Results 161 to 170 of about 233,933 (299)

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Genomic prediction of feed efficiency in boars by deep learning. [PDF]

G3 (Bethesda)
Onabanjo O, Meuwissen T, Gjøen HM, Al Machot F, van Son M, Berg P.   +5 more
europepmc   +1 more source

Detection and characterization of the feed intake response of growing pigs to perturbations

, 2018
International audienceImproving robustness for farm animals is seen as a new breeding target. However, robustness is a complex trait and not measurable directly.
van Milgen, Jaap, J., Taghipoor, Masoomeh, Nguyen-Ba, Hieu   +2 more
core  

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair, Hrisheekesh Thachoth Chandran, Karl Leo, Hans Kleemann   +3 more
wiley   +1 more source

A bibliometric review about scientific trends and advances on residual feed intake (RFI) and feed efficiency in ruminants. [PDF]

Trop Anim Health Prod
Ferreira J, Gonçalves LF, Paim TDP, Bonilha SFM, Cyrillo JNDSG, Zerlotti Mercadante ME, Arnandes RHB, da Costa RLD, McManus C.   +8 more
europepmc   +1 more source

Path‐Decoupled Cation‐Eutaxy III–V van der Waals Memristive Semiconductors for Mitigating the Neuromorphic Accuracy‐Energy Trade‐off

Advanced Materials, EarlyView.
Path‐decoupled III–V van der Waals memtransistors spatially separate ionic and electronic transport to overcome the conventional trade‐off between accuracy and energy in neuromorphic hardware. Mobile K+ ions in the vdW gaps set a wide conductance window, Gmax/Gmin, while gate‐tunable hole conduction lowers programming energy, enabling reliable ...
Jihong Bae, Ji Hoon Han, Taeyoung Kim, Jongbum Won, Seokmin Park, Gyu Won Kim, Sungsoon Kim, Hong Choi, Taehoon Kim, Hong‐Sub Lee, Jae‐Hyun Lee, Young Jin Choi, Jinwoo Cheon, Wooyoung Shim   +13 more
wiley   +1 more source

Integrating GWAS and eQTL analysis to decipher genetic mechanisms of feed efficiency and feeding behaviors in pigs. [PDF]

Genet Sel Evol
Zhang Z, He Y, Zhao W, Wei R, Han H, Zhan Q, Yu P, Li S, Hou X, Wang J, Zhao Q, Fu Y, Chen Z, Wang Z, Pan Y, Wang Q, Zhang Z.   +16 more
europepmc   +1 more source

Feed intake and feed efficiency in double muscle and conventional cattle

Genetics Selection Evolution, 1980
Hanset R, Stasse A, Michaux C
openaire   +4 more sources

A Super‐Adhesive Air Filter With Capillarity‐Mediated Spontaneous Particle Absorption via Dynamic Bond Exchange

Advanced Materials, EarlyView.
We address the inherently weak particle adhesion of conventional air filters by coating a dynamically crosslinked adhesive layer that delivers capillarity‐driven strong adhesion and particle absorption mediated by dynamic bond exchange. The resulting enhancement in particle adhesion enables efficient ultrafast (up to 20 m s−1) and omnidirectional ...
Junyong Park, Hyeri Jeon, Hyunwoong Park, Ji Min Lee, Yeomyung Yoon, Gyeong Hwan Choi, Sazzadul A. Rahat, Dong Wook Lee, Sohdam Jeong, Jonathan T. Pham, Chae Bin Kim, Sanghyuk Wooh   +11 more
wiley   +1 more source

Different feed efficiency modeling approaches for the prediction of genomic breeding values in lactating dairy cows. [PDF]

Front Genet
Chegini A, Negussie E, Kokkonen T, Lidauer MH.   +3 more
europepmc   +1 more source