Results 71 to 80 of about 2,716,934 (278)

Why human connection is the true metric of research success

FEBS Open Bio, EarlyView.
Human‐centred mentorship can be shaped by mentor attributes, actions, intrinsic drive and career ambition. Drawing on reflections across Singapore and France, as well as workshop insights from FEBS‐IUBMB ENABLE 2024, this article shows that human‐centred mentorship creates the conditions for sustainable growth, well‐being and retention in research ...
Timothy Lin Yun Tan, Mattias Wei Ren Kon, Xavier Coumoul, Fun Man Fung   +3 more
wiley   +1 more source

Experimental-analytical and digital based investigation of 3D printed sandwich sand mold used for precast structure

Case Studies in Construction Materials
The 3D printing technique for sand mold exhibited the good response of precast concrete structure manufacturing process. The designed sandwich core structure, including solid core, diamond core, honeycomb core, pyramid core and round O core were ...
Khoa Vo Anh Pham, Hyoseo Ahn, Jiuk Shin, Gayoon Lee, Kihak Lee   +4 more
doaj   +1 more source

Emerging insights into CC and CXC chemokines and their receptors in Mycobacterium tuberculosis infection

FEBS Open Bio, EarlyView.
The dual roles of CC and CXC chemokines in distinguishing active, latent, and subclinical tuberculosis were reviewed, along with an evaluation of their potential as diagnostic biomarkers and therapeutic targets to advance precision medicine in tuberculosis management. The graphical abstract was generated with AI assistance (Gemini 3.0).
Xuying Yin, Dangsheng Xiao, Jiezuan Yang
wiley   +1 more source

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Deep learning? What deep learning?

South African Journal of Higher Education, 2003
In teaching generally over the past twenty years, there has been a move towards teaching methods that encourage deep, rather than surface approaches to learning. The reason for this being that students, who adopt a deep approach to learning are considered to have learning outcomes of a better quality and desirability than those who adopt a surface ...
openaire   +2 more sources

Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer

Aging and Cancer, EarlyView.
Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss, Alexis C. Wardell, Allison M. Deal, Kirsten A. Nyrop, Allison Ross, Yara G. Abdou, Jeffrey D. Aldrich, Lisa A. Cary, E. Claire Dees, Katherine E. Reeder‐Hayes, Emily M. Ray, Natalia Mitin, Denis Tsygankov   +12 more
wiley   +1 more source

Deep Learning in Science

CoRR, 2020
Much of the recent success of Artificial Intelligence (AI) has been spurred on by impressive achievements within a broader family of machine learning methods, commonly referred to as Deep Learning (DL). This paper provides insights on the diffusion and impact of DL in science.
Stefano Bianchini, Moritz Müller, Pierre Pelletier   +2 more
openaire   +2 more sources

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

Deep Learning With DAGs

SSRN Electronic Journal
Social science theories often postulate systems of causal relationships among variables, which are commonly represented using directed acyclic graphs (DAGs). As non-parametric causal models, DAGs require no assumptions about the functional form of the hypothesized relationships.
Sourabh Balgi, Adel Daoud, Jose M. Peña, Geoffrey T. Wodtke, Jesse Zhou   +4 more
openaire   +2 more sources

Unlocking stroke prediction: Harnessing projection-based statistical feature extraction with ML algorithms

Heliyon
Non-communicable diseases, such as cardiovascular disease, cancer, chronic respiratory diseases, and diabetes, are responsible for approximately 71% of all deaths worldwide.
Saad Sahriar, Sanjida Akther, Jannatul Mauya, Ruhul Amin, Md Shahajada Mia, Sabba Ruhi, Md Shamim Reza   +6 more
doaj   +1 more source