Results 171 to 180 of about 28,487,165 (236)

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

The FunAqua dataset of global fungal biodiversity in aquatic ecosystems. [PDF]

Sci Data
Prins V, Tedersoo L, Mikryukov V, Paiste P, Sepp M, Grossart H, Kisand V, Laas A, Tammert H, Abarenkov K, Agan A, Agasild H, Agha R, Alatalo J, Alvarez-Manjarrez J, Ameryk A, Anderson J, Anslan S, Antão-Geraldes A, Antosiak A, Funck JA, Arias-Real R, Ariyan M, Bahram M, Bansal S, Bao R, Beck S, Bernotas P, Berry N, Bertilsson S, Birnbaum C, Bonk M, Borges AV, Botez F, Brearley FQ, Brookes J, Bruno D, Budzyńska A, Bullerjahn G, Bundschuh M, Calheiros-Nogueira B, Calore R, Capelli C, Caputo L, Carballeira R, Chronis I, Čiampor F, Čiamporová-Zaťovičová Z, Craig D, Csabai Z, Cukrov N, da Silva L, de Eyto E, Delgado J, Dimante-Deimantovica I, Domaizon I, Dondajewska-Pielka R, Dornan T, Drenkhan R, Drouillard K, Duarte S, Dulya O, Dzhulai A, Dziga D, Egeter B, Espenberg M, Färkkilä S, Fazi S, Feckler A, Fenoy E, Fernandes I, Ferreira S, Ferreira V, Fleituch T, Fornaroli R, Freiwald A, Frenken T, Gaffney P, García-Oliva O, Geara H, Gkelis S, Gohar D, Gołdyn R, Grandjean F, Gsell A, Gutiérrez-Cánovas C, Haase P, Hagh-Doust N, Harris T, Hashem A, Havens S, Heidari B, Higgins S, Moghaddam MH, Ibrahim A, Jerinkić D, Jones S, Kagami M, Kahar S, Kangro K, Kariman K, Kataržytė M, Kepfer-Rojas S, Khan H, Knoll LB, Knorrn A, Kõljalg U, Konstantinou D, Kotta J, Kowalczewska-Madura K, Kozak A, Kulawig B, Kupagme J, Kušan I, Laarmaa R, Laas P, Langenheder S, Lanzén A, Lateef A, Ligi M, Löffler T, Lortou U, Lujza K, MacConnell T, Maček I, Macreadie P, Maileht K, Marazzi F, Marcello L, Markovskaja S, Martin A, Martínez S, Mata V, Matočec N, McKay R, McKindles K, Mehrshad M, Menéndez M, Merino N, Mešić A, Moctar S, Moza M, Nõges P, Nõges T, O'Hanlon R, Öğlü B, Oja J, Okello W, Orav-Kotta H, Orr P, Osemwegie I, Padisák J, Pajunen V, Panou M, Papatheodoulou A, Pavlovska M, Pearman J, Pehlak H, Peng X, Pereira A, Pereira R, Pernecker B, Picazo F, Pinnow S, Pochekutova P, Põlme S, Pontevedra-Pombal X, Pošta A, Prekrasna-Kviatkovska Y, Pruuli J, Pruuli M, Pruuli T, Radoja N, Rahimlou S, Rannap R, Rasconi S, Rasmussen A, Remmers W, Reyes L, Rhodes G, Roe C, Rojas-Castillo O, Roslin T, Runnel K, Rusch J, Rybak M, Rychtecký P, Sahadevan S, Saitta A, Salehi-Najafabadi A, Santi I, Sarapuu J, Schäfer RB, Schneeweiss A, Scholz B, Selmeczy G, Smederevac-Lalić M, Sommaruga R, Stetler J, Stoica E, Stoll S, Strand D, Tamm M, Tapolczai K, Tarand J, Teurlincx S, Thompson J, Thomson-Laing G, Tiirmann L, Tkalčec Z, Trbojević I, Trevathan-Tackett S, Tsiarta N, Tuvikene A, Tuvikene L, Vacaflores-Argandoña M, Vahter T, Vaino K, Val AL, Vandergoes M, Vasemägi A, Vask A, Vasquez M, Veríssimo J, Vesamäki J, Virta L, Visser P, Viza A, Vrålstad T, Ward CS, Waryszak P, Wierenga J, Wilson P, Wood S, Woźniczka A, Wurzbacher C, Zingel P, Znachor P, Dela Cruz TEE, Panksep K.   +239 more
europepmc   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

Mapping the Global Habitat Redistribution of Critically Endangered Commercial Fish Species Under Climate Change. [PDF]

Glob Chang Biol
Gong Y, Zhang H, Ye G, Zeng J, Yan X.
europepmc   +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Mariculture Probiotics: A Scoping Review of Research Trends, Knowledge Gaps and Opportunities. [PDF]

Mar Biotechnol (NY)
Alperstein L, Nappi J, Egan S.
europepmc   +1 more source

A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing

Advanced Intelligent Systems, EarlyView.
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti, Weng Buxiu, Petr Trunin, Muhammad Sunny Nazeer, Lucia Beccai, Perla Maiolino, Cecilia Laschi   +6 more
wiley   +1 more source

Flavasperfurans A and B, Two New Asperfuran Derivatives From the Marine-Derived Fungus Aspergillus flavus. [PDF]

Chem Biodivers
Wang CX, Zou ZB, Li LS, Gao CH, Yang XW.
europepmc   +1 more source

Designing Wire Mazes for Replicating Natural Echoes to Study Bat Biosonar Function

Advanced Intelligent Systems, EarlyView.
A validated framework combining efficient physical modeling (multiple scattering model) and deep learning is presented to guide wire‐maze design for bat biosonar studies. This approach rapidly generates large datasets to test acoustic distinguishability among wire arrangements.
Chunlin Jia, Gengkai Hu, Boo Cheong Khoo, Rolf Müller   +3 more
wiley   +1 more source