Results 121 to 130 of about 934,547 (259)

Facial cosmetic therapy use amongst patients with systemic sclerosis: an Australian cohort study

Arthritis Care &Research, Accepted Article.
Objective Systemic sclerosis (SSc) is associated with numerous facial manifestations for which patients may engage in cosmetic therapies. It is unclear how patients with SSc use these therapies. This study sought to characterise patient engagement and experiences with cosmetic therapies for SSc‐related and non‐SSc‐related facial changes.
Zachary Warren, Diane Apostolopoulos, Gene‐Siew Ngian, Amanda M Saracino, Laura Ross, Nava Ferdowsi, Jennifer Walker, Cindy Hall, Kim Griggs, Susanna Proudman, Wendy Stevens, Joanne Sahhar   +11 more
wiley   +1 more source

Determinants of efficiency in state-chartered financial institutions: Why financial education and freedom matter. [PDF]

Heliyon, 2020
de Abreu ES, Kimura H.
europepmc   +1 more source

β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations

Advanced Biology, Volume 9, Issue 3, March 2025.
Ammonia, detoxified by the liver into urea and glutamine, impacts autophagy differently at varying levels. Low ammonia activates autophagy via c‐Myc and β‐catenin, while high levels suppress it. Using Huh7 cells and Spf‐ash mice, c‐Myc's role in cytoprotective autophagy is revealed, offering insights into hyperammonemia and potential therapeutic ...
S. Sergio, B. Spedicato, G. Corallo, A. Inguscio, M. Greco, D. Musarò, D. Vergara, A. F. Muro, G. De Sabbata, L. R. Soria, N. Brunetti Pierri, M. Maffia   +11 more
wiley   +1 more source

Digital Financial Literacy and Financial Well-Being Among MSMEs: A Multi-Group Analysis and Implications for Higher Education Finance

Educational Process: International Journal
Background/purpose. The digital transformation of the financial system has reshaped not only the practices of Micro, Small, and Medium Enterprises (MSMEs) but also the educational needs of students preparing for future entrepreneurship.
Andriansyah, Isfenti Sadalia, Khaira Amalia Fachrudin, Syahyunan   +3 more
doaj   +1 more source

Financial Education and Financial Access for Transnational Households: Field Experimental Evidence from the Philippines. [PDF]

Econ Dev Cult Change, 2020
Abarcar P, Barua R, Yang D.
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Financial Education for Female Foreign Domestic Workers in Singapore. [PDF]

Econ Educ Rev, 2020
Barua R, Shastry GK, Yang D.
europepmc   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source