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The analysis of public affairs documents is crucial for citizens as it promotes transparency, accountability, and informed decision-making. It allows citizens to understand government policies, participate in public discourse, and hold representatives accountable. This is crucial, and sometimes a matter of life or death, for companies whose operation depend on certain regulations. Large Language Models (LLMs) have the potential to greatly enhance the analysis of public affairs documents by effectively processing and understanding the complex language used in such documents. In this work, we analyze the performance of LLMs in classifying public affairs documents. As a natural multi-label task, the classification of these documents presents important challenges. In this work, we use a regex-powered tool to collect a database of public affairs documents with more than 33K samples and 22.5M tokens. Our experiments assess the performance of 4 different Spanish LLMs to classify up to 30 different topics in the data in different configurations. The results shows that LLMs can be of great use to process domain-specific documents, such as those in the domain of public affairs.

The automatic analysis of document layouts in digital-born PDF documents remains a challenging problem due to the heterogeneous arrangement of textual and nontextual elements and the imprecision of the textual metadata in the Portable Document Format. In this work, we benchmark Graph Neural Network (GNN) architectures for the task of fine-grained layout classification of text blocks from digital native documents. We introduce two graph construction structures: a k-closest-neighbor graph and a fully connected graph, and generate node features via pre-trained text and vision models, thus avoiding manual feature engineering. Three experimental frameworks are evaluated: single-modality (text or visual), concatenated multimodal, and dual-branch multimodal. We evaluated four foundational GNN models and compared them with the baseline. Our experiments are specifically conducted on a rich dataset of public affairs documents that includes more than 20 sources (e.g., regional and national-level official gazettes), 37K PDF documents, with 441K pages in total. Our results demonstrate that GraphSAGE operating on the k-closest-neighbor graph in a dual-branch configuration achieves the highest pe

Ask your chatbot to impersonate an expert from Russia and an expert from US and query it on Chinese politics. How might the outputs differ? Or, to prepare ourselves for the worse, how might they converge? Scholars have raised concerns LLM based applications can homogenize cultures and flatten perspectives. But exactly how much does LLM generated outputs converge despite explicit different role assignment? This study provides empirical evidence to the above question. The critique centres on pretrained models regurgitating ossified political jargons used in the Western world when speaking about China, Iran, Russian, and US politics, despite changes in these countries happening daily or hourly. The experiments combine role-prompting and similarity metrics. The results show that AI generated discourses from four models about Iran and China are the most homogeneous and unchanging across all four models, including OpenAI GPT, Google Gemini, Anthropic Claude, and DeepSeek, despite the prompted perspective change and the actual changes in real life. This study does not engage with history, politics, or literature as traditional disciplinary approaches would; instead, it takes cues from int

Coronary artery calcium (CAC) is highly predictive of cardiovascular events. While millions of chest CT scans are performed annually in the United States, CAC is not routinely quantified from scans done for non-cardiac purposes. A deep learning algorithm was developed using 446 expert segmentations to automatically quantify CAC on non-contrast, non-gated CT scans (AI-CAC). Our study differs from prior works as we leverage imaging data across the Veterans Affairs national healthcare system, from 98 medical centers, capturing extensive heterogeneity in imaging protocols, scanners, and patients. AI-CAC performance on non-gated scans was compared against clinical standard ECG-gated CAC scoring. Non-gated AI-CAC differentiated zero vs. non-zero and less than 100 vs. 100 or greater Agatston scores with accuracies of 89.4% (F1 0.93) and 87.3% (F1 0.89), respectively, in 795 patients with paired gated scans within a year of a non-gated CT scan. Non-gated AI-CAC was predictive of 10-year all-cause mortality (CAC 0 vs. >400 group: 25.4% vs. 60.2%, Cox HR 3.49, p < 0.005), and composite first-time stroke, MI, or death (CAC 0 vs. >400 group: 33.5% vs. 63.8%, Cox HR 3.00, p < 0.005)

Vine copula models have become highly popular practical tools for modeling multivariate dependencies. To maintain tractability, a commonly employed simplifying assumption is that conditional copulas remain unchanged by the conditioning variables. This assumption has sparked a somewhat polarizing debate within the copula community. The fact that much of this dispute occurs outside the public record has placed the field in an unfortunate position, impeding scientific progress. In this article, I will review what we know about the flexibility and limitations of simplified vine copula models, explore the broader implications, and offer my own, hopefully reconciling, perspective on the issue.

This study investigates the complexity of regulatory affairs in the medical device industry, a critical factor influencing market access and patient care. Through qualitative research, we sought expert insights to understand the factors contributing to this complexity. The study involved semi-structured interviews with 28 professionals from medical device companies, specializing in various aspects of regulatory affairs. These interviews were analyzed using open coding and Natural Language Processing (NLP) techniques. The findings reveal key sources of complexity within the regulatory landscape, divided into five domains: (A) Regulatory language complexity, (B) Intricacies within the regulatory process, (C) Global-level complexities, (D) Database-related considerations, and (E) Product-level issues. The participants highlighted the need for strategies to streamline regulatory compliance, enhance interactions between regulatory bodies and industry players, and develop adaptable frameworks for rapid technological advancements. Emphasizing interdisciplinary collaboration and increased transparency, the study concludes that these elements are vital for establishing coherent and effectiv

Over the last 10 years, there has been a growing interest in diversity in human capital. Fueled by the business case for diversity, there is an increasing interest in understanding how the combination of people with different backgrounds fosters the innovation performance of firms. Studies have measured diversity on a wide range of personal-level characteristics, at different levels of the organization, and in particular kinds of settings. Innovation performance has been measured using an arsenal of indicators, often drawing on a large range of databases. This paper takes stock of this research, identifying the current state of affairs and proposing future research trajectories in the field of diversity and innovation

Every day, thousands of digital documents are generated with useful information for companies, public organizations, and citizens. Given the impossibility of processing them manually, the automatic processing of these documents is becoming increasingly necessary in certain sectors. However, this task remains challenging, since in most cases a text-only based parsing is not enough to fully understand the information presented through different components of varying significance. In this regard, Document Layout Analysis (DLA) has been an interesting research field for many years, which aims to detect and classify the basic components of a document. In this work, we used a procedure to semi-automatically annotate digital documents with different layout labels, including 4 basic layout blocks and 4 text categories. We apply this procedure to collect a novel database for DLA in the public affairs domain, using a set of 24 data sources from the Spanish Administration. The database comprises 37.9K documents with more than 441K document pages, and more than 8M labels associated to 8 layout block units. The results of our experiments validate the proposed text labeling procedure with accura

In 2010, the United Nations Committee on the Peaceful Uses of Outer Space began consideration of a new agenda item under a three-year work plan on the International Space Weather Initiative (ISWI). The main objectives of ISWI are to contribute to the development of the scientific insight necessary to improve understanding and forecasting capabilities of space weather as well as to education and public outreach. The United Nations Programme on Space Applications, implemented by the Office for Outer Space Affairs, is implementing ISWI in the framework of its United Nations Basic Space Science Initiative (UNBSSI), a long-term effort, launched in 1991, for the development of basic space science and for international and regional cooperation in this field on a worldwide basis, particularly in developing countries. UNBSSI encompassed a series of workshops, held from 1991 to 2004, which addressed the status of basic space science in Africa, Asia and the Pacific, Latin America and the Caribbean, and Western Asia. As a result several small astronomical research facilities have been inaugurated and education programmes at the university level were established. Between 2005 and 2009, the UNBS

The ability to recognize students weakness and solve any problem that may confront them in timely fashion is always a target for all educational institutions. Thus, colleges and universities implement the so-called academic advising affairs. On the academic advisor relies the responsibility of solving any problem that may confront students learning progress. This paper shows how the adviser can benefit from data mining techniques, namely decision trees techniques. The C 4.5 algorithm is used as a method for building such trees. The output is evaluated based on the accuracy measure, Kappa measure, and ROC area. The difference between the registered and gained credit hours is considered as the main attribute on which advisor can rely

The first release of the 5G protocol specifications, 3rd Generation Partnership Project (3GPP) Release 15, were published in December 2017 and the first 5G protocol security specifications in March 2018. As one of the technology cornerstones for Vehicle-to-Vehicle (V2X), Vehicle-to-Everything (V2E) systems and other critical systems, 5G defines some strict communication goals, such as massive device connectivity, sub-10ms latency and ultra high bit-rate. Likewise, given the firm security requirements of certain critical applications expected to be deployed on this new cellular communications standard, 5G defines important security goals. As such, 5G networks are intended to address known protocol vulnerabilities present in both legacy GSM (Global System for Mobile Communications) networks as well as current LTE (Long Term Evolution) mobile systems. This manuscript presents a summary and analysis of the current state of affairs in 5G protocol security, discussing the main areas that should still be improved further before 5G systems go live. Although the 5G security standard documents were released just a year ago, there is a number of research papers detailing security vulnerabilit

In this work, we propose a zero-adjusted log-symmetric quantile regression model. Initially, we introduce zero-adjusted log-symmetric distributions, which allow for the accommodation of zeros. The estimation of the parameters is approached by the maximum likelihood method and a Monte Carlo simulation is performed to evaluate the estimates. Finally, we illustrate the proposed methodology with the use of a real extramarital affairs data set.

Social media provides political news and information for both active duty military personnel and veterans. We analyze the subgroups of Twitter and Facebook users who spend time consuming junk news from websites that target US military personnel and veterans with conspiracy theories, misinformation, and other forms of junk news about military affairs and national security issues. (1) Over Twitter we find that there are significant and persistent interactions between current and former military personnel and a broad network of extremist, Russia-focused, and international conspiracy subgroups. (2) Over Facebook, we find significant and persistent interactions between public pages for military and veterans and subgroups dedicated to political conspiracy, and both sides of the political spectrum. (3) Over Facebook, the users who are most interested in conspiracy theories and the political right seem to be distributing the most junk news, whereas users who are either in the military or are veterans are among the most sophisticated news consumers, and share very little junk news through the network.

Kuranishi structures were introduced to symplectic topology by Fukaya and Ono and recently refined by Joyce, in order to extract homological data from compactified moduli spaces of holomorphic maps in cases where geometric regularization approaches such as perturbations of the almost complex structure do not yield a smooth structure on the moduli space. We give a general survey of regularization techniques in symplectic topology, pointing to some general analytic issues, and discussing some specific topological issues of the Kuranishi approach. In the main body of the paper we provide an abstract framework of Kuranishi atlases which separates the analytic and topological issues. Throughout, we focus on the most fundamental issues, which are already present in applying virtual transversality techniques to moduli spaces of holomorphic spheres without nodes or nontrivial isotropy. This is the reinstated 2013 version of this survey and sample construction. A generalized version of the topological theory is now available under 'The topology of Kuranishi atlases' arxiv:1508.01844, with the survey parts and VMC construction updated in 'The fundamental class of smooth Kuranishi atlases wit