Results 121 to 130 of about 4,825 (248)

Analyzing Non‐Random Selectivity in Online Job Advertisements Using Eurostat Benchmark Data and Generalized Sample Selection Models: An Application to EU Regional Labor Markets

LABOUR, Volume 40, Issue 2, Page 131-161, June 2026.
ABSTRACT The present paper provides an overall framework to afford the problem of non‐representativeness and non‐random selectivity arising from online job ads data, using Generalized sample selection models and Eurostat benchmark data. We jointly model the outcome intensity (number of online job ads in observed profiles, whose levels are defined by ...
Pietro Giorgio Lovaglio, Mario Mezzanzanica   +1 more
wiley   +1 more source

Mapping the Cerebral Organoid Landscape: A Systematic Review of Preclinical 3D Models in Neuroscience

Advanced Healthcare Materials, Volume 15, Issue 18, 15 May 2026.
Cerebral organoids are transforming brain research, yet the field remains fragmented. This comprehensive systematic review maps 738 studies published between 2014 and 2024 to uncover trends, gaps, and opportunities across neuroscience. Introducing OrganoidMap—an interactive, open‐access platform to explore and compare models—this work enables ...
Anna Wolfram, Vanessa Arnold, Maik Wolfram‐Schauerte, Anastassiya Moskalchuk, Caroline Trust, Marie Vontz, Mona Scheurenbrand, Vijayasarathy Sampath‐Kumar, Sogand Ahari, Carlos Romero‐Nieto, Lisa Sevenich   +10 more
wiley   +1 more source

The ITGB2‐COPS3‐SOX2 Axis and SOX2 Liquid‐Liquid Phase Separation: Dual Mechanisms Governing Osteosarcoma Stemness

Advanced Science, Volume 13, Issue 29, 22 May 2026.
Osteosarcoma stemness is driven by the ITGB2‐COPS3‐SOX2 signaling axis. This study reveals that nuclear COPS3 stabilizes SOX2, which in turn undergoes liquid‐liquid phase separation to promote stemness. Based on this mechanism, a novel COPS3 inhibitor, Z‐5891, was developed, effectively suppressing tumor growth and stemness in vivo, offering a ...
Lei Guo, Zhiqing Zhao, Wei Wang, Jianfang Niu, Bing Wang, Yunfei Lin, Wei Guo, Taiqiang Yan   +7 more
wiley   +1 more source

Information retrieval or document retrieval? Terminological confusions and unrealistic goals in information science, exemplified in relation to generative artificial intelligence

Journal of the Association for Information Science and Technology, Volume 77, Issue 5, Page 714-726, May 2026.
Abstract ChatGPT and related technologies have revived an old issue in information science (IS) concerning information retrieval (IR) versus document retrieval. Since 1950, the term IR has primarily been used as a misnomer for document retrieval. This problematic terminology reflects a desire to go beyond documents and provide, in response to user ...
Birger Hjørland
wiley   +1 more source

Advancing Sustainable Development in Manufacturing: A Strategic Framework for Overcoming Green–Lean Implementation Barriers

Business Strategy and the Environment, Volume 35, Issue 4, Page 5320-5343, May 2026.
ABSTRACT Manufacturing's transition to sustainable development depends on integrating green with lean under credible environmental policy and stakeholder engagement. Although benefits are well established, the literature underspecifies implementation barriers and their prioritisation. This study identifies, structures, and prioritises barriers to green–
Jose Arturo Garza‐Reyes, Andrew Defanto, Ranjit Roy Ghatak, Rohit Joshi, Walid al Saad   +4 more
wiley   +1 more source

Engineering a Scalable Laboratory Infrastructure for Assembly Language Scaffolding: Design and Deployment of a Locally Optimized GenAI Assistant for the CODE‐2 Educational Architecture

Computer Applications in Engineering Education, Volume 34, Issue 3, May 2026.
ABSTRACT The transition from high‐level programming to assembly language constitutes a well‐documented pedagogical bottleneck in computer engineering curricula, particularly in large‐cohort laboratory settings where individualized scaffolding cannot scale.
Federico Garcia Crespi
wiley   +1 more source

Batch Size Effects on Mid‐2025 State‐of‐the‐Art Large Language Model Performance in Automated Title and Abstract Screening

Cochrane Evidence Synthesis and Methods, Volume 4, Issue 3, May 2026.
ABSTRACT Background Manual abstract screening is a primary bottleneck in evidence synthesis. Emerging evidence suggests that large language models (LLMs) can automate this task, but their performance when processing multiple references simultaneously in “batches” is uncertain.
Petter Fagerberg, Oscar Sallander, Kim Vikhe Patil, Anders Berg, Anastasia Nyman, Natalia Borg, Thomas Lindén   +6 more
wiley   +1 more source

Accelerated‐USE: A Benchmark Framework for GPU‐Driven Graph Neural Network Training

Concurrency and Computation: Practice and Experience, Volume 38, Issue 9, May 2026.
ABSTRACT Graph processing is used in many domains to extract knowledge from real‐world data. With the rise of deep neural networks and scaled compute infrastructure in artificial intelligence (AI), specialized techniques emerged to leverage graphs in applications such as recommendation systems and social networks.
Lucas de Angelo Martins Ribeiro, Willian Borges de Lemos, Vanessa Telles da Silva, Marcelo de Gomensoro Malheiros, Nelson Lopes Duarte Filho, Marcelo Rita Pias   +5 more
wiley   +1 more source

Provably-Secure Public Auditing with Deduplication

KSII Transactions on Internet and Information Systems, 2017
Dongmin Kim, Ik Rae Jeong
openaire   +1 more source

Target Capture Sequencing Provides Insights Into Hybridogenetic Water Frogs

Ecology and Evolution, Volume 16, Issue 5, May 2026.
The genomics of European frogs of the genus Pelophylax are intriguing due to their propensity to hybridise, the prevalence of polyploidy, and the unusual hemiclonal hybridogenetic complexes formed in many populations. This study examines the use of target capture sequencing using the Frog Cap bait set to investigate these complex systems.
Lisanne van Veldhuijzen, Maciej Pabijan, Tariq Stark, Richard P. J. H. Struijk, Ben Wielstra, James France   +5 more
wiley   +1 more source