Results 61 to 70 of about 3,377 (218)

Learning and recall differentiated in serial learning [PDF]

open access: yesPsychonomic Science, 1969
In a serial learning experiment in which the first item was made unique, the controls learned the list in the usual manner. For the experimental group, each trial began at a different, randomly chosen syllable. The results show that (a) acquisition is impaired and there is a different curve for the experimental group; (b) the unique item has an ...
Stephen C. Woods, Michael L. Epstein
openaire   +1 more source

TRANSFORMATECH: INTERACTIVE LEARNING WEBSITE BASED ON CHALLENGE-BASED DIFFERENTIATED LEARNING INTEGRATED WITH SCRATCH FEATURING BATIK NUSANTARA TO OPTIMIZE STUDENTS' COMPUTATIONAL THINKING SKILLS

open access: yesPrima: Jurnal Pendidikan Matematika
Computational thinking (CT) has become a vital competence in mathematics education, yet students in Indonesia often demonstrate low proficiency in this area, particularly in abstraction and algorithmic thinking.
Resty Kartika Sari   +5 more
doaj   +1 more source

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

open access: yesMolecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur   +11 more
wiley   +1 more source

CEACAM1 participation in breast cancer progression

open access: yesMolecular Oncology, EarlyView.
In invasive breast cancer (BC), CEACAM1 shifts from an apical to a uniform membranous/cytoplasmic pattern, or is lost, as tumors dedifferentiate, inversely tracking the Ki‐67 proliferative index. In MCF‐7 cells, only CEACAM1‐4L suppresses proliferation, repressing cell cycle and growth factor genes.
Mykola Lyndin   +3 more
wiley   +1 more source

Partial FAK suppression promotes tumor growth, an effect reversed by macrophage p110δ PI3K inactivation

open access: yesMolecular Oncology, EarlyView.
Partial inhibition of focal adhesion kinase (FAK) can paradoxically promote tumor growth, rather than simply producing a weaker antitumor effect than that observed with strong FAK suppression. In breast cancer and melanoma models, targeting p110δ PI3K, particularly in macrophages, counteracted these tumor‐promoting effects, highlighting the importance ...
Lydia Xenou   +4 more
wiley   +1 more source

Learning to Differentiate

open access: yes, 2020
Artificial neural networks together with associated computational libraries provide a powerful framework for constructing both classification and regression algorithms. In this paper we use neural networks to design linear and non-linear discrete differential operators.
Ålund, Oskar   +2 more
openaire   +1 more source

Development of Teaching Materials Based on Differentiated Learning to Improve Critical Thinking Dimensions of The Pancasila Learner Profile

open access: yesJurnal Kependidikan
This research aims to develop teaching materials based on differentiated learning to improve critical thinking dimensions of the Pancasila Learner Profile for students in elementary schools.
Farhania Maulida   +2 more
doaj   +1 more source

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

open access: yesMolecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic   +10 more
wiley   +1 more source

Learning by solving differential equations

open access: yesCoRR
Modern deep learning algorithms use variations of gradient descent as their main learning methods. Gradient descent can be understood as the simplest Ordinary Differential Equation (ODE) solver; namely, the Euler method applied to the gradient flow differential equation.
Benoit Dherin   +5 more
openaire   +3 more sources

Innovative Differentiated Learning for Inclusive Schools : Supporting Students with Special Needs

open access: yesJurnal Kependidikan
: This study aims to analyze differentiated learning innovations in the context of inclusive education. The main focus is how content, process and product differentiation strategies are implemented to accommodate student diversity and the role of Special
Asrorul Mais, Lailil Aflahkul Yaum
doaj   +1 more source

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