Results 141 to 150 of about 229,699 (289)
We investigate size‐dependent CO selectivity on Ag nanoparticles, where optimized Ag loading achieves nearly 100% Faradaic Efficiency for CO at −100 mA·cm−2. In situ SERS and XPS reveal the crucial role of optimized loading in catalytic performance. The Ag/C catalyst further exhibits bifunctional activity, enabling efficient electrolysis of CO2 and ...
Venkata S. R. K. Tandava +16 more
wiley +1 more source
Pengaruh Model Pembelajaran Probing Prompting Terhadap Hasil Belajar Ditinjau Dari Self-Efficacy
This experimental research aims to find out whether or not: 1) the probing-prompting learning model affects learning achievement, 2) the self-efficafy affects learning achievement, and 3) the model affects the interaction between the learning model and ...
Viola Vesa Novena +1 more
doaj
The objective of this study is to examine the questioning behaviours and strategies used by EFL instructors to enhance reflective learning in the communicative English language skills course at Hawassa University, Ethiopia.
Kefyalew Woreta Haile +2 more
doaj +1 more source
Decomposed Prompting: Probing Multilingual Linguistic Structure Knowledge in Large Language Models
Probing the multilingual knowledge of linguistic structure in LLMs, often characterized as sequence labeling, faces challenges with maintaining output templates in current text-to-text prompting strategies. To solve this, we introduce a decomposed prompting approach for sequence labeling tasks.
Ercong Nie +6 more
openaire +3 more sources
We developed a patient‐derived, functional microfluidic model of the diffuse midline glioma (DMG) blood–brain–tumor barrier (BBTB) comprised of endothelial cells, astrocytes, pericytes, and tumor cells. The system forms perfusable microvasculature, reveals the BBTB retains vascular integrity, identifies DMG‐specific transcriptomic changes distinct from
Kimberly R. Bennett +7 more
wiley +1 more source
More Than a Score: Probing the Impact of Prompt Specificity on LLM Code Generation
State-of-the-art Large Language Models (LLMs) achieve high pass@1 on general benchmarks like HumanEval but underperform on specialized suites such as ParEval. Is this due to LLMs missing domain knowledge or insufficient prompt detail is given? To answer this, we introduce PartialOrderEval, which augments any code generation benchmark with a partial ...
Yangtian Zi, Harshitha Menon, Arjun Guha
openaire +4 more sources
PENERAPAN PROBING-PROMPTING LEARNING UNTUK MENINGKATKAN HASIL BELAJAR SISWA DI SEKOLAH DASAR
Abstrak Penelitian ini bertujuan untuk mendeskripsikan peningkatan aktivitas guru selama menerapan Probing-Prompting Learning, mendeskripsikan peningkatan aktivitas siswa selama menerapan Probing-Prompting Learning, dan mendeskripsikan hasil belajar yang
HENDRAWAN, TEGUH
core
Under NIR irradiation, PTCPP generates ROS to eliminate MRSA biofilms and promote M1 macrophage polarization for phagocytosis. After bacterial clearance, the material is phagocytosed by macrophages, shifting their polarization to M2 phenotype via metabolic reprogramming, which synergistically enhances anti‐infection therapy and wound healing.
Honghao Ma +13 more
wiley +1 more source
Silicone breast implants are presented as a model system for understanding polymer permeation in vivo. Rather than representing material failure, “gel bleed” emerges from solution–diffusion transport‐mediated. By integrating polymer architecture, physicochemical transport, and biointerfacial processes, this review provides a unified framework that ...
D. Bouyer +12 more
wiley +1 more source
UDMM-Discourse Probe: User Guide and Standard Prompt
A Brief Interpretive Guide: How Does the Tool Think? Core Idea: Discourse is not just words; it's a "predictive act." Our minds are "prediction machines" that constantly try to make external reality match our internal model. When a person speaks, they are attempting to shape your reality to see the world as they do.
openaire +2 more sources

