Results 151 to 160 of about 12,439,103 (299)

Theorizing future phenomena: Metaverse, wearables, and humanoids

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary We propose that entrepreneurship and strategy research can develop theory about phenomena of the future rather than only explain those of the past. Research has potential for practical relevance when researchers make claims towards applications to decisions practitioners have yet to make.
Andy Wu, Ronald Wang
wiley   +1 more source

Computing Generalized Method of Moments and Generalized Empirical Likelihood with R [PDF]

This paper shows how to estimate models by the generalized method of moments and the generalized empirical likelihood using the R package gmm. A brief discussion is offered on the theoretical aspects of both methods and the functionality of the package ...
Pierre Chaussé
core  

Revealing Airflow–Particle Dynamics in Dry Powder Inhalers

Small, EarlyView.
An integrated framework combining device and formulation characterization, CFD–DEM simulations, and interpretable machine learning is established. This framework reveals how airflow and particle interactions govern powder dispersion across prevailing dry powder inhalers.
Jiale Chen, Ziyi Fan, Qingliang Yang, Yuanyuan Shao, Dongbing Li, Xiaoyang Wei, Xiang Luo, Kaiqi Shi, Gang Yang, Gensheng Yang, Ying Ma, Yuqing Ye, Jesse Zhu   +12 more
wiley   +1 more source

Quadrature solution of fractional coupled burgers and plankton-oxygen dynamics under climate change. [PDF]

Sci Rep
Zayed MA, Almetwally EM, Mohamed M, Ragb O, Khidr MF, Matbuly MS, Salah M.   +6 more
europepmc   +1 more source

Generalized Newton Methods for Crack Problems with Non-Penetration Condition

, 2003
A class of semismooth Newton methods for unilaterally constrained variational problems modelling cracks under a non-penetration condition are introduced and investigated.
Hintermüller, M., Kovtunenko, V.A., Kunisch, K.   +2 more
core  

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 more
wiley   +1 more source

Reliability Assessment of MEMS Gyroscopes via Dual-Mechanism Synergistic Degradation: A Generalized Linear Model with Physics-Informed Wiener Processes. [PDF]

Sensors (Basel)
Yang P, Liu Z, Liang Y, Guo X, Geng H.
europepmc   +1 more source

Accelerating Molecular Ferroelectrics: From Rapid Mapping to Scalable High‐Yield Synthesis

Small Methods, EarlyView.
An integrated fluidic framework enables rapid crystallization screening of molecular ferroelectrics and bridges single‐crystal growth with high‐yield continuous production using pressurized CO2 as a tunable antisolvent. ABSTRACT Molecular ferroelectrics (MFs) represent a transformative class of functional materials, which offer mechanical flexibility ...
Sabine Lakhloufi, Chloé Boucleinville, Elisa Rotondo, Jérôme Rouquette, Mickaël Beaudhuin, Stanislav Pechev, Eric Lebraud, Cyril Aymonier, Jérôme Long   +8 more
wiley   +1 more source

Fingering instability at the interface between growing and not-growing cell populations with different mobilities. [PDF]

J Math Biol
Ciarletta P, Magri M, Shkurti D, de Falco C.   +3 more
europepmc   +1 more source

A Novel Approach to Energy Management in Electric Steelworks

steel research international, EarlyView.
Feed‐forward neural networks are exploited to estimate electric energy consumptions of the electric arc furnace and ladle furnace processes. The models are used to optimize production schedule so that more energy intensive grades are produced when the cost of energy is lower.
Valentina Colla, Stefano Dettori, Silvia Cateni, Marco Vannucci, Antonella Vignali, Claudio Mocci, Irene Dovichi, Davide Chionna, Lorenzo Vannini, Enrico Paluzzano, Costanzo Pietrosanti, Davide Onesti, Daniele Venier   +12 more
wiley   +1 more source