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

Qiyao Wang, Hongbo Wang, Longze Chen et al.

Scientific idea generation (SIG) is critical to AI-driven autonomous research, yet existing approaches are often constrained by a static retrieval-then-generation paradigm, leading to homogeneous and insufficiently divergent ideas. In this work, we propose FlowPIE, a tightly coupled retrieval-generation framework that treats literature exploration and idea generation as a co-evolving process. FlowPIE expands literature trajectories via a flow-guided Monte Carlo Tree Search (MCTS) inspired by GFlowNets, using the quality of current ideas assessed by an LLM-based generative reward model (GRM) as a supervised signal to guide adaptive retrieval and construct a diverse, high-quality initial population. Based on this population, FlowPIE models idea generation as a test-time idea evolution process, applying selection, crossover, and mutation with the isolation island paradigm and GRM-based fitness computation to incorporate cross-domain knowledge. It effectively mitigates the information cocoons arising from over-reliance on parametric knowledge and static literature. Extensive evaluations demonstrate that FlowPIE consistently produces ideas with higher novelty, feasibility and diversity compared to strong LLM-based and agent-based frameworks, while enabling reward scaling during test time.

Daniil Sherki, Daniil Merkulov, Alexandra Savina et al.

We present PERELMAN (PipEline foR sciEntific Literature Meta-ANalysis), an agentic framework designed to extract specific information from a large corpus of scientific articles to support large-scale literature reviews and meta-analyses. Our central goal is to reliably transform heterogeneous article content into a unified, machine-readable representation. PERELMAN first elicits domain knowledge-including target variables, inclusion criteria, units, and normalization rules-through a structured dialogue with a subject-matter expert. This domain knowledge is then reused across multiple stages of the pipeline and guides coordinated agents in extracting evidence from narrative text, tables, and figures, enabling consistent aggregation across studies. In order to assess reproducibility and validate our implementation, we evaluate the system on the task of reproducing the meta-analysis of layered Li-ion cathode properties (NMC811 material). We describe our solution, which has the potential to reduce the time required to prepare meta-analyses from months to minutes.

Hein Htet, Amgad Ahmed Ali Ibrahim, Yutaka Sasaki et al.

The oxygen reduction reaction (ORR) catalyst plays a critical role in enhancing fuel cell efficiency, making it a key focus in material science research. However, extracting structured information about ORR catalysts from vast scientific literature remains a significant challenge due to the complexity and diversity of textual data. In this study, we propose a named entity recognition (NER) and relation extraction (RE) approach using DyGIE++ with multiple pre-trained BERT variants, including MatSciBERT and PubMedBERT, to extract ORR catalyst-related information from the scientific literature, which is compiled into a fuel cell corpus for materials informatics (FC-CoMIcs). A comprehensive dataset was constructed manually by identifying 12 critical entities and two relationship types between pairs of the entities. Our methodology involves data annotation, integration, and fine-tuning of transformer-based models to enhance information extraction accuracy. We assess the impact of different BERT variants on extraction performance and investigate the effects of annotation consistency. Experimental evaluations demonstrate that the fine-tuned PubMedBERT model achieves the highest NER F1-score of 82.19% and the MatSciBERT model attains the best RE F1-score of 66.10%. Furthermore, the comparison with human annotators highlights the reliability of fine-tuned models for ORR catalyst extraction, demonstrating their potential for scalable and automated literature analysis. The results indicate that domain-specific BERT models outperform general scientific models like BlueBERT for ORR catalyst extraction.

Duarte Sampaio de Almeida, Fernando Brito e Abreu, Inês Boavida-Portugal

Purpose: This systematic literature review (SLR) characterizes the current state of the art on digital twinning (DT) technology in tourism-related applications. We aim to evaluate the types of DTs described in the literature, identifying their purposes, the areas of tourism where they have been proposed, their main components, and possible future directions based on current work. Design/methodology/approach: We conducted this SLR with bibliometric analysis based on an existing, validated methodology. Thirty-four peer-reviewed studies from three major scientific databases were selected for review. They were categorized using a taxonomy that included tourism type, purpose, spatial scale, data sources, data linkage, visualization, and application. Findings: The topic is at an early, evolving stage, as the oldest study found dates back to 2021. Most reviewed studies deal with cultural tourism, focusing on digitising cultural heritage. Destination management is the primary purpose of these DTs, with mainly site-level spatial scales. In many studies, the physical-digital data linkage is unilateral, lacking twin synchronization. In most DTs considered bilateral, the linkage is indirect. There are more applied than theoretical studies, suggesting progress in applying DTs in the field. Finally, there is an extensive research gap regarding DT technology in tourism, which is worth filling. Originality/Value: This paper presents a novel SLR with a bibliometric analysis of DTs' applied and theoretical application in tourism. Each reviewed publication is assessed and characterized, identifying the current state of the topic, possible research gaps, and future directions.

D. Kringos, W. Boerma, Y. Bourgueil et al.

Christian Näther, Daniel Herzinger, Stefan-Lukas Gazdag et al.

Networks such as the Internet are essential for our connected world. Quantum computing poses a threat to this heterogeneous infrastructure since it threatens fundamental security mechanisms. Therefore, a migration to post-quantum-cryptography (PQC) is necessary for networks and their components. At the moment, there is little knowledge on how such migrations should be structured and implemented in practice. Our systematic literature review addresses migration approaches for IP networks towards PQC. It surveys papers about the migration process and exemplary real-world software system migrations. On the process side, we found that terminology, migration steps, and roles are not defined precisely or consistently across the literature. Still, we identified four major phases and appropriate substeps which we matched with also emerging archetypes of roles. In terms of real-world migrations, we see that reports used several different PQC implementations and hybrid solutions for migrations of systems belonging to a wide range of system types. Across all papers we noticed three major challenges for adopters: missing experience of PQC and a high realization effort, concerns about the security of the upcoming system, and finally, high complexity. Our findings indicate that recent standardization efforts already push quantum-safe networking forward. However, the literature is still not in consensus about definitions and best practices. Implementations are mostly experimental and not necessarily practical, leading to an overall chaotic situation. To better grasp this fast moving field of (applied) research, our systematic literature review provides a comprehensive overview of its current state and serves as a starting point for delving into the matter of PQC migration.

Sarah Farahdel, Chun Wang, Anjali Awasthi

This systematic literature review explores sustainability assessment frameworks (SAFs) across diverse industries. The review focuses on SAF design approaches including the methods used for Sustainability Indicator (SI) selection, relative importance assessment, and interdependency analysis. Various methods, including literature reviews, stakeholder interviews, questionnaires, Pareto analysis, SMART approach, and adherence to sustainability standards, contribute to the complex SI selection process. Fuzzy-AHP stands out as a robust technique for assessing relative SI importance. While dynamic sustainability and performance indices are essential, methods like DEMATEL, VIKOR, correlation analysis, and causal models for interdependency assessment exhibit static limitations. The review presents strengths and limitations of SAFs, addressing gaps in design approaches and contributing to a comprehensive understanding. The insights of this review aim to benefit policymakers, administrators, leaders, and researchers, fostering sustainability practices. Future research recommendations include exploring multi-criteria decision-making models and hybrid approaches, extending sustainability evaluation across organizational levels and supply chains. Emphasizing adaptability to industry specifics and dynamic global adjustments is proposed for holistic sustainability practices, further enhancing organizational sustainability.

Sebastian Pagel, Michael Jirasek, Leroy Cronin

Chemputation is the process of programming chemical robots to do experiments using a universal symbolic language, but the literature can be error prone and hard to read due to ambiguities. Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains, including natural language processing, robotic control, and more recently, chemistry. Despite significant advancements in standardizing the reporting and collection of synthetic chemistry data, the automatic reproduction of reported syntheses remains a labour-intensive task. In this work, we introduce an LLM-based chemical research agent workflow designed for the automatic validation of synthetic literature procedures. Our workflow can autonomously extract synthetic procedures and analytical data from extensive documents, translate these procedures into universal XDL code, simulate the execution of the procedure in a hardware-specific setup, and ultimately execute the procedure on an XDL-controlled robotic system for synthetic chemistry. This demonstrates the potential of LLM-based workflows for autonomous chemical synthesis with Chemputers. Due to the abstraction of XDL this approach is safe, secure, and scalable since hallucinations will not be chemputable and the XDL can be both verified and encrypted. Unlike previous efforts, which either addressed only a limited portion of the workflow, relied on inflexible hard-coded rules, or lacked validation in physical systems, our approach provides four realistic examples of syntheses directly executed from synthetic literature. We anticipate that our workflow will significantly enhance automation in robotically driven synthetic chemistry research, streamline data extraction, improve the reproducibility, scalability, and safety of synthetic and experimental chemistry.

A. Calafat, Fernando García, M. Juan et al.

Claudia C. Ramirez, Y. Farmer, Marie-Ève Bouthillier

To reduce the arbitrariness in the allocation of rare resources in intensive care units (ICU) in the context of the pandemic, tiebreakers were considered in some COVID-19 triage algorithms. They were also contemplated to facilitate the tragic decisions of healthcare workers when faced with two patients with similar prognosis and only one ICU bed available. Little is known about the public's perspective on tiebreakers. To consolidate the available scientific literature on public consultations, particularly on tiebreakers and their underlying values. Also, to obtain an overview of the key arguments presented by the participating public and to identify potential gaps related to this topic. The steps described by Arksey and O’Malley was the preferred method to our approach. Seven electronic databases were searched from January 2020 to April 2022, using keywords for each database: PubMed, Medline, EMBASE, Web of Science, PsycINFO, EBM reviews, CINAHL complete. We also searched in Google and Google Scholar, and in the references of the articles found. Our analysis was mainly qualitative. A thematic analysis was performed to consider the public’s perspectives on tiebreakers and their underlying values, according to these studies. Of 477 publications found, 20 were selected. They carried out public consultations through various methods: surveys (80%), interviews (20%), deliberative processes (15%) and others (5%) in various countries: Australia, Brazil, Canada, China, France, Germany, India, Iran, Italy, Japan, Korea, Netherlands, Portugal, Spain, Switzerland, Thailand, United Kingdom, and United States. Five themes emerged from our analysis. The public favored the life cycle (50%) and absolute age (45%) as a tiebreaker. Other values considered important were reciprocity, solidarity, equality, instrumental value, patient merit, efficiency, and stewardship. Among the new findings were a preference for patient nationality and those affected by COVID-19. There is a preference for favoring younger patients over older patients when there is a tie between similar patients, with a slight tendency to favor intergenerational equity. Variability was found in the public’s perspectives on tiebreakers and their values. This variability was related to socio-cultural and religious factors. More studies are needed to understand the public's perspective on tiebreakers.

Donato Di Carlo, C. Ibsen, Oscar Molina

This special issue (SI) brings the industrial relations scholarship on the public sector into dialogue with the comparative political economy (CPE) literature on growth models/regimes. While the former has paid great attention to the public sector, in CPE the public sector has been analysed less, and mostly as subaltern to the export-sector’s actors, interests and institutions. We posit that the public sector matters for CPE in its own right for three reasons. First, the state remains today the single largest employer in virtually every European economy, providing incomes to a large segment of the middle class. Second, public employers’ wage bill – one of the largest items of governments’ current expenditures – is funded by the taxpayers. Hence, public sector wage policy is fiscal policy, ultimately pursued by public/political employers. Third, public employers are simultaneously public managers and political sovereigns acting in the shadow of hierarchy. Case-study contributions to the SI detail how these insights matter within different European growth regimes: (1) the Mediterranean demand-led growth regime (France, Italy, Spain and Portugal), (2) the German export-led growth regime, (3) the Nordic balanced growth regime (Denmark and Sweden) and (4) the FDI-led Eastern European growth regime (Czechia and Slovakia).

Natalia Nair Soares de Oliveira, F. Hellmann, P. Cantista et al.

O. E. Olorunmoteni, F. Gómez-Olivé, B. Popoola et al.

Introduction Problematic sleep is a major threat to health and quality of life among adolescents. Hence, to provide directions for research and interventions, there is a need to examine the literature on adolescent sleep health in Africa. However, available studies on adolescent sleep health in Africa have not been properly mapped. Thus, this scoping review aims to investigate the extent and type of available evidence concerning sleep health among adolescents in Africa and to highlight the relationship of adolescent sleep health with adverse mental health outcomes and cardiometabolic risk factors. The review will further highlight areas of agreement and controversies on adolescent sleep health, and identify evidence gaps that require research attention across the continent. Methods and analysis This scoping review will be conducted using Arksey and O’Malley’s six-step procedure. Thus, we have prepared this protocol according to the framework for scoping reviews developed by the Joanna Briggs Institute. To identify eligible studies, we will search MEDLINE, Scopus, PsycINFO, AJOL, JSTOR, HINARI and Google Scholar. The review will include all published articles in English, French, Spanish, Portuguese and Italian languages on adolescent sleep health in Africa from the inception of the databases, while relevant information will be extracted from included studies using an adapted data extraction tool. The results will be presented using tables and charts as appropriate. Ethics and dissemination The scoping review does not require ethical approval because the publications to be used for the review are publicly available and the study does not involve contact with humans or other animals as research participants. Furthermore, clinical records will not be used for the study. Upon completion, findings from the study will be disseminated through presentations at scientific meetings and publication in a relevant peer-reviewed journal. Scoping review registration Open Science Framework (https://osf.io/5sjwq/).

Deep Kumar Kirtania

The main objective of this study is to conduct a bibliometric analysis of scholarly publications of Authorship Pattern. The present study covers 1723 research papers published in the area of authorship pattern and indexed in Scopus database from the year 2013 to 2022. These research publications considered for the present study have been analysed based on their year wise growth, pattern of authorship, times citations, type of publication, most productive publication source as well as countries and institutions. The study shows the positive growth of the literatures with collaborative authorship pattern and good citation status. This original research paper will be helpful to the researchers of library and information science, especially who are working in the area of bibliometrics studies.

Qiao Jin, Ashley Shin, Zhiyong Lu

Queries with similar information needs tend to have similar document clicks, especially in biomedical literature search engines where queries are generally short and top documents account for most of the total clicks. Motivated by this, we present a novel architecture for biomedical literature search, namely Log-Augmented DEnse Retrieval (LADER), which is a simple plug-in module that augments a dense retriever with the click logs retrieved from similar training queries. Specifically, LADER finds both similar documents and queries to the given query by a dense retriever. Then, LADER scores relevant (clicked) documents of similar queries weighted by their similarity to the input query. The final document scores by LADER are the average of (1) the document similarity scores from the dense retriever and (2) the aggregated document scores from the click logs of similar queries. Despite its simplicity, LADER achieves new state-of-the-art (SOTA) performance on TripClick, a recently released benchmark for biomedical literature retrieval. On the frequent (HEAD) queries, LADER largely outperforms the best retrieval model by 39% relative NDCG@10 (0.338 v.s. 0.243). LADER also achieves better performance on the less frequent (TORSO) queries with 11% relative NDCG@10 improvement over the previous SOTA (0.303 v.s. 0.272). On the rare (TAIL) queries where similar queries are scarce, LADER still compares favorably to the previous SOTA method (NDCG@10: 0.310 v.s. 0.295). On all queries, LADER can improve the performance of a dense retriever by 24%-37% relative NDCG@10 while not requiring additional training, and further performance improvement is expected from more logs. Our regression analysis has shown that queries that are more frequent, have higher entropy of query similarity and lower entropy of document similarity, tend to benefit more from log augmentation.

Arham Muslim, Mohamed Amine Chatti, Mouadh Guesmi

Open Learning Analytics (OLA) is an emerging research area that aims at improving learning efficiency and effectiveness in lifelong learning environments. OLA employs multiple methods to draw value from a wide range of educational data coming from various learning environments and contexts in order to gain insight into the learning processes of different stakeholders. As the research field is still relatively young, only a few technical platforms are available and a common understanding of requirements is lacking. This paper provides a systematic literature review of tools available in the learning analytics literature from 2011-2019 with an eye on their support for openness. 137 tools from nine academic databases are collected to form the base for this review. The analysis of selected tools is performed based on four dimensions, namely 'Data, Environments, Context (What?)', 'Stakeholders (Who?)', 'Objectives (Why?)', and 'Methods (How?)'. Moreover, five well-known OLA frameworks available in the community are systematically compared. The review concludes by eliciting the main requirements for an effective OLA platform and by identifying key challenges and future lines of work in this emerging field.

F. Tamarozzi, M. Legnardi, Andrea V. Fittipaldo et al.

Cystic echinococcosis (CE) is a neglected zoonosis caused by infection with the cestode Echinococcus granulosus sensu lato. We carried out a systematic literature review on E. granulosus s.l. human and animal (cattle, sheep, dog) infection in European Mediterranean and Balkan countries in 2000–2019, to provide a picture of its recent epidemiology in this endemic area. MEDLINE, EMBASE, Scopus, Google Scholar and Open Grey databases were searched. Included cases were: i) for humans, data from hospital records and imaging studies; ii) for dogs, data from necropsy and coprological studies; iii) for ruminants, cases based on slaughter inspection. The NUTS (Nomenclature of Territorial Units for Statistics) classification was used to categorize extracted data in epidemiological units, defined as data referred to one NUTS2 (basic region) in one year time. Data were then aggregated to NUTS1 level (major regions), calculating the average incidence value of included epidemiological units. For prevalence studies covering different epidemiological units, the pooled prevalence was estimated. Data were extracted from 79 publications, 25 on human infection (covering 437 epidemiological units), and 54 on animal infection (52 epidemiological units for cattle, 35 for sheep and 25 for dogs). At NUTS1 level, average annual incidence rates of human CE ranged from 0.10–7.74/100,000; pooled prevalence values ranged from 0.003–64.09% in cattle, 0.004–68.73% in sheep, and 0–31.86% in dogs. Southern and insular Italy, central Spain, Romania and Bulgaria reported the highest values. Bovine data showed a more similar pattern to human data compared to sheep and dogs. Limitation of evidence included the paucity of human prevalence studies, data heterogeneity, and the patchy geographical coverage, with lack of data especially for the Balkans. Our results confirm Italy, Spain, and Eastern Europe being the most affected areas, but data are extremely heterogeneous, geographical coverage very patchy, and human prevalence studies extremely scant. Results also highlight the notorious problem of underreporting of E. granulosus s.l. infection in both humans and animals.

Mara Gabbrielli, A. Perego, M. Acutis et al.

Cover crops provide agro-ecological services like erosion control, improvement of soil quality, reduction of nitrate leaching and weed control. Before planting the subsequent cash crop, cover crops need to be terminated with herbicides, mechanically or with the help of frost (winterkill). Winterkill termination is expected to increase its relevance in the next years, especially for organic farming due to limitations in the use of herbicides and for conservation agriculture cropping systems. Termination by frost depends on complex interactions between genotype, development stage and weather conditions. To understand these interactions for management purposes, crop frost damage models, whose review is the purpose of this article, can be very useful. A literature search led to the collection of eight frost damage models, mainly dedicated to winter wheat. Three of these models are described in detail because they appear suited to adaptation to cover crops. Indeed, they explicitly simulate frost tolerance acquisition and loss as influenced by development stage using a crop frost tolerance temperature, whose rate of variation depends on the processes of hardening and dehardening. This tolerance temperature is compared daily with environmental temperature to calculate frost damage to the vegetative organs. The three models, when applied to winter wheat in Canada, Norway and France, have shown good agreement between measured and simulated crop frost tolerance temperature (when declared, the root mean squared error was 2.4°C). To compare the behaviour of these models, we applied them in two locations with different climatic conditions (temperate climate: Sant’Angelo Lodigiano, Italy, and continental climate: Saskaatoon, Canada) with respect to frost tolerance acquisition. This comparison revealed that the three models provide different simulated dates for the frost damage event in the continental site, while they are more similar in the temperate site. In conclusion, we have shown that the reviewed models are potentially suitable for simulating cover crop frost damage. Highlights - Frost termination is very important for cover crops and needs to be simulated with crop models. - Lacking a cover crop frost damage model, we review eight models simulating damage of cash crops, namely cereals. - Three of these models are also applicable to cover crops and are described in more detail. - The simulated crop frost tolerance temperature decreases and increases with hardening and dehardening, respectively. - This tolerance temperature is compared with environmental temperature to calculate frost damage to the crop.

Sergio Chejfec

Priyank Sharma, Meet Patel, Apoorva Prasad

The Internet of Vehicles IoV commonly referred to as connected automobiles is a vast network that connects various entities including users sensors and vehicles They will connect across a network to lessen traffic accidents and improve both the security and safety of smart vehicles The Internet of Vehicles is subject to a wide variety of threats including spoofing attacks recognition attacks privacy attacks and verification attacks Our the primary concern when creating any new smart gadget is the users safety which will be improved by identifying solutions to the various cyber threats Therefore we will cover the security of smart automobiles in this literature review including their attacks and solutions.