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The EPPO Bulletin's "Annual Report and Council Recommendations 2023" provides an overview of EPPO's activities, including workshops, database development, and discussions on plant health. The report emphasizes the organization's focus on plant health for food security and human welfare, detailing efforts in plant protection products, diagnostics, phytosanitary risks, and communication. The Minor Uses Coordination Facility (MUCF) works to enhance sustainable crop protection solutions within an Integrated Pest Management (IPM) framework, funded by European countries and facilitating collaboration between stakeholders. The MUCF hosts expert groups, establishes working groups, and shares information on minor crop status and residue extrapolation possibilities, collaborating with EPPO and other organizations to contribute to OECD guidance documents. [Extracted from the article]

The article "Traces of Contact in the Lexicon: Austronesian and Papuan Studies" edited by Marian Klamer and Francesca R. Moro explores the historical and linguistic interactions between Austronesian and Papuan languages in the regions of Indonesia and the Philippines. The volume focuses on the lexical effects of contact, presenting detailed studies on ancient and modern contact scenarios, as well as the borrowing of words between different language families. The chapters offer valuable insights into the complexities of language contact, historical trajectories, and cultural exchanges in the region, making it a significant resource for scholars interested in the linguistic diversity of eastern Indonesia. [Extracted from the article]

ABSTRACT Digital textbooks (DTs) have evolved from DT 1.0, which simply converted paper textbooks to PDF format, to DT 2.0, which provides various multimedia content, for example, video and audio content. DTs have now advanced to DT 3.0, which enhances learner engagement through gamification and simulations. Recently, with the advancement of cloud computing technology and digital devices, for example, tablets, DT 4.0, which supports personalised learning through artificial intelligence (AI) tutors and chatbots, has been realised. South Korea is actively implementing a policy to distribute artificial intelligence–based DTs, equivalent to DT 4.0, to all schools under national leadership. For artificial intelligence–based DTs (AIDTs) in South Korea to develop into a sustainable education system, reliance on cloud computing alone is insufficient. It is also necessary to build layers of fog computing and edge computing from the initial stage. There are concerns that AIDTs may exacerbate the learning gap because they are more likely to be utilised actively by high‐performing students with established self‐directed learning habits rather than struggling students. Thus, it is essential to enhance usage monitoring and explore strategies that provide educational scaffolding to prevent differences in the level of AIDT utilisation from leading to a widening learning gap. [ABSTRACT FROM AUTHOR]

The document is a review of the new product, Mergent Market Atlas, within the Mergent Lineage. It compares Market Atlas to other Mergent products like Mergent Online and Intellect, highlighting differences in data coverage and functionality. The review discusses Market Atlas's features, such as company research, industry classifications, and sustainability ratings, as well as its limitations compared to other financial information services platforms like FactSet and Bloomberg. Pricing information and conclusions about Market Atlas's intended audience are also provided. [Extracted from the article]

The "Changing values and the writing of history" article reviews the United States Foreign Policy History & Resource Guide, a website offering a comprehensive history of US foreign policy from the War of 1812 to the "War on Terror." The Guide features essays by multiple authors, is ad-free, and provides downloadable PDFs for offline use. While the Guide is praised for its accessibility, accuracy, and rich content, some critiques include potential bias in its recommendations and a lack of in-depth exploration of concepts like imperialism. The article also highlights the Guide's detailed analysis of the "war on terror" section, which provides a thorough and balanced account of conflicts from 2001 to 2022, incorporating diverse perspectives and voices. [Extracted from the article]

Background: Allergic diseases are systemic chronic inflammatory diseases associated with multiorgan damage and complex pathogenesis. Several studies have revealed the association of gene expression abnormalities with the development of allergic diseases, but the biomedical field still lacks a public platform for comprehensive analysis and visualization of transcriptomic data of allergic diseases. Objective: The aim of the study is to provide a comprehensive web tool for multiple analysis in allergic diseases. Methods: We retrieved and downloaded human and mouse gene expression profile data associated with allergic diseases from the Gene Expression Omnibus (GEO) database and standardized the data uniformly. We used gene sets obtained from the MSigDB database for pathway enrichment analysis and multiple immune infiltration algorithms for the estimation of immune cell proportion. The basic construction of the web pages was based on the Shiny framework. Additionally, more convenient features were added to the server to improve the efficiency of the web pages, such as jQuery plugins and a comment box to collect user feedback. Results: We developed CTPAD, an interactive R Shiny application that integrates public databases and multiple algorithms to explore allergic disease-related datasets and implement rich transcriptomic visualization capabilities, including gene expression analysis, pathway enrichment analysis, immune infiltration analysis, correlation analysis, and single-cell RNA sequencing analysis. All functional modules offer customization options and can be downloaded in PDF format with high-resolution images. Conclusions: CTPAD largely facilitates the work of researchers without bioinformatics background to enable them to better explore the transcriptomic features associated with allergic diseases. CTPAD is available at https://smuonco.shinyapps.io/CTPAD/. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, we present CORE-GPT, an innovative service of the COnnecting REpositories (CORE) Open Access Collection that combines the Generative Pre-trained Transformers (GPT) model with the extensive collection of open access scientific documents from the CORE Open Access Collection. CORE-GPT provides citations of the scientific papers underlying the answers, links to PDF formats of the papers and thus improves the reliability and credibility of the answers. Methodology/approach: This paper gives an insight into the performance of the GPT models that played an important role in the creation of the CORE-GPT service. We also present some results from a recent study on the reliability of the CORE-GPT service and reflect on the role of libraries in the use of open access services. Results: CORE-GPT represents an important step forward in improving the search experience and the reliability of answers. By combining the GPT with the rich CORE database, it enables the provision of comprehensive and evidence-based answers to questions. Originality/practical implications: This article is one of the first presentations of the CORE-GPT service in Slovenia. [ABSTRACT FROM AUTHOR]

The article reviews Jacques Schuhmacher's book "Nazi-Era Provenance of Museum Collections: A research guide," which provides a framework for researchers and museum professionals to uncover the tragic stories of families and art lost during the Holocaust. The book contextualizes provenance research, emphasizing the importance of commemorating victims and seeking justice to challenge the lingering impact of Nazi actions. It covers Nazi spoliation, restitution efforts post-1945, and practical research techniques for provenance work, highlighting the complexities and challenges faced by researchers in uncovering historical truths. The book is available in multiple formats, including a freely accessible PDF, and features historical photographs that shed light on Nazi looting and persecution. [Extracted from the article]

The article discusses the intersection of AI, art, and copyright, focusing on the legal and ethical implications of generative AI platforms. It highlights concerns about data scraping, copyright infringement, and the need for legislative responses. The text also mentions global initiatives, such as the G7 AI Principles, OECD AI Principles, and UNESCO's Recommendation on the Ethics of AI, to address the responsible use of AI technologies. The article concludes by emphasizing the importance of updating copyright laws to protect creators in the evolving landscape of AI-generated content. [Extracted from the article]

The extraction of data from tables in PDF documents has been a longstanding challenge in the field of data processing and analysis. While traditional methods have been explored in depth, the rise of Large Language Models (LLMs) offers new possibilities. This article addresses the knowledge gaps regarding LLMs, specifically ChatGPT-4 and BARD, for extracting and interpreting data from financial tables in PDF format. This research is motivated by the real-world need to efficiently gather and analyze corporate financial information. The hypothesis is that LLMs—in this case, ChatGPT-4 and BARD—can accurately extract key financial data, such as balance sheets and income statements. The methodology involves selecting representative pages from 46 annual reports of large Swiss corporations listed in the SMI Expanded Index from 2022 and copy–pasting text from these into LLMs. Eight analytical questions were posed to the LLMs, and their responses were assessed for accuracy and for identifying potential error sources in data extraction. The findings revealed significant variance in the performance of ChatGPT-4 and another LLM, BARD, with ChatGPT-4 generally exhibiting superior accuracy. This research contributes to understanding the capabilities and limitations of LLMs in processing and interpreting complex financial data from corporate documents. [ABSTRACT FROM AUTHOR]

Accurate data extraction is a key component of evidence synthesis and critical to valid results. The advent of publicly available large language models (LLMs) has generated interest in these tools for evidence synthesis and created uncertainty about the choice of LLM. We compare the performance of two widely available LLMs (Claude 2 and GPT‐4) for extracting pre‐specified data elements from 10 published articles included in a previously completed systematic review. We use prompts and full study PDFs to compare the outputs from the browser versions of Claude 2 and GPT‐4. GPT‐4 required use of a third‐party plugin to upload and parse PDFs. Accuracy was high for Claude 2 (96.3%). The accuracy of GPT‐4 with the plug‐in was lower (68.8%); however, most of the errors were due to the plug‐in. Both LLMs correctly recognized when prespecified data elements were missing from the source PDF and generated correct information for data elements that were not reported explicitly in the articles. A secondary analysis demonstrated that, when provided selected text from the PDFs, Claude 2 and GPT‐4 accurately extracted 98.7% and 100% of the data elements, respectively. Limitations include the narrow scope of the study PDFs used, that prompt development was completed using only Claude 2, and that we cannot guarantee the open‐source articles were not used to train the LLMs. This study highlights the potential for LLMs to revolutionize data extraction but underscores the importance of accurate PDF parsing. For now, it remains essential for a human investigator to validate LLM extractions. [ABSTRACT FROM AUTHOR]

The article discusses the importance of reciprocity in school-based research, highlighting the need to consider the costs and benefits to schools and teachers. It suggests that schools should be offered more empowering rewards for participating in research, rather than just financial incentives. The article also addresses the challenges faced by schools in engaging in research, such as lack of access to literature and expertise in research design and ethics. It proposes that collaborative partnerships between schools and research institutions can overcome these challenges and lead to more impactful and relevant research findings. The traditional relationship between researchers and participants should be reconsidered to acknowledge the expertise and contribution of both parties. Applying research findings to practice in schools can be challenging due to differences in starting points, community, and economic factors. Schools can conduct internal studies to determine the applicability of external findings within their specific contexts. Opportunities for schools to participate in research can be found through organizations like the Chartered College of Teaching and the Education Endowment Foundation. Collaborative research between schools and research institutions can help bridge the gap between research outcomes and what is relevant and feasible in different contexts. It is important for research organizers and sponsors to disclose how partnerships are formed to encourage similar procedures in the future. [Extracted from the article]

The article explores how QTLS accreditation can enhance evidence-informed practice in further education (FE) settings. QTLS, awarded by the Society for Education and Training (SET), validates teachers' expertise in FE and encourages the integration of research evidence with practitioner knowledge. Teachers seeking QTLS accreditation must demonstrate their competence in delivering high-quality teaching and learning through a portfolio that showcases their ability to engage with evidence-informed practice. The article emphasizes the role of QTLS in promoting evidence-informed leadership and driving positive outcomes in FE, while acknowledging the challenges and opportunities associated with the accreditation process. It discusses the challenges faced by teachers pursuing QTLS accreditation, such as the need for mentorship programs, access to resources and workshops, and financial barriers. The article suggests addressing these challenges on an institutional level to ensure equitable access to professional development opportunities and promote evidence-informed practices within FE institutions. [Extracted from the article]

In this work, we investigate existing citation practices by analysing a huge set of articles published in journals to measure which metadata are used across the various scholarly disciplines, independently from the particular citation style adopted, for defining bibliographic reference. We selected the most cited journals in each of the 27 subject areas listed in the SCImago Journal Rank in the 2015–2017 triennium according to the SCImago total cites ranking. Each journal in the sample was represented by five articles (in PDF format) published in the most recent issue published in October 2019, for a total of 729 articles. We extracted all 34,140 bibliographic references in the bibliographic references lists of these articles. Finally, we detected the types of cited works in each discipline and the structure of bibliographic references and in-text reference pointers for each type of cited work. By analysing the data gathered, we observed that the bibliographic references in our sample referenced 36 different types of cited works. Such a considerable variety of publications revealed the existence of particular citing behaviours in scientific articles that varied from subject area to subject area. [ABSTRACT FROM AUTHOR]

Avian Diseases is an international journal that focuses on avian diseases, particularly in poultry health. The journal publishes original research on topics such as microbiology, immunology, pathology, and epidemiology. Manuscripts submitted to the journal undergo a review process by the editor and members of the Editorial Board. The journal is copyrighted by the American Association of Avian Pathologists (AAAP) and offers Open Access options for authors. Authors are provided with guidelines for manuscript submission, including specific formatting requirements and instructions for citing references. The document also provides information on various types of publications accepted by the journal and guidelines for including supplemental materials. [Extracted from the article]

Despite the public availability of legal documents, there is a need for finding specific information contained in them, such as paragraphs, clauses, items and so on. With such support, users could find more specific information than only finding whole legal documents. Some research efforts have been made in this area, but there is still a lot to be done to have legal information available more easily to be found. Thus, due to the large number of published legal documents and the high degree of connectivity, simple access to the document is not enough. It is necessary to recover the related legal framework for a specific need. In other words, the retrieval of the set of legal documents and their parts related to a specific subject is necessary. Therefore, in this work, we present a proposal of a RDF-based graph to represent and search parts of legal documents, as the output of a set of terms that represents the pursued legal information. Such a proposal is well-grounded on an ontological view, which makes possible to describe the general structure of a legal system and the structure of legal documents, providing this way the grounds for the implementation of the proposed RDF graph in terms of the meaning of their parts and relationships. We posed several queries to retrieve parts of legal documents related to sets of words and the results were significant. [ABSTRACT FROM AUTHOR]

The article discusses the relationship between files and programs, arguing that while all files can be considered programs, not all programs are files. It challenges common assumptions about programs and files, demonstrating that any file can be seen as a program when supplied as input to a specific program. The author emphasizes that the distinction between files and programs depends on the context of use and the intentions of the user. The text provides historical examples and philosophical perspectives to support its arguments, ultimately suggesting that there is no technical criterion for distinguishing between file-program pairs and program-interpreter pairs. [Extracted from the article]

This study aims to improve college magazines, making them more engaging and user-friendly. We combined eye-tracking technology with artificial intelligence to accurately predict consumer behaviours and preferences. Our analysis included three college magazines, both online and in PDF format. We evaluated user experience using neuromarketing eye-tracking AI prediction software, trained on a large consumer neuroscience dataset of eye-tracking recordings from 180,000 participants, using Tobii X2 30 equipment, encompassing over 100 billion data points and 15 consumer contexts. An analysis was conducted with R programming v. 2023.06.0+421 and advanced SPSS statistics v. 27, IBM. (ANOVA, Welch's Two-Sample t-test, and Pearson's correlation). Our research demonstrated the potential of modern eye-tracking AI technologies in providing insights into various types of attention, including focus, engagement, cognitive demand, and clarity. The scientific accuracy of our findings, at 97–99%, underscores the reliability and robustness of our research, instilling confidence in the audience. This study also emphasizes the potential for future research to explore automated datasets, enhancing reliability and applicability across various fields and inspiring hope for further advancements in the field. [ABSTRACT FROM AUTHOR]

The article discusses William Still's role as an abolitionist and civil rights leader in Philadelphia from 1853 to 1861, assisting nearly 1,000 freedom seekers in their escape from enslavement. Still's data collection methods provided scholars with a dataset on Underground Railroad activities, shedding light on individual stories of enslaved individuals seeking freedom. The dataset offers opportunities for scholars to explore trends in freedom seekers' experiences and transportation methods, contributing to a deeper understanding of the Underground Railroad's use during the 1850s. [Extracted from the article]

Investors, practitioners, and stock researchers highly need data related to financial performance to predict a company's financial health condition, which is used as a basis to consider investing in it. The Indonesia Stock Exchange (IDX) website provides reports on the company's financial performance. Unfortunately, the company’s financial data found on the IDX website are in PDF format, and researchers must download them one by one, which takes a long time. This study presents a website-based application, named Indonesia Company Performance (INDCOMP), built using the R programming language and involving various R packages and frameworks to assist investors, practitioners, and stock researchers in studying the financial performance of companies. This application can help users quickly access the financial performance data of various companies, present financial performance data in data tables, and perform data visualizations as well as statistical analyses [ABSTRACT FROM AUTHOR]

The article evaluates the performance of the ChatGPT-4o large language model in risk of bias assessments using Cochrane's RoB 2.0 tool. The study found that ChatGPT-4o had slight agreement in the overall assessment and varied agreement rates in different bias domains. The results suggest that ChatGPT-4o may not be suitable for risk of bias assessments with simple prompts, highlighting the need for further research on improving its performance. [Extracted from the article]

Background: Clinical practice guidelines are crucial for enhancing healthcare quality and patient outcomes. Yet, their implementation remains inconsistent across various professions and disciplines. Previous findings on the implementation of the German guideline for schizophrenia (2019) revealed low adherence rates among healthcare professionals. Barriers to guideline adherence are multifaceted, influenced by individual, contextual, and guideline-related factors. This study aims to investigate the effectiveness of a digital guideline version compared to print/PDF formats in enhancing guideline adherence. Methods: A multicenter, cluster-randomized controlled trial was conducted in South Bavaria, Germany, involving psychologists and physicians. Participants were divided into two groups: implementation of the guideline using a digital online version via the MAGICapp platform and the other using the traditional print/PDF version. The study included a baseline assessment and a post-intervention assessment following a 6-month intervention phase. The primary outcome was guideline knowledge, which was assessed using a guideline knowledge questionnaire. Results: The study included 217 participants at baseline and 120 at post-intervention. Both groups showed significant improvements in guideline knowledge; however, no notable difference was found between both study groups regarding guideline knowledge at either time points. At baseline, 43.6% in the control group (CG) and 52.5% of the interventional group (IG) met the criterion. There was no significant difference in the primary outcome between the two groups at either time point (T0: Chi2(1) = 1.65, p = 0.199, T1: Chi2(1) = 0.34, p = 0.561). At post-intervention, both groups improved, with 58.2% in the CG and 63.5% in the IG meeting this criterion. Conclusions: While the study did not include a control group without any implementation strategy, the overall improvement in guideline knowledge following an implementation strategy, independent of the format, was confirmed. The digital guideline version, while not superior in enhancing knowledge, showed potential benefits in shared decision-making skills. However, familiarity with traditional formats and various barriers to digital application may have influenced these results. The study highlights the importance of tailored implementation strategies, especially for younger healthcare providers. Trial registration: https://drks.de/search/de/trial/DRKS00028895 [ABSTRACT FROM AUTHOR]

Portable Document Format (PDF) files have emerged as a ubiquitous and multi-faceted medium for the dissemination and interchange of information. The watermarking algorithms based on PDF document have spurred much research in academia due to their practical applications in copyright protection, trace-tracking and digital forensics. In this work, we emphasize the unique nature of PDF documents among other multimedia content, and propose a robust PDF watermarking scheme with versatility and compatibility, which is competent in resisting multi-level attacks including text editing, format modification, page extraction, textbox republication, and more. We traverse over the decompressed PDF file for objects related to important elements like text, images and forms, and embed encrypted watermark as a dictionary entry inside the objects. In addition, we have developed a tamper detection algorithm that ensures content integrity and facilitates the identification of tampered areas within the watermarked file. We finally make a comparison between the proposed and existing algorithms, and our algorithm offers high invisibility, scalable embedding capacity, strong robustness. It has excellent compatibility in files with different mediums, content and languages, and it is accessible to diverse file generators and readers. Meanwhile, the method can be applied in various application scenarios like copyright protection, multi-level distribution trace tracking and tamper detection. [ABSTRACT FROM AUTHOR]

This study presents a novel algorithm for image classification based on a quasi-Bayesian approach and the extraction of probability density functions (PDFs). First, representative PDFs are extracted from each image using its features. Next, a measure is developed to evaluate the similarity between the extracted PDFs. Finally, an algorithm is established for determining prior probabilities using fuzzy clustering techniques. By combining these improvements, we develop a more efficient algorithm for classifying image data. An image is assigned to a specific group if it has the highest value of prior probability and a similar level to that group. We explain the proposed algorithm step-by-step with a numerical example and clearly demonstrate its convergence. When applied to multiple image datasets, the proposed algorithm has shown stability and efficiency, outperforming many other statistical and machine learning methods. Additionally, we have developed a Matlab procedure to apply the proposed algorithm to real image datasets. These applications demonstrate the potential of research in various fields related to the digital revolution and artificial intelligence. [ABSTRACT FROM AUTHOR]

The Wagner Journal has launched a new website that offers a wide range of resources for Wagner enthusiasts. The website features over 50 regular issues, special issues, feature articles, and reviews of live performances, books, CDs, and DVDs. Users can purchase individual features and reviews in PDF format, browse issues, and subscribe to the journal. The website is user-friendly and does not have pop-ups or require the acceptance of cookies. Additionally, the website includes a section of free content, including articles not published in the print edition. [Extracted from the article]

The article examines the role of science in European integration, highlighting the concept of ‘EUropeanisation in and through science' as both a cause and effect of European development within the European Union (EU). Topics discussed include the evolution of EU science policy, the impact of scientific research on European integration, and the role of science diplomacy in fostering interconnectedness within the EU.

The document titled "Selected Open Access Studies on Nonviolent Collective Action: Preventing Mass Atrocities, Transforming Civil Wars, Democratizing Regimes" is a comprehensive collection of resources on nonviolent collective action. It includes a documentary series called "A Force More Powerful" that showcases how nonviolent power has been successful in overcoming oppression and authoritarian rule in various countries. The document also offers a study guide for the documentary, a webinar on external support in nonviolent campaigns, and a proposed normative framework called "The Right to Assist" for preventing mass atrocities. It further explores the impact of nonviolent resistance on civil wars and the prevention of mass killings during popular uprisings. The text provides summaries and resources on civil resistance tactics, including reports, monographs, and a database of over 1000 summaries of nonviolent campaigns worldwide. These resources offer insights into the strategies, challenges, and success factors of nonviolent movements, as well as recommendations for effectively supporting them. [Extracted from the article]