Hasil untuk "French literature - Italian literature - Spanish literature - Portuguese literature"

J. Maudos, J. Guevara

G. Vandermeersch, L. Van Cauwenberghe, Colin R. Janssen et al.

Geoffrey Taghon

Aptamer researchers face a literature landscape scattered across publications, supplements, and databases, with each search consuming hours that could be spent at the bench. AptaFind transforms this navigation problem through a three-tier intelligence architecture that recognizes research mining is a spectrum, not a binary success or failure. The system delivers direct sequence extraction when possible, curated research leads when extraction fails, and exhaustive literature discovery for additional confidence. By combining local language models for semantic understanding with deterministic algorithms for reliability, AptaFind operates without cloud dependencies or subscription barriers. Validation across 300 University of Texas Aptamer Database targets demonstrates 84 % with some literature found, 84 % with curated research leads, and 79 % with a direct sequence extraction, at a laptop-compute rate of over 900 targets an hour. The platform proves that even when direct sequence extraction fails, automation can still deliver the actionable intelligence researchers need by rapidly narrowing the search to high quality references.

Huan He, Xueqing Peng, Yutong Xie et al.

Biomedical researchers face increasing challenges in navigating millions of publications in diverse domains. Traditional search engines typically return articles as ranked text lists, offering little support for global exploration or in-depth analysis. Although recent advances in generative AI and large language models have shown promise in tasks such as summarization, extraction, and question answering, their dialog-based implementations are poorly integrated with literature search workflows. To address this gap, we introduce MedViz, a visual analytics system that integrates multiple AI agents with interactive visualization to support the exploration of the large-scale biomedical literature. MedViz combines a semantic map of millions of articles with agent-driven functions for querying, summarizing, and hypothesis generation, allowing researchers to iteratively refine questions, identify trends, and uncover hidden connections. By bridging intelligent agents with interactive visualization, MedViz transforms biomedical literature search into a dynamic, exploratory process that accelerates knowledge discovery.

Camilo Sanchez, Sui Wang, Kaisa Savolainen et al.

HCI is future-oriented by nature: it explores new human--technology interactions and applies the findings to promote and shape vital visions of society. Still, the visions of futures in HCI publications seem largely implicit, techno-deterministic, narrow, and lacking in roadmaps and attention to uncertainties. A literature review centered on this problem examined futuring and its forms in the ACM Digital Library's most frequently cited HCI publications. This analysis entailed developing the four-category framework SPIN, informed by futures studies literature. The results confirm that, while technology indeed drives futuring in HCI, a growing body of HCI research is coming to challenge techno-centric visions. Emerging foci of HCI futuring demonstrate active exploration of uncertainty, a focus on human experience, and contestation of dominant narratives. The paper concludes with insight illuminating factors behind techno-centrism's continued dominance of HCI discourse, as grounding for five opportunities for the field to expand its contribution to futures and anticipation research.

Allard Oelen, Mohamad Yaser Jaradeh, Sören Auer

As the volume of published scholarly literature continues to grow, finding relevant literature becomes increasingly difficult. With the rise of generative Artificial Intelligence (AI), and particularly Large Language Models (LLMs), new possibilities emerge to find and explore literature. We introduce ASK (Assistant for Scientific Knowledge), an AI-driven scholarly literature search and exploration system that follows a neuro-symbolic approach. ASK aims to provide active support to researchers in finding relevant scholarly literature by leveraging vector search, LLMs, and knowledge graphs. The system allows users to input research questions in natural language and retrieve relevant articles. ASK automatically extracts key information and generates answers to research questions using a Retrieval-Augmented Generation (RAG) approach. We present an evaluation of ASK, assessing the system's usability and usefulness. Findings indicate that the system is user-friendly and users are generally satisfied while using the system.

S. Brugueras, B. F. Martínez, Josué Martínez de la Puente et al.

Mosquito borne diseases are a group of infections that affect humans. Emerging or reemerging diseases are those that (re)occur in regions, groups or hosts that were previously free from these diseases: dengue virus; chikungunya virus; Zika virus; West Nile fever and malaria. In Europe, these infections are mostly imported; however, due to the presence of competent mosquitoes and the number of trips both to and from endemic areas, these pathogens are potentially emergent or re-emergent. Present and future climatic conditions, as well as meteorological, environmental and demographic aspects are risk factors for the distribution of different vectors and/or diseases.This review aimed to identify and analyze the existing literature on the transmission of mosquito borne diseases and those factors potentially affecting their transmission risk of them in six southern European countries with similar environmental conditions: Croatia, France, Greece, Italy, Portugal and Spain. In addition, we would identify those factors potentially affecting the (re)introduction or spread of mosquito vectors. This task has been undertaken with a focus on the environmental and climatic factors, including the effects of climate change. We undertook a systematic review of the vectors, diseases and their associations with climactic and environmental factors in European countries of the Mediterranean region. We followed the PRISMA guidelines and used explicit and systematic methods to identify, select and critically evaluate the studies which were relevant to the topic.We identified 1,302 articles in the first search of the databases. Of those, 160 were selected for full-text review. The final data set included 61 articles published between 2000 and 2017. 39.3% of the papers were related with dengue, chikungunya and Zika virus or their vectors. Temperature, precipitation and population density were key factors among others. 32.8% studied West Nile virus and its vectors, being temperature, precipitation and NDVI the most frequently used variables. Malaria have been studied in 23% of the articles, with temperature, precipitation and presence of water indexes as the most used variables. The number of publications focused on mosquito borne diseases is increasing in recent years, reflecting the increased interest in that diseases in southern European countries. Climatic and environmental variables are key factors on mosquitoes´ distribution and to show the risk of emergence and/or spread of emergent diseases and to study the spatial changes in that distributions.

Anna Bringmann, Anastasia Zhukova

This literature review gives an overview of current approaches to perform domain adaptation in a low-resource and approaches to perform multilingual semantic search in a low-resource setting. We developed a new typology to cluster domain adaptation approaches based on the part of dense textual information retrieval systems, which they adapt, focusing on how to combine them efficiently. We also explore the possibilities of combining multilingual semantic search with domain adaptation approaches for dense retrievers in a low-resource setting.

Gyeong Hoon Yi, Jiwoo Choi, Hyeongyun Song et al.

Efficiently extracting data from tables in the scientific literature is pivotal for building large-scale databases. However, the tables reported in materials science papers exist in highly diverse forms; thus, rule-based extractions are an ineffective approach. To overcome this challenge, we present MaTableGPT, which is a GPT-based table data extractor from the materials science literature. MaTableGPT features key strategies of table data representation and table splitting for better GPT comprehension and filtering hallucinated information through follow-up questions. When applied to a vast volume of water splitting catalysis literature, MaTableGPT achieved an extraction accuracy (total F1 score) of up to 96.8%. Through comprehensive evaluations of the GPT usage cost, labeling cost, and extraction accuracy for the learning methods of zero-shot, few-shot and fine-tuning, we present a Pareto-front mapping where the few-shot learning method was found to be the most balanced solution owing to both its high extraction accuracy (total F1 score>95%) and low cost (GPT usage cost of 5.97 US dollars and labeling cost of 10 I/O paired examples). The statistical analyses conducted on the database generated by MaTableGPT revealed valuable insights into the distribution of the overpotential and elemental utilization across the reported catalysts in the water splitting literature.

S. Meo, A. Meo, D. C. Klonof

S. Ciarlantini, M. Madaleno, M. Robaina et al.

The present study intends to explore the relationship between tourism growth and air pollution at a regional level for five important tourism European destinations: France, Spain, Greece, Portugal, and Italy. Most of the studies found in the literature examine this relationship on a national scale and focus only on the CO_2 pollutant, which is a greenhouse gas but not a critical pollutant in terms of air quality and human exposure. This research focuses on a regional basis (NUTS 2 classification) and takes into account the main critical pollutants in terms of urban air pollution (namely: NOx, PM10, and PM2.5), and considers 10 years, from 2009 until 2018. This work aims to investigate evidence of a tourism-induced Environmental Kuznets Curve (EKC) for the countries through the construction of five panels, one for each country, including different variables: the Gross Domestic Product, the energy consumption, and the number of nights spent at tourist accommodation establishments from both domestic and foreign tourists. The Levin-Lin-Chu unit root test proves the variables to be stationary, while the Pedroni cointegration test shows that they are integrated. The pooled OLS estimator is employed throughout the countries to check the relationship among the variables. Results reveal that the tourism-induced EKC hypothesis is not validated for any of the countries. The findings also show that in Portugal, Italy, and Greece, there is a negative relationship between economic growth and environmental pollution, while mixed evidence is found for France and Spain. Moreover, differences in the impacts of international and domestic tourists on air pollution are found: foreign tourists negatively impact emissions, while domestic ones increase them. This result is clear for Spain, Greece, and Italy. The Granger panel causality test is then conducted to see the causality among the variables.

Mike Nkongolo, Nita Mennega, Izaan van Zyl

This study employs a systematic literature review approach to identify the requirements of a career as a cybersecurity professional. It aims to raise public awareness regarding opportunities in the Information Security (IS) profession. A total of 1,520 articles were identified from four academic databases by searching using the terms "cybersecurity" and "skills". After rigorous screening according to various criteria, 31 papers remained. The findings of these studies were thematically analyzed to describe the knowledge and skills an IS professional should possess. The research found that a considerable investment in time is necessary for cybersecurity professionals to reach the required technical proficiency. It also identified female gender barriers to cybersecurity careers due to the unique requirements of the field and suggests that females may successfully enter at lower levels and progress up the tiers as circumstances dictate.

Marco Antonio Stranisci, Eleonora Bernasconi, Viviana Patti et al.

Digital media have enabled the access to unprecedented literary knowledge. Authors, readers, and scholars are now able to discover and share an increasing amount of information about books and their authors. However, these sources of knowledge are fragmented and do not adequately represent non-Western writers and their works. In this paper we present The World Literature Knowledge Graph, a semantic resource containing 194,346 writers and 965,210 works, specifically designed for exploring facts about literary works and authors from different parts of the world. The knowledge graph integrates information about the reception of literary works gathered from 3 different communities of readers, aligned according to a single semantic model. The resource is accessible through an online visualization platform, which can be found at the following URL: https://literaturegraph.di.unito.it/. This platform has been rigorously tested and validated by $3$ distinct categories of experts who have found it to be highly beneficial for their respective work domains. These categories include teachers, researchers in the humanities, and professionals in the publishing industry. The feedback received from these experts confirms that they can effectively utilize the platform to enhance their work processes and achieve valuable outcomes.

C. Maier

BackgroundNurse prescribing of medicines is increasing worldwide, but there is limited research in Europe. The objective of this study was to analyse which countries in Europe have adopted laws on nurse prescribing.MethodsCross-country comparative analysis of reforms on nurse prescribing, based on an expert survey (TaskShift2Nurses Survey) and an OECD study. Country experts provided country-specific information, which was complemented with the peer-reviewed and grey literature. The analysis was based on policy and thematic analyses.ResultsIn Europe, as of 2019, a total of 13 countries have adopted laws on nurse prescribing, of which 12 apply nationwide (Cyprus, Denmark, Estonia, Finland, France, Ireland, Netherlands, Norway, Poland, Spain, Sweden, United Kingdom (UK)) and one regionally, to the Canton Vaud (Switzerland). Eight countries adopted laws since 2010. The extent of prescribing rights ranged from nearly all medicines within nurses’ specialisations (Ireland for nurse prescribers, Netherlands for nurse specialists, UK for independent nurse prescribers) to a limited set of medicines (Cyprus, Denmark, Estonia, Finland, France, Norway, Poland, Spain, Sweden). All countries have regulatory and minimum educational requirements in place to ensure patient safety; the majority require some form of physician oversight.ConclusionsThe role of nurses has expanded in Europe over the last decade, as demonstrated by the adoption of new laws on prescribing rights.

Jesus Guerrero, Izzat Alsmadi

Within the text analysis and processing fields, generated text attacks have been made easier to create than ever before. To combat these attacks open sourcing models and datasets have become a major trend to create automated detection algorithms in defense of authenticity. For this purpose, synthetic text detection has become an increasingly viable topic of research. This review is written for the purpose of creating a snapshot of the state of current literature and easing the barrier to entry for future authors. Towards that goal, we identified few research trends and challenges in this field.

Yasmeen Anjeer Alshehhi, Mohamed Abdelrazek, Alessio Bonti

Personal data cover multiple aspects of our daily life and activities, including health, finance, social, Internet, Etc. Personal data visualisations aim to improve the user experience when exploring these large amounts of personal data and potentially provide insights to assist individuals in their decision making and achieving goals. People with different backgrounds, gender and ages usually need to access their data on their mobile devices. Although there are many personal tracking apps, the user experience when using these apps and visualisations is not evaluated yet. There are publications on personal data visualisation in the literature. Still, no systematic literature review investigated the gaps in this area to assist in developing new personal data visualisation techniques focusing on user experience. In this systematic literature review, we considered studies published between 2010 and 2020 in three online databases. We screened 195 studies and identified 29 papers that met our inclusion criteria. Our key findings are various types of personal data, and users have been addressed well in the found papers, including health, sport, diet, Driving habits, lifelogging, productivity, Etc. The user types range from naive users to expert and developers users based on the experiment's target. However, mobile device capabilities and limitations regarding data visualisation tasks have not been well addressed. There are no studies on the best practices of personal data visualisation on mobile devices, assessment frameworks for data visualisation, or design frameworks for personal data visualisations

Ishika Sahni, Araftoz Kaur

It is expected that the creation of next-generation wireless networks would result in the availability of high-speed and low-latency connectivity for every part of our life. As a result, it is important that the network is secure. The network's security environment has grown more complicated as a result of the growing number of devices and the diversity of services that 5G will provide. This is why it is important that the development of effective security solutions is carried out early. Our findings of this review have revealed the various directions that will be pursued in the development of next-generation wireless networks. Some of these include the use of Artificial Intelligence and Software Defined Mobile Networks. The threat environment for 5G networks, security weaknesses in the new technology paradigms that 5G will embrace, and provided solutions presented in the key studies in the field of 5G cyber security are all described in this systematic literature review for prospective researchers. Future research directions to protect wireless networks beyond 5G are also covered.

Giovanni Maria Biancofiore, Yashar Deldjoo, Tommaso Di Noia et al.

Question answering systems are recognized as popular and frequently effective means of information seeking on the web. In such systems, information seekers can receive a concise response to their query by presenting their questions in natural language. Interactive question answering is a recently proposed and increasingly popular solution that resides at the intersection of question answering and dialogue systems. On the one hand, the user can ask questions in normal language and locate the actual response to her inquiry; on the other hand, the system can prolong the question-answering session into a dialogue if there are multiple probable replies, very few, or ambiguities in the initial request. By permitting the user to ask more questions, interactive question answering enables users to dynamically interact with the system and receive more precise results. This survey offers a detailed overview of the interactive question-answering methods that are prevalent in current literature. It begins by explaining the foundational principles of question-answering systems, hence defining new notations and taxonomies to combine all identified works inside a unified framework. The reviewed published work on interactive question-answering systems is then presented and examined in terms of its proposed methodology, evaluation approaches, and dataset/application domain. We also describe trends surrounding specific tasks and issues raised by the community, so shedding light on the future interests of scholars. Our work is further supported by a GitHub page with a synthesis of all the major topics covered in this literature study. https://sisinflab.github.io/interactive-question-answering-systems-survey/

Vinicius dos Santos, Rick Kazman, Rafael Capilla et al.

Systematic literature reviews (SLR) have been increasingly conducted in software engineering and they provide significant benefits in terms of summarizing the state of the research. The process of conducting SLR is complex, involving several activities and consuming considerable effort and time from researchers. Researchers often skip or poorly conduct essential activities, which introduce threats to validity, resulting in lower-quality SLR. But researchers are often unaware of what they could do to mature their SLR process, thus improving the SLR quality. The main goal of this paper is to introduce a maturity model for the SLR process named MM4SLR. To this end, we were inspired by well-known models like CMMI (Capability Maturity Model Integration). We first identified 39 key practices for SLR from the literature and grouped them into nine goals that were further grouped into five process areas. We then organized the process areas into five maturity levels which compose our model. Our proof of concept, applying the MM4SLR to four published SLR showed that the MM4SLR is suitable for appraising SLR and can identify important flaws in SLR quality. MM4SLR can therefore support researchers in creating their SLR processes and selecting practices that could be adopted to mature their processes.

Yannick Gouchan