Results 181 to 190 of about 197,508 (306)

Indirect calorimetry compared with predictive equations for resting energy expenditure in patients with intestinal failure. [PDF]

Intest Fail
Wyer N, Reynolds E, Norrie L, Woodend L, Richardson H, Ferguson E.   +5 more
europepmc   +1 more source

Multilayered Digital Microfluidic Chip for Cell‐Based Assays

Advanced Materials Interfaces, EarlyView.
A multilayered digital microfluidic (mDMF) chip architecture is introduced to improve throughput and robustness in cell‐based assays. By multilayering electrode components and dielectric layers on glass, this design significantly reduces actuation voltage, maintains reliability, and enables expansion of the operational area with minimum current leakage.
Mert Ozden, Oksana K. Savchak, Burcu Gumuscu   +2 more
wiley   +1 more source

Thyrotropin-releasing hormone neurons of different hypothalamic nuclei increase energy expenditure. [PDF]

Nat Commun
Constantinescu A, Chandrasekar A, Kleindienst L, Höhne L, Da Silva Lima N, Richter M, Neve V, Spiecker F, Stölting I, Brandt W, Matschl U, Wenzel J, Oelkrug R, Prevot V, Heuer H, Mittag J, Nogueiras R, Schwaninger M, Müller-Fielitz H.   +18 more
europepmc   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

Advanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue, Yuan Gao, Fanping Sui, Jason Wang, Megan Teng, Peggy Tsao, Huicong Deng, Yande Peng, Liwei Lin   +8 more
wiley   +1 more source

Regulation of physical activity and energy expenditure through Phf6 in the medial preoptic area. [PDF]

Nat Commun
Wang J, Liu B, Wu X, Sun J, Wang Y, He L, Gan L, Du X, Ruan J, Pi L, Wu QF, Huang J.   +11 more
europepmc   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Feasibility, reproducibility, and cold-induced energy expenditure using whole-room calorimetry in adults and children. [PDF]

J Endocr Soc
Cheveldayoff P, Alamri B, Wang D, Gonzalez RC, Thomas ACQ, Konyer N, Noseworthy MD, Gerstein HC, Punthakee Z, Steinberg GR, Morrison KM.   +10 more
europepmc   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

A wearable IMU-based framework for daily physical activity recognition and energy expenditure level classification in university students. [PDF]

Front Public Health
Zhou X, Wang S, He L, Ma L.
europepmc   +1 more source