Results 161 to 170 of about 11,236 (199)

Endoplasmic Reticulum Geometry Dictates Neuronal Bursting via Calcium Store Refill Rates and Exposes Selective Neuronal Vulnerability

Advanced Science, EarlyView.
The ER's continuous tubular network is maintained by ER‐shaping proteins whose mutation or dysregulation contributes to neurodegenerative diseases. Here, we show that ER morphology sets the speed of Ca2+ store replenishment between firing events. Disrupting ER continuity slows intra‐ER Ca2+ redistribution from extracellular refill (SOCE) sites, driving
Valentina Davi, Pierre Parutto, Yuyi Zhang, Tasuku Konno, Cecile Crapart, Raquel Pereira, John P. Franklin, Mosab Ali Awadelkareem, Daniel C Maddison, Michael J. Devine, Edgar R. Gomes, Joseph Chambers, Elena Koslover, Edward Avezov   +13 more
wiley   +1 more source

Data Generation for Machine Learning Interatomic Potentials and Beyond. [PDF]

Chem Rev
Kulichenko M, Nebgen B, Lubbers N, Smith JS, Barros K, Allen AEA, Habib A, Shinkle E, Fedik N, Li YW, Messerly RA, Tretiak S.   +11 more
europepmc   +1 more source

Recent Advances in Laser‐Induced Graphene‐Based Gas Sensors: From Sensing Mechanisms to Biomedical Applications

Advanced Science, EarlyView.
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas, Ankan Dutta, Shuvendu Das, Abu Musa Abdullah, Wanqing Zhang, Fatema Tuz Zohra, Huanyu Cheng   +6 more
wiley   +1 more source

Finite size approximation for representations of $U_q(\widehat{\mathfrak{sl}}(n))$(Combinatorial Aspects in Representation Theory and Geometry)

Finite size approximation for representations of $U_q(\widehat{\mathfrak{sl}}(n))$(Combinatorial Aspects in Representation Theory and Geometry)
openaire  

Optimising Sensor Placement in Heritage Buildings: A Comparison of Model-Based and Data-Driven Approaches. [PDF]

Sensors (Basel)
Chaves E, Barontini A, Mendes N, Compán V.   +3 more
europepmc   +1 more source

Reconfigurable, Temperature Resilient Phase‐Change Metasurfaces Fabricated via High Throughput Nanoimprinting Lithography

Advanced Science, EarlyView.
ABSTRACT The combination of metasurfaces with chalcogenide phase‐change materials is a highly promising route toward the development of multifunctional and reconfigurable nanophotonic devices. However, their transition into real‐world devices is hindered by several technological challenges. This includes, amongst others, the lack of large area photonic
Carlota de Ruiz de Galarreta, Yinghao Zhao, Jose Mendoza‐Carreño, José M. Caicedo, José Santiso, C. David Wright, M. Isabel Alonso, Jiafang Li, Agustin Mihi   +8 more
wiley   +1 more source

Relative invariants of the polynomial rings over the finite and tame type quivers(Combinatorial Aspects in Representation Theory and Geometry)

Relative invariants of the polynomial rings over the finite and tame type quivers(Combinatorial Aspects in Representation Theory and Geometry)
openaire  

Bioinspired Designs for Lightweighting, a Critical Review for Manufacturing. [PDF]

Biomimetics (Basel)
Kenny V, Bapat S, Smith P, La Scala J, Malshe AP.   +4 more
europepmc   +1 more source

Lattice Genome Framework for Regionally Tailored Component‐Level Multi‐Objective Design in Additive Manufacturing

Advanced Science, EarlyView.
A Lattice Genome framework links geometric and process “genes” to lattice “phenotypes” via correction‐calibrated high‐throughput simulations and a growing performance database. Genome‐driven retrieval and recombination of unit cells enables component‐level, regionally tailored multi‐objective design: stress fields are programmed under constant relative
Haoyuan Deng, Yufan Zhao, Mingyang Cao, Haiou Yang, Pan Wang, Hongze Wang, Hao Wang, Akihiko Chiba, Xin Lin   +8 more
wiley   +1 more source

Leveraging Machine Learning for Porosity Prediction in AM Using FDM for Pretrained Models and Process Development. [PDF]

Materials (Basel)
Ouajjani K, Steck JE, Olivares G.
europepmc   +1 more source