Results 51 to 60 of about 75,586 (259)

Spontaneous Perovskite Passivator Featuring Dual Functional Groups

Advanced Energy Materials, EarlyView.
A novel strategy to suppress multiple defect sites in perovskite crystals using a spontaneous passivator with dual functional groups is proposed, addressing an intrinsic drawback of conventional spontaneous perovskite passivators. 2‐thiophene‐ethyl‐ammonium‐bis(trifluoromethylsulfonyl)imide (TEA‐TFSI) is newly synthesized and successfully demonstrate ...
Naoyuki Nishimura, Yoyo Hinuma, Hiroyuki Kanda, Kohei Yamamoto, Hideyuki Takada, Masaki Yumoto, Daniela Serien, Kenichi Tashiro, Aiko Narazaki, Takurou N. Murakami   +9 more
wiley   +1 more source

SOME ECONOMIC INCENTIVES AT USING OF THE WORKED OVER WASTE PRODUCTS IN METALLURGICAL PRODUCTION

Литьë и металлургия, 2013
The statistical analysis of the production of certain metallurgical enterprises of Urals and Siberia on waste formation and their secondary application is carried out.
S. A. Nikiforov, M. V. Nikiforova, V. I. Gerner, A. N. Georgadze, M. I. Elashvili, V. V. Obrezkov, A. N. Pletnev   +6 more
doaj  

SHM strategy optimization and structural maintenance planning based on Bayesian joint modelling [PDF]

, 2017
In this contribution, an example is used to illustrate the application of Bayesian joint modelling in optimizing the SHM strategy and structural maintenance planning.
Caspeele, Robby, Taerwe, Luc, Xing, Cheng   +2 more
core   +1 more source

Assessing Astrophysical Uncertainties in Direct Detection with Galaxy Simulations

, 2016
We study the local dark matter velocity distribution in simulated Milky Way-mass galaxies, generated at high resolution with both dark matter and baryons.
Brooks, Alyson M., Buckley, Matthew R., Governato, Fabio, Sloane, Jonathan D.   +3 more
core   +1 more source

Classification of damage in structural systems using time series analysis and supervised and unsupervised pattern recognition techniques [PDF]

, 2010
Peer ...
De Lautour, O. R., Omenzetter, P.
core   +1 more source

SHM via topological derivative [PDF]

, 2020
This thesis focuses on the investigation of the usage of a relatively novel mathematical tool, the so-called topological derivative, for Structural Health Monitoring. In essence, the topological derivative approach minimizes a scalar objective function that measures the least squares difference between response to excitation of healthy and damaged ...
openaire   +2 more sources

Machine Learning‐Driven Digital Twin of a Field‐Effect Transistor‐Based Hormone Biosensor for Real‐Time Estradiol Monitoring

Advanced Intelligent Systems, EarlyView.
A machine learning‐driven digital twin simulates an aptamer‐functionalized BioFET measuring 17β‐estradiol. Real‐time Isd signals are processed, features are extracted, and trained models estimate hormone concentration. In parallel, a one‐step‐ahead forward model learns biosensor dynamics and generates realistic synthetic signals, enabling in silico ...
Anastasiia Gorelova, Alexandra Parichenko, Shirong Huang, Santiago Melia, Gianaurelio Cuniberti   +4 more
wiley   +1 more source

Diffusion MRI and α‐Synuclein Seed Amplification Status in Parkinson's Disease

Annals of Neurology, EarlyView.
Objective Positive α‐synuclein seed amplification assay (SAA) is a biomarker found in most people with Parkinson's disease (PD). We explored if free‐water (FW) imaging detects microstructural differences in the brains of patients with early PD with SAA+ or SAA– status.
Shannon Y. Chiu, Wei‐en Wang, Robin Chen, Jesse C. DeSimone, Derek B. Archer, Charles H. Adler, Shyamal H. Mehta, Sara R. Dresler, Melissa J. Armstrong, Nikolaus McFarland, Michael Okun, David E. Vaillancourt, Parkinson's Progression Markers Initiative, Neha Prakash, Tanya Simuni, Nabila Dahodwala, Caroline Tanner, Lana Chahine, Brit Mollenhauer, Anat Mirelman, Roy Alcalay; Katherine Leaver, Marie Saint‐Hilaire, Ruth Schneider, Christopher Tarolli, Werner Poewe, Aleksandar Videnovic, David Standaert, Marissa Dean, Sonja Jonsdottir, Rejko Krueger, Claire Pauly, Stewart Factor, Penelope Hogarth, Robert Hauser, Amy Amara, Michelle Fullard, Cyrus Zabetian, Hubert Fernandez, Kathrin Brockmann, Isabel Wurster, Yen Tai, Paolo Barone, Marina Picillo, Stuart Isaacson, Alberto Espay, Eduardo Tolosa, Javier Ruiz Martinez, Leonidas Stefanis, Kelvin Chou, Lorraine Kalia, Connie Marras, David Grimes, Tiago Mestre, Rajesh Pahwa, Mark Lew, Holly Shill, Shyamal Mehta, Giulietta Riboldi, Nikolaus McFarland, Ron Postuma, Zoltan Mari, David Ledingham, Nicola Pavese, Michele Hu, Norbert Brueggemann, Christine Klein, Bastiaan Bloem, Cristina Simonet, Alastair Noyce, Anette Janzen, David Pedrosa, Wolfgang Oertel, Njideka Okubadejo, David Shprecher, Arjun Tarakad, Emile Moukheiber, Joy Antala, Carla Aranda, Karen Williams, Sophia Melton, Karina Benson, Ashwini Ramachandran, Danielle Potts, Grace LaMoure, Ritikha Vengadesh, Ryan Manzler, Jaime Heller, Primi Ranola, Farah Kausar, Sherri Mosovsky, Diana Willeke, Elizabeth Kalinkara Gomez, Janelle Rodriguez, Nobuko Kemmotsu, May Eshel, Deborah Raymond, Abigail Desrosiers, Raymond James, Lauren Jackson, Iris Egner, Wesley Schlett, Courtney Blair, Lauren Ruffrage, Berenice Sevilla, Barbara Sommerfeld, Dustin Le, Erica Botting, Gabriella Mazur, Daniele Derlein, Ying Liu, Ciera Cobb, Olivia Masiewicz, Jennifer Mule, Michael Morsillo, Ella Hilt, Lisbeth Pennente, Bobbie Stubbeman, Alicia Garrido, Valeria Ravasi, Ioana Croitoru, Christos Koros, Nikolas Papagiannakis, Frank Ferrari, Mengyu Zheng, Shawna Reddie, Alicia Alejandra, Andrea Gray, Alejandra Valenzuela, Caitlin Goodman, Sara Dresler, Neil Santos, Fahrial Esha, Kyle Rizer, Nadine Zablith, Liliana Dumitrescu, Debra Galley, Victoria Kate Foster, Jamil Razzaque, Madita Grümmer, Yara Krasowski, Elisabeth Sittig, Oluwadamilola Ojo, Kelly Clark, Rory Mahabir, Kori Ribb, Shamera Willoughby   +145 more
wiley   +1 more source

DynaView: General Dynamic Visualization Model for SHM [PDF]

Mathematical Problems in Engineering, 2012
We present a general dynamic visualization model named DynaView to construct virtual scenes of structural health monitoring (SHM) process. This model consists of static, dynamic, and interaction submodels. It makes the visualization process dynamic and interactive. By taking an example of a simplified reinforced concrete beam structure model, we obtain
Sun, Peng, Wu, Ziyan, Hua, Qingyi, Li, Zhanhuai, Kang, Muning   +4 more
openaire   +2 more sources

Early stages of tooth development in the harbor porpoise Phocoena phocoena

The Anatomical Record, EarlyView.
Abstract Here we describe the stages of tooth development in toothed whales on the basis of the harbor porpoise (Phocoena phocoena). The aim of the study was to find out whether these stages are identical to those of other mammals analyzed so far although toothed whales are homodont and monophyodont.
Lasse M. Mathes, Lennart Müller‐Thomsen, Stefan Huggenberger   +2 more
wiley   +1 more source