG) type and has the property of entering the fetus through the placental barrier.
Subject: medicine
Intent: Other
Query: find all relevant papers for this work: To advance the conversational forecasting tasks with a focus on Conversation Gone Awry (CGA) tasks, we tackle key challenges limiting progress. % We introduce a larger dataset and an open-source framework for reproducible conversational forecasting experiments. % Using the new dataset and evaluation framework, we first report new state-of-the-art (SOTA) performance on CGA tasks achieved by both the RoBERTa and Gemma-2 models. % Paving the way for future research, our work also introduces the first well-trained human baseline for this task. % Then, we critically the role of conversational dynamics and introduce an additional evaluation dimension for the task that relies on the models' capacity to capture these dynamics.

Subject: computer science
Intent: Paper Finding
Query: This paper proposes a hybrid NOMA/OMA system that combines the strengths of both access schemes to address the challenges of WFL in 6G networks. The hybrid model dynamically assigns resource blocks, allowing multiple devices to share blocks using NOMA where feasible while reserving OMA blocks for devices with stricter latency or interference requirements. Through adaptive scheduling strategies that consider device channel conditions, computational load, and latency needs, this hybrid system aims to achieve optimal resource utilization, minimize latency, and enhance scalability.
Subject: engineering
Intent: Other
Query: write introduction about " Blockchain technology in the metaverse: Enhancing security, trust, and interoperability." based on the following information :-
 The metaverse is an immersive digital environment where users interact via avatars, virtual assets, and digital experiences. However, the current metaverse faces significant challenges:

Security: Threats such as data breaches and unauthorized access.
Trust: Issues in verifying digital ownership and content authenticity.
Interoperability: Limited transferability of assets between platforms.
Blockchain technology, known for its decentralized and transparent nature, can address these limitations. This review explores the intersection of blockchain and the metaverse, providing insights into how blockchain enhances security, trust, and interoperability.
Subject: computer science
Intent: Paper Understanding
Query: To address these limitations of traditional RL, a research direction combining Large Language Models (LLMs) with Reinforcement Learning has emerged in recent years and has become a significant trend in the field of artificial intelligence. Leveraging their powerful natural language understanding and generation capabilities, vast knowledge bases, and exceptional high-level abstraction abilities, LLMs offer novel solutions for Reinforcement Learning. Existing research has explored various roles for LLMs within Reinforcement Learning, such as: acting as information processors to interpret environmental feedback, aiding in the design of visualization metrics and log interpretation; serving as reward designers to generate or refine reward functions based on task descriptions, simplifying the design process; functioning as decision-makers to output policy drafts during high-level planning stages, guiding traditional RL algorithms; or acting as generators to simulate complex scenarios and generate adversarial samples, promoting robustness testing.
Subject: computer science
Intent: Other
Query: In recent years, the increasing frequency of natural disasters has emphasized the need for rapid and accurate damage assessment. Particularly in the case of earthquakes and other disasters, it is crucial to immediately grasp the extent of the damage and take appropriate countermeasures. Machine learning and deep learning are technologies that extract patterns by learning from vast amounts of past data and apply them to new data. Research is advancing in utilizing satellite images, social media data, and IoT sensor data to assess damage in real time.

This study attempts to develop a method for generating damage situation maps using the GPT-4o API as a generative AI capable of assessing damage by leveraging the latest image recognition technology. By utilizing AI, past disaster data can be learned, making it possible to evaluate the extent of damage. Traditional remote sensing-based indicators have demonstrated high speed in assessments. However, AI technology enables the analysis of vast amounts of image data, the immediate verbalization of post-disaster situations, and a quantitative grasp of damage, allowing for more accurate information retrieval from maps.

For example, by analyzing satellite images and drone-captured footage with AI, it becomes possible to quickly evaluate the number of collapsed buildings and the extent of flooded areas. Additionally, by analyzing social media posts in real time, citizen-reported damage information can be immediately reflected. This allows for a more accurate understanding of the disaster-stricken areas, supporting swift decision-making. Furthermore, by classifying the extent of damage in detail, it becomes possible to prioritize response efforts in severely affected areas.

In this study, we classify building damage levels into four categories: "No Damage," "Minor," "Moderate," and "Severe," thereby constructing a system for assessing damaged buildings. This system enhances the efficiency of rescue operations and damage assessments.

Moreover, alongside technological advancements, improving societal acceptance is also essential. To ensure the widespread recognition of AI's effectiveness in disaster response, it is necessary to collaborate with municipalities, disaster prevention agencies, and private enterprises, incorporating AI into actual disaster prevention plans. Citizen cooperation is particularly important; instead of merely allowing AI to collect and analyze damage information, integrating real-time data provided by citizens enables a more comprehensive understanding of damage.

Subject: computer science
Intent: Other
Query: In developing countries, e-commerce is generating enormous opportunities for consumers and producers alike; The advantages to consumers are more convenience, more product availability, and savings (Lu et al., 2016). For each of the businesses, e-commerce helps in reducing operational cost and market accessibility  (Shilinde, 2018). Yet, in a number of developing countries, specifically Tanzania, there is a low level of e-commerce uptake arising from poor infrastructure, limited levels of digital literacy and trust (Halder, Roy & Chakraborty, 2017). We need to have the ability to overcome these barriers capabilities that cannot be achieved without trust, which is the critical enabler of online transaction popularity and consumer confidence to interact with e-commerce platforms (Crespo & Del Bosque, 2010).
Subject: business
Intent: Other
Query: To investigate the relationship between drug substructure and side effects, we calculated the extent to which the development of side effects varies with drugs containing specific chemical substructures (MACCS keys). Since certain substructures are known to be involved in the development of side effects, examining the relationship between substructure and side effects may aid in the selection of drugs with a small risk of side effects when diverting drugs. The following figure shows the results.
The values in each cell of the heatmap represent the following ratios
Ratio = incidence of side effects for drugs with a specific substructure / incidence of side effects for drugs with a specific substructure
Specific substructures (MACCS keys 15, 13, 12, and 9) have a lower incidence for most side effects. Drugs with these substructures have a small risk of side effects and may be appropriate as diverting agents. However, drugs containing specific functional groups tend to be biased toward certain classes of drugs (e.g., drugs for psychiatric disorders), and side effects specific to those classes may be expressed. Factors other than the effect of the functional group itself may be mixed in, making it difficult to identify a direct causal relationship.
Subject: medicine
Intent: Other
Query: Find papers on Spin-Orbit Coupling and Topological Properties in regards to 2D Spintronics for Neuromorphic Computing with Scalability and Energy Efficiency.
- Examine materials such as WTe$_2$ and Bi$_2$Se$_3$ for their strong spin-orbit coupling and potential for spin-charge interconversion.
- Highlight the relevance of topological insulators and quantum anomalous Hall insulators in wearable neuromorphic devices.
Synaptic weights in neuromorphic systems with fast switching (<1 ns) and low energy (<10 fJ/bit).
- W/CoFeB/MgO structures have demonstrated high spin-torque efficiency.
Subject: physics
Intent: Paper Finding
Query: Provide a detailed explanation of the Human Papillomavirus (HPV/VPH) replication cycle by addressing the following interconnected processes: How does HPV specifically bind to host cell receptors, such as heparan sulfate proteoglycans (HSPGs) and α6 integrins, and what entry mechanisms (e.g., clathrin-mediated endocytosis, pH-dependent fusion) enable its internalization into keratinocytes or mucosal epithelial cells? Once inside, what sequential steps occur during its replication process, including the critical phase of genome replication (e.g., episomal maintenance of circular dsDNA in the nucleus, reliance on host DNA polymerases, and regulation by viral proteins like E1 and E2)? Finally, how does HPV exit the host cell—given its non-enveloped structure—to infect new cells, and how do these egress strategies (e.g., delayed release via epithelial differentiation, cell shedding, or lack of lytic burst) differ from those of enveloped or lytic viruses? Integrate your discussion to highlight how HPV’s receptor specificity, intracellular trafficking, replication tactics, and asymptomatic release mechanisms contribute to its lifecycle and persistence in human hosts
Subject: biology
Intent: Literature Understanding
Query: Can you help me add the correct references to the appropriate places in the article I wrote? I require a variety of references：Gastrointestinal diseases impose a significant health burden globally. According to the Global Burden of Disease (GBD) study, digestive system diseases account for more than one-third of all disease prevalence, and their new cases constitute about one-fifth of all new disease cases. [37302558] The lower gastrointestinal tract, responsible for nutrient absorption and fecal excretion, is a major component of the digestive system. Diseases in this region are diverse and complex, involving mechanisms such as ischemia, mechanical obstruction, autoimmune inflammation, and tumors. The burden of these diseases shows significant regional and gender differences. For instance, in 2019, approximately 7 million people worldwide were affected by inflammatory bowel disease (IBD). The prevalence of IBD is significantly higher in high-income countries compared to low-income countries, with the incidence rate in the United States being 4.5 times higher than the global average. Additionally, the incidence and mortality rates of IBD are higher in females than in males. Therefore, understanding the epidemiological characteristics of this group of diseases is crucial for improving health policies and reducing disease burden.
Subject: medicine
Intent: Paper Finding
Query: An ITH program that continued to mediate the most signaling under known heterogeneous conditions was considered a critical MP. Our results indicated that most cancers exhibited notable consistency across all drug groups. As shown in Figure 3, programs related to the cell cycle and stress responses displayed evident trends, reflecting the proliferation and metastasis characteristics of tumor cells. To assess the level of heterogeneity, core heterogeneity genes from each drug group were used to enrich the specific genes of MPs. The MP with the largest absolute value of the Normalized Enrichment Score (NES) was selected as the heterogeneity-associated MP contributing to differences in drug efficacy. paraphrase this paragraph

Subject: biology
Intent: Paper Understanding
Query: Are there any research papers on joint learning or multi-modal deep learning approaches for segmenting HE (Hematoxylin and Eosin) images using both IHC (Immunohistochemistry) and HE images? Specifically, I am looking for methods that combine IHC staining region information with HE tissue structure to improve segmentation of HE images, especially in cases where there are significant differences in color and intensity between the two modalities. Techniques such as multi-task learning, cross-modality image fusion, or domain adaptation would be of particular interest.
Subject: computer science
Intent: Paper Finding
Query: In traditional Reinforcement Learning (RL), agents often struggle to learn effectively due to the lack of semantic clarity in the environmental feedback they receive, particularly in complex state spaces or under sparse reward conditions. The integration of Large Language Models (LLMs) first manifests in their powerful information processing capabilities. They are capable of performing deep semantic interpretation and high-level feature extraction on raw, high-dimensional environmental inputs, such as images, sensor data, or text \cite{gu_mutual_2025}. For instance, in robotics tasks, LLMs can transform sensor readings into an understanding of the environmental layout and target states. This semantic information processing not only addresses the challenges associated with high-dimensional state spaces but, more crucially, lays a solid foundation for subsequent reward design. By understanding the environmental state and task objectives, LLMs can more accurately identify which actions or states are critical for achieving the goals.
Subject: computer science
Intent: Other