Results 71 to 80 of about 245,585 (258)

A Lasso approach to covariate selection and average treatment effect estimation for clustered RCTs using design-based methods

Journal of Causal Inference, 2022
Statistical power is often a concern for clustered randomized control trials (RCTs) due to variance inflation from design effects and the high cost of adding study clusters (such as hospitals, schools, or communities).
Schochet Peter Z.
doaj   +1 more source

The Accessible Lasso Models

, 2016
A new line of research on the lasso exploits the beautiful geometric fact that the lasso fit is the residual from projecting the response vector $y$ onto a certain convex polytope.
Harris, Naftali, Sepehri, Amir
core   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

A Novel Clinical Prognostic Model for Breast Cancer Patients with Malignant Pleural Effusion: Avoiding Chemotherapy in Low-Risk Groups?

Cancer Management and Research, 2023
Yichen Wang,1,* Tao Zhou,2,* Shanshan Zhao,1,* Ning Li,3 Siwen Sun,1 Man Li1 1Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People’s Republic of China; 2Department of Oncology, The First ...
Wang Y, Zhou T, Zhao S, Li N, Sun S, Li M   +5 more
doaj  

Local Thermal Conductivity Patterning in Rotating Lattice Crystals of Anisotropic Sb2S3

Advanced Functional Materials, EarlyView.
Microscale control of thermal conductivity in Sb2S3 is demonstrated via laser‐induced rotating lattice crystals. Thermal conductivity imaging reveals marked thermal transport anisotropy, with the c axis featuring amorphous‐like transport, whereas in‐plane directions (a, b) exhibit 3.5x and 1.7x larger thermal conductivity.
Eleonora Isotta, Rosemary Wynnychenko, Binayak Mukherjee, Jack Kaman, Hrushikesh Sahasrabuddhe, Jiongzhi Zheng, Anubhav Jain, Geoffroy Hautier, Alexandra Zevalkink, Evan Musterman, Volkmar Dierolf, Himanshu Jain, G. Jeffrey Snyder, Oluwaseyi Balogun   +13 more
wiley   +1 more source

Electroactive Liquid Crystal Elastomers as Soft Actuators

Advanced Functional Materials, EarlyView.
Electroactive liquid crystal elastomers (eLCEs) can be actuated via electromechanical, electrochemical, or electrothermal effects. a) Electromechanical effects include Maxwell stress, electrostriction, and the electroclinic effect. b) Electrochemical effects arise from electrode redox reactions.
Yakui Deng, Min‐Hui Li
wiley   +1 more source

MARS via LASSO

The Annals of Statistics
Multivariate adaptive regression splines (MARS) is a popular method for nonparametric regression introduced by Friedman in 1991. MARS fits simple nonlinear and non-additive functions to regression data. We propose and study a natural lasso variant of the MARS method.
Ki, Dohyeong, Fang, Billy, Guntuboyina, Adityanand   +2 more
openaire   +3 more sources

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Prediction of Taxi-in Time and Analysis of Influencing Factors for Arrival Flights at Airport with a Decentralised Terminal Layout

Promet (Zagreb)
Accurately predicting taxi-in times for arrival flights is crucial for efficient ground handling resource allocation, impacting flight departure timeliness.
Xiaowei TANG, Mengfan YE, Shengrun ZHANG, Kurt FUELLHART   +3 more
doaj   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source