Results 141 to 150 of about 403,368 (289)
Laser‐Induced Graphene from Waste Almond Shells
Advanced Functional Materials, EarlyView.Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova +9 more
wiley +1 more source
AiBi Revista de Investigación, Administración e IngenieríaGround deformation during tunneling projects is one of the complicated concerns that must be constantly monitored to prevent unanticipated damages and human losses.
Shubham Kanojiya, Gopal Krishna Mehta
doaj +1 more source
FORECAST EVALUATION FOR MULTIVARIATE TIME-SERIES MODELS: THE U.S. CATTLE MARKET [PDF]
A set of rigorous diagnostic techniques is used to evaluate the forecasting performance of five multivariate time-series models for the U.S. cattle sector.
Park, Timothy A.
core +1 more source
Band Alignment in In‐Oxo Metal Porphyrin SURMOF Heterojunctions
Advanced Functional Materials, EarlyView.Porphyrin core metalation in indium‑oxo SURMOFs enables systematic tuning of band edge positions without altering the crystal structure. First‑principles calculations reveal type‑I and type‑II heterostructures as well as multi‑junction energy cascades, establishing a modular strategy for exciton funneling and charge separation in optoelectronic ...
Puja Singhvi, Nina Vankova, Thomas Heine
wiley +1 more source
Solow Residuals without Capital Stocks [PDF]
For more than fifty years, the Solow decomposition (Solow 1957) has served as the standard measurement of total factor productivity (TFP) growth in economics and management, yet little is known about its precision, especially when the capital stock is ...
Battista Severgnini, Michael C. Burda
core
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 +7 more
wiley +1 more source
Jackknife bias reduction in the presence of a near-unit root
, 2016 This paper considers the specification and performance of jackknife estimators of the autoregressive coefficient in a model with a near-unit root.
Chambers, Marcus J., Kyriacou, Maria
core
Advanced Functional Materials, EarlyView.A multivalent antiviral platform based on honeycomb‐shaped DNA nanostructures (HC–Urumin) is developed to enhance the potency and breadth of the host defense peptide Urumin. Through spatially patterned trimeric presentation, HC–Urumin disrupts influenza A virus entry, improves cell viability, and reduces disease severity in vivo‐offering a modular and ...
Saurabh Umrao +11 more
wiley +1 more source
Long Short-Term Memory Mixture Density Network for Remaining Useful Life Prediction of IGBTs
TechnologiesA reliable prediction of the remaining useful life of critical electronic components, such as insulated gate bipolar transistors, is necessary for preventing failures in many industrial applications.
Yarens J. Cruz +2 more
doaj +1 more source
Stop using root-mean-square error as a precipitation target!
Root-mean-square error (RMSE) remains the default training loss for data-driven precipitation models, despite precipitation being semi-continuous, zero-inflated, strictly non-negative, and heavy-tailed. This Gaussian-implied objective misspecifies the data-generating process because it tolerates negative predictions, underpenalises rare heavy events ...
openaire +2 more sources