Digital problem-based learning in health professions : systematic review and meta-analysis by the digital health education collaboration by Car, Lorainne Tudor, Kyaw, Bhone Myint, Dunleavy, Gerard, Smart, Neil A., Semwal, Monika, Rotgans, Jerome Ingmar, Low-Beer, Naomi, Campbell, James

“…We used the random-effects model in the meta-analyses. Results: Nine RCTs involving 890 preregistration health professionals were included. …”
Get full text
Get full text

Effectiveness of clinician client-centered counseling on knowledge, attitudes and sexual bahaviors of antiretroviral therapy patients in Yola, Nigeria by Martins, Olutayo Folashade

“…A clinician client centered training module was developed based on the Information Behavior and Motivation (IBM) Model. Nine Clinicians were trained with this module to deliver a 10 to 15 minutes clinic based intervention (Clinician client centered counseling). …”
Get full text

Distortion in laser micro welding of stainless steel SS304 foils by M. N., Jamaludin, Quazi, Moinuddin Mohammed, Aiman, Mohd Halil, M., Ishak

“…Stainless Steel 304 is a fine material selection for industrial usage in laser micro welding for e-mobility applications wherein battery components are fabricated. …”
Get full text
Get full text

Thermal stability of laser modified die insert surface in hot press forming of 22MnB5 by Norhafzan, Bariman, Syarifah Nur Aqida, Syed Ahmad, Izwan, Ismail, Khairil, Che Mat

“…Despite its superior properties, the thermal stability of fine grain structure is questionable as its metastable phase. …”
Get full text

Tuning the shear thickening of suspensions through surface roughness and physico-chemical interactions by Bourrianne, Philippe, Niggel, Vincent, Polly, Gatien, Divoux, Thibaut, McKinley, Gareth H.

“…Finally, we demonstrate how mixtures of particles with opposing surface chemistry make it possible to finely tune the shear-thickening response of the suspension at a fixed volume fraction, paving the way for a fine control of the shear-thickening transition in engineering applications.…”
Get full text

Language, Camera, Autonomy! Prompt-engineered Robot Control for Rapidly Evolving Deployment by Macdonald, Jacob P., Mallick, Rohit, Wollaber, Allan B., Peña, Jaime D., McNeese, Nathan, Siu, Ho Chit

Get full text

Drive-specific selection in multistable mechanical networks by Kedia, Hridesh, Pan, Deng, Slotine, Jean-Jacques, England, Jeremy L.

“…We found that there exists a range of forcing amplitudes for which the attractor states of driven disordered multistable mechanical networks are fine-tuned with respect to the pattern of external forcing to have low energy absorption from it. …”
Get full text

Stability of internal gravity wave modes: from triad resonance to broadband instability by Akylas, T.R., Kakoutas, Christos

“…For short-scale perturbations such that 𝜇 ≪ 1 but 𝛼 = 𝜇/𝜖 ≫ 1, this triad resonance instability reduces to the familiar parametric subharmonic instability (PSI), where triads comprise fine-scale perturbations with half the basic-wave frequency. …”
Get full text

Physics-informed deep learning for multi-species membrane separations by Rehman, Danyal, Lienhard, John H.

“…The neural methods are pre-trained on simulated data from continuum models and fine-tuned on independent experiments to learn multi-ionic rejection behaviour. …”
Get full text

Supermind Ideator: How Scaffolding Human-AI Collaboration Can Increase Creativity by Heyman, Jennifer, Rick, Steven, Giacomelli, Gianni, Wen, Haoran, Laubacher, Robert, Taubenslag, Nancy, Knicker, Max, Jeddi, Younes, Ragupathy, Pranav, Curhan, Jared, Malone, Thomas

Get full text

Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition by Zhang, Da, Wang, Qingyi, Song, Shaojie, Chen, Simiao, Li, Mingwei, Shen, Lu, Zheng, Siqi, Cai, Bofeng, Wang, Shenhao, Zheng, Haotian

“…In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. …”
Get full text

Bridging the Health Divide: Achieving Equitable Healthcare Access in Kenya through Artificial Intelligence by Nyakiongora, Geoffrey Mosoti

“…A GPT model is developed and fine-tuned on a comprehensive dataset of Kenyan cultural information, healthcare data, and architectural knowledge. …”
Get full text

Speed-Modulated Ironing: High-Resolution Shade and Texture Gradients in Single-Material 3D Printing by Ozdemir, Mehmet, AlAlawi, Marwa, Dogan, Mustafa Doga, Martinez Castro, Jose, Mueller, Stefanie, Doubrovski, Zjenja

Get full text

Tango 2: Aligning Diffusion-based Text-to-Audio Generations through Direct Preference Optimization by Majumder, Navonil, Hung, Chia-Yu, Ghosal, Deepanway, Hsu, Wei-Ning, Mihalcea, Rada, Poria, Soujanya

“…The loser outputs, in theory, have some concepts from the prompt missing or in an incorrect order. We fine-tune the publicly available Tango text-to-audio model using diffusion-DPO (direct preference optimization) loss on our preference dataset and show that it leads to improved audio output over Tango and AudioLDM2, in terms of both automatic- and manual-evaluation metrics.…”
Get full text

Hardness of Approximate Diameter: Now for Undirected Graphs by Dalirrooyfard, Mina, Li, Ray, Vassilevska Williams, Virginia

“…A series of papers on fine-grained complexity have led to strong hardness results for diameter in directed graphs, culminating in a recent tradeoff curve independently discovered by [Li, STOC'21] and [Dalirrooyfard and Wein, STOC'21], showing that under the Strong Exponential Time Hypothesis (SETH), for any integer k?…”
Get full text

Enabling Perspective-Aware Ai with Contextual Scene Graph Generation by Platnick, Daniel, Alirezaie, Marjan, Rahnama, Hossein

“…We evaluated PASGG-LM pipelines using state-of-the-art SGG models, including Motifs, Motifs-TDE, and RelTR, and showed that fine-tuning LLMs, particularly GPT-4o-mini and Llama-3.1-8B, improves performance in terms of R@K, mR@K, and mAP. …”
Get full text

Decoding Codon Bias: The Role of tRNA Modifications in Tissue-Specific Translation by Ando, Daisuke, Rashad, Sherif, Begley, Thomas J., Endo, Hidenori, Aoki, Masashi, Dedon, Peter C., Niizuma, Kuniyasu

“…Our knowledge of the role of the tRNA epitranscriptome in fine-tuning translation via codon decoding at tissue or cell levels remains incomplete. …”
Get full text

Characteristics of scanning curves of two soils by Tami, Denny, Rahardjo, Harianto, Leong, Eng Choon

“…The first slope model consisted of a fine sand layer overlying a gravelly sand layer, while the second slope model involved a silty sand layer overlying a gravelly sand layer. …”
Get full text
Get full text

WAHRSIS : a low-cost high-resolution whole sky imager with near-infrared capabilities by Dev, Soumyabrata, Savoy, Florian M., Lee, Yee Hui, Winkler, Stefan

“…Cloud imaging using ground-based whole sky imagers is essential for a fine-grained understanding of cloud formations, which can be useful in many applications. …”
Get full text
Get full text
Get full text

Non-motorised transport prioritisation model using spatial intelligence by Poyil, Rohith P., Lopez, Maria Cecilia Rojas, Wong, Yiik Diew

“…The concept of spatial intelligence was used to predict the NMT prioritisation scheme; spatial intelligence is the ability to visualise spatial features and apply spatial judgement for mobility problems involving navigation or to identify fine details or patterns. The NMT prioritisation model was developed based on NMT movements in relation to spatial features such as residential buildings, community centres, schools and hospitals, recreation and sports centres, economic zones, transport hubs, bus stops and green spaces. …”
Get full text