Results 211 to 220 of about 249,105 (274)

Extended grain filling has potential to improve yield in grain sorghum. [PDF]

J Exp Bot
Otwani D, McLean G, Hammer G, Cruickshank A, Hunt C, Tao Y, Koltunow A, Mace E, Jordan D.   +8 more
europepmc   +1 more source

Generative Deep Learning for Advanced Battery Materials

Batteries &Supercaps, EarlyView.
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal, Adrian Cierpka, Britta Nestler, Arnd Koeppe   +3 more
wiley   +1 more source

Dissecting the genetic architecture of yield-related traits by QTL mapping in maize. [PDF]

Front Plant Sci
Zhang H, Li T, Zhang Z, Wang J, Yang H, Liu J, Zhu W, Xue J, Xu S.   +8 more
europepmc   +1 more source

Strategic techniques for upgrading bio‐oil from fast pyrolysis: a critical review

Biofuels, Bioproducts and Biorefining, EarlyView.
Abstract Pyrolysis has been the subject of extensive scientific research due to its potential application to various waste streams and byproducts from different production systems. One of its main products is the liquid fraction known as bio‐oil – a complex material composed of a wide variety of organic molecules and a significant water content.
Luciana R Santos, Daniela R Araujo, Marco AS Rodrigues   +2 more
wiley   +1 more source

Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches. [PDF]

Sci Rep
Cheng B, Liu X, Guo K, Rastegarnia A.
europepmc   +1 more source

The Missing Link: Connecting Cultivation Conditions and Refolding Performance via Inclusion Body Biophysical Properties

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Inclusion bodies (IBs) frequently form during the expression of heterologous proteins in Escherichia coli and are therefore important in pharmaceutical production. While it is accepted that cultivation conditions affect cultivation performance, the link to refolding performance remains unexplored. This study proposes that this interplay relies,
Matthias Rüdt, Aymerick Bussien, Joan Cortada‐Garcia, Holger Morschett, Hauke Holm, Chiara Mazzucchelli, Karlheinz Flicker   +6 more
wiley   +1 more source

In silico analysis of the evolution of root phenotypes during maize domestication in Neolithic soils of Tehuacán. [PDF]

New Phytol
Lopez-Valdivia I, Vallebueno-Estrada M, Rangarajan H, Swarts K, Benz BF, Blake M, Sidhu JS, Perez-Limon S, Sawers RJH, Schneider H, Lynch JP.   +10 more
europepmc   +1 more source

Optimized Machine Learning for Autonomous Enzymatic Reaction Intensification in a Self‐Driving Lab

Biotechnology and Bioengineering, EarlyView.
A machine learning‐powered self‐driving lab accelerates enzymatic reaction optimization by autonomously navigating complex parameter spaces. Through over 10,000 simulated campaigns, we identified an optimal algorithm for efficient, automated optimization.
Sebastian Putz, Niklas Teetz, Michael Abt, Pascal Jerono, Thomas Meurer, Matthias Franzreb   +5 more
wiley   +1 more source

The Assessment of In Vitro Protein Digestibility and Quality on Mechanically Scoured and Moisture Conditioned Navy Beans (Phaseolus vulgaris) and Chickpeas (Cicer arietinum) Subject to Roller‐Milling

Cereal Chemistry, EarlyView.
ABSTRACT Background and Objectives Roller‐milling practices for pulses to establish potential end‐use applications are required. Scouring and moisture conditioning may improve milling efficiency and hull removal, in addition to influencing nutritional quality.
Adam J. Franczyk, Nguyen Bui, Jiayi Chen, Lindsey Boyd, Ning Wang, Elaine Sopiwnyk, Ashok Sarkar, Jason Neufeld, Jitendra Paliwal, Michael Nickerson, James D. House   +10 more
wiley   +1 more source

Agronomic characteristics, mineral nutrient content, antioxidant capacity, biochemical composition, and fatty acid profile of Iranian pistachio (Pistacia vera L.) cultivars. [PDF]

BMC Plant Biol
Khadivi A, Nikoogoftar-Sedghi M, Tunç Y.   +2 more
europepmc   +1 more source