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Skyscanner
A comprehensive flight search engine that scans for prices on hundreds of travel sites in seconds and provides the best deals.
Google Flights
Offers a user-friendly interface to compare prices for multiple destinations and find low fares.
Holiday Pirates
Specializes in finding flight deals within Europe, catering to budget-conscious travelers[2].
Going (formerly Scott’s Cheap Flights)
Sends alerts on upcoming flight deals, primarily for US flights, to help travelers find the best deals[2].
Google Flights Explore Tool
Allows users to search for flights by entering their home airport and finding deals to various destinations on a map[2].
Student Universe
A travel agency that offers discounts for students, helping them secure cheaper airfare[2].
Flight Centre
A travel agency that assists in finding budget-friendly flight options for various routes[2].
Budget Airlines
Various carriers that may provide cheaper prices for specific routes, primarily regional travel, but often come with additional fees[2].
Travel Credit Cards
Allows users to accumulate points and miles for free flights and travel perks through credit card use[2].
Last-Minute Deal Websites
Provide access to special promotions and discounts on flights that can be used for spontaneous travel plans[2].
Flexible Date Searches
Suggests searching for flights on different dates to find lower fares, as prices can vary significantly based on timing[2].
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A healthy work-life balance is the ability to effectively manage both professional and personal responsibilities without one overwhelming the other. It is generally characterized by a sense of fulfillment and contentment in both areas of life, allowing individuals to meet work deadlines while still having time for personal relationships, hobbies, and self-care[1][2].
Signs of a healthy work-life balance include not feeling constant conflict between work obligations and personal responsibilities, meeting deadlines without overtime, getting adequate sleep, maintaining a balanced diet, and having time for leisure and family[2]. Additionally, a balanced life allows for flexibility, where individuals can integrate personal tasks into their work schedule without feeling guilty[4].
Achieving this balance requires awareness of one's feelings and priorities, as well as the ability to set boundaries around work commitments[5][6]. Regular reflection on one's situation and ongoing adjustments are crucial, as needs and circumstances change over time[3][6]. Ultimately, a healthy work-life balance is about finding harmony that fits individual goals and priorities, recognizing that both work and personal life can coexist supportively[2][4].
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Different soil types support various plants based on their characteristics. For instance, loamy soil, which is a balanced mix of sand, silt, and clay, is ideal for a wide range of plants due to its excellent drainage and nutrient retention[1]. Sandy soil is suitable for drought-tolerant plants like lavender and carrots, while clay soil can be productive for plants such as hostas and irises, but these require modifications for drainage[2][3].
Chalky soils are alkaline, favoring plants like lilacs and coneflowers, while peaty soils benefit acid-loving plants like rhododendrons and blueberries[2][6]. Silty soils are nutrient-rich and suitable for moisture-loving plants such as willows and birches[3][5].
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ASMR roleplay videos are a subcategory of ASMR content where the creator, often referred to as an 'ASMRtist,' simulates providing personal attention to the viewer. These videos typically involve the ASMRtist acting directly to the camera as if the viewer were the recipient of a simulated service, such as having their hair styled, makeup applied, or undergoing a medical examination. Many viewers report that watching such simulations triggers the ASMR sensation, which is characterized by a pleasurable tingling feeling often accompanied by relaxation and sleepiness[1].
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Over the long term, we believe earnings are likely to prevail, or else why would we buy these securities
Warren Buffett[1]
Our calculations exclude capital gains and losses, realized or unrealized, on the stocks and bonds we hold
Warren Buffett[1]
If we change our minds, we will modify the contracts we offer
Warren Buffett[1]
Properly pricing P/C insurance is both an art and a science and is definitely not a business for optimists
Warren Buffett[1]
We can’t buy or sell stocks easily. Sometimes it takes a year or more to build or divest an investment
Warren Buffett[1]
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Introduction to mR2AG
In the ever-evolving field of Artificial Intelligence, particularly in multimodal understanding, the challenge of effectively integrating visual and textual knowledge has gained significant attention. Traditional Multimodal Large Language Models (MLLMs) like GPT-4 have shown prowess in visual question answering (VQA) tasks; however, they often falter when confronted with Knowledge-based VQA tasks, such as INFOSEEK and Encyclopedic-VQA. These tasks require the models to provide specific and accurate answers based on external information rather than relying solely on their pre-existing knowledge base.
To address these limitations, the mR2AG framework—short for Multimodal Retrieval-Reflection-Augmented Generation—has been developed. This innovative approach combines retrieval mechanisms with reflective processes to enhance the performance of MLLMs in answering knowledge-based questions accurately and efficiently.
Overview of mR2AG
mR2AG introduces two critical reflection operations: Retrieval-Reflection and Relevance-Reflection. Retrieval-Reflection determines whether the user query is Knowledge-based or Visual-dependent, thereby deciding the necessity of information retrieval. This adaptive retrieval process helps avoid the unnecessary complexity of retrieving information when it’s not needed, ultimately streamlining the question-answering process.
The second reflection operation, Relevance-Reflection, plays a crucial role in identifying specific pieces of evidence from the retrieved content that are beneficial for answering the query. This allows the MLLM to generate answers rooted in accurate and relevant information rather than vague generalities, which is often a problem with current models.
As described in the paper, mR2AG “achieves adaptive retrieval and useful information localization to enable answers through two easy-to-implement reflection operations, preventing high model complexity”[1]. This efficiency is vital for maintaining the MLLMs' original performance across a variety of tasks, especially in Visual-dependent scenarios.
Performance and Results
The mR2AG framework has demonstrated significant improvements over prior models in handling knowledge-based queries. Comprehensive evaluations on datasets such as INFOSEEK reveal that mR2AG outperforms existing MLLMs by notable margins. Specifically, when using LLaVA-v1.5-7B as the basis for MLLM, applying mR2AG leads to performance gains of 10.6% and 15.5% on the INFOSEEK Human and Wikidata test sets, respectively, while also excelling in the Encycopedic-VQA challenge[1].
One of the compelling aspects of mR2AG is its ability to refine its outputs based on the relevance of retrieved information. The results indicate that by effectively evaluating retrieval content, mR2AG can identify and utilize evidence passages, resulting in more reliable answer generation. “Our method can effectively utilize noisy retrieval content, accurately pinpoint the relevant information, and extract the knowledge needed to answer the questions”[1].
Moreover, mR2AG does not merely improve knowledge-based questioning; it preserves the foundational capabilities of the underlying MLLMs to handle Visual-dependent tasks with similar finesse. This balance between specialized retrieval and generalizeable knowledge is a hallmark of mR2AG's design.
Methodology
The success of mR2AG hinges on its structured methodology. Initially, user queries are classified by type—either Visual-dependent or Knowledge-based. The MLLM generates retrieval-reflection predictions to decide whether external knowledge is necessary. If the model predicts that retrieval is required, it selects relevant articles from a knowledge base, focusing on Wikipedia entries, which are rich in information[1].
Once the relevant documents are retrieved, the model employs Relevance-Reflection to assess each passage's potential as evidence for the query. Each passage undergoes evaluation to determine its relevance, allowing the model to generate answers based on identified supportive content. This layered approach—first distinguishing the need for external information, then pinpointing the most pertinent evidence—significantly enhances the accuracy of responses.
The mR2AG framework also introduces an instruction tuning dataset (mR2AG-IT) specifically designed for Knowledge-based VQA tasks, which aids in the model's adaptability through a structured training process[1].
Conclusion
The mR2AG framework represents a significant advancement in the domain of knowledge-based visual question answering within AI. By integrating adaptive retrieval with precise evidence identification, mR2AG not only enhances the accuracy of answers but also streamlines the complexity typically associated with multimodal models. Its robust performance across various benchmarks demonstrates its effectiveness in tackling challenging knowledge-centric tasks while maintaining the versatility required for visual understanding.
As the AI landscape continues to evolve, frameworks like mR2AG underline the potential for models that can both comprehend intricate visual data and harness external knowledge bases efficiently, setting a foundation for future advancements in multimodal AI systems.
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People enjoy cleaning videos for several psychological reasons. These videos often provide a sense of control and order in chaotic times, particularly during and after the pandemic, when many sought comfort in tidiness while feeling overwhelmed by life's unpredictability[2][4][5]. The transformation from dirty to clean, combined with calming sounds, also triggers feelings similar to ASMR, offering viewers a soothing experience[1][3][6].
Moreover, cleaning content serves as a form of 'behavioral activation,' a therapeutic technique that can improve symptoms of depression by promoting small, manageable tasks that build momentum and confidence[4][5]. This aspirational content not only entertains but can also foster emotional well-being[2][5].
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Company culture plays a critical role in employee retention by influencing job satisfaction and engagement. A strong corporate culture fosters a sense of belonging and connection among employees, making them more likely to stay with the organization. When employees feel valued and part of a cohesive team, their loyalty increases, thereby reducing turnover rates[4][5].
Moreover, a positive culture encourages open communication, provides career development opportunities, and promotes work-life balance, all of which contribute to higher employee satisfaction[1][3][5]. In environments where employees connect with the company’s mission and values, they are more invested in their work and committed to the organization’s success[2][3][4].
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Collins Wild Flower Guide
Covers over 1,900 species of wildflowers, trees, shrubs, grasses, and ferns in Britain and Ireland, organized by families with detailed illustrations and descriptions[5].
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The Wild Flower Key
Provides identification for wild plants, trees, and shrubs in Britain and Ireland, suitable for both beginners and experienced botanists with detailed descriptions and illustrations[4][10].
Collins Complete Guide - British Wild Flowers
Features over 1,000 common species with concise descriptions, excellent photographs, and habitat information, ideal for foraging and field use[4][7].
Newcomb’s Wildflower Guide
A comprehensive guide based on natural structural features that makes identification straightforward, suitable for beginners and experienced nature enthusiasts alike[6][8].
The Little Book Of Wild Flowers
A child-friendly guide focusing on striking images, aimed at young wildflower enthusiasts and packed with basic identification tips[2].
Flora Britannica by Richard Mabey
A blend of cultural and botanical insights, featuring nearly 500 photographs and over 1,000 species, highlighting the connection between wild plants and social life[2].
Wild Flowers of Britain Month by Month
Features beautifully painted illustrations and tracks blooming species by month, making it a thoughtful gift for botanical art lovers[2].
Wonderful Wildflowers of Wales
Focuses on Welsh wildflowers with a chart for quick identification by color and detailed habitat information[2].
Harrap’s Wild Flowers
A photographic guide that describes and illustrates over 1,225 wildflowers, shrubs, and trees in the British Isles with practical identification tips[7][10].
Guide to Flowers of Walks and Waysides
A lightweight and portable laminate leaflet that includes essential wildflower information for walks in the countryside and urban areas[2].
Wildflowers by Colour
Organizes species primarily by flower color for quick identification, recommended for users without extensive botanical knowledge[2].
The Easy Way to Wildflower Recognition
Utilizes a simple yes/no key to identify approximately 200 common wildflowers in Britain and Ireland, ideal for beginners[5].
/types-of-wildflowers-4061772-hero-4f093bf89ec94cd9ac766a4e0465238d.jpg "Wildflowers in the Field and Forest")
Wildflowers in the Field and Forest
A field guide covering over 1,400 species of herbaceous wildflowers with excellent color photographs and range maps[8].
Flowering Plants of the World
A general guide that covers a significant number of flowering species, illustrated with photographs and concise descriptions, useful for amateur botanists[5].
Edible Wild Plants
A field guide detailing over 370 edible plants, including visual aids for identification and preparation techniques[8].
Field Guide to Medicinal Plants & Herbs of Eastern & Central N. America
Provides identification for over 530 medicinal plants, highlighting their uses and habitat[8].
Botany in a Day
Employs a pattern method to teach users how to identify plants quickly and easily, suitable for beginners wanting a simplified approach[8].
The Wildflower Field Guide
Covers approximately 1,100 wildflower species in Britain including key features for identification, suitable for both beginners and experienced users[5][10].
Peterson Field Guide to Wildflowers
Features more than 1,200 species with detailed descriptions, useful for beginners and experts in North America[8].
Wild Edible Plants of North America
Classifies and describes over 200 edible plants, organized by season, with identification help and preparation guidance[8].
Collins Wildflower Guide (2nd Edition)
Detailed descriptions and illustrations of 1,900 wildflowers with identification keys, suitable for more experienced botanists[5][10].
Urban Wildflowers
Identifies wildflowers typically found in urban settings, contributing to the identification in city environments[2].
Pocket Guide to British Wildflowers
A compact guide for on-the-go identification of common British wildflowers, featuring photographs and clear descriptions[2].
Nature’s Almanac
A seasonal guide to local wildflowers and their habitats, aimed at enhancing the user’s understanding of plant ecology[8].
Discovering British Wildflowers
Aimed at beginners, this guide simplifies the identification process with clear visuals and straightforward instructions[10].
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Based on the IRS[1] guidance in Notice 2023-63, software development costs[1] can be capitalized and amortized under Section 174[1], rather than being expensed. For tax years beginning after 2021[2], amended Sec. 174 requires capitalization[2] and amortization of software development costs, with recovery through amortization over a specified period. The specific amortization period for software development costs under amended Sec. 174 is not provided in the given text. Additionally, the Tax Cuts and Jobs Act[1] now requires mandatory capitalization of software development costs. Certain costs related to the development of new software programs[4] and enhancements to existing software[4] are required to be capitalized under Section[1] 174, but costs incurred after the software is ready for sale or license to others[4], such as marketing, distribution, or customer support, are not required to be capitalized under Section 174.
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