Results 101 to 110 of about 190,933 (296)

PIK3CA Mutations Downregulate PPT1 to Promote Adipogenesis by Suppressing P300 Depalmitoylation and Phase Separation

open access: yesAdvanced Science, EarlyView.
This study demonstrates that somatic PIK3CA mutations suppress PPT1 expression via activation of the PI3K–AKT–c‐JUN axis. This reduction in PPT1 weakens its interaction with P300, thereby increasing palmitoylation at C1176 of P300 and protecting P300 from lysosomal degradation.
Hongrui Chen   +7 more
wiley   +1 more source

Solution of inverse problem of fuzzy relational equation by using perceptron model [PDF]

open access: yes
A Max-Min fuzzy system can be regarded as a network of max and min operational elements. Thus, the inverse problem of a fuzzy relational equation is interpreted as an input estimation problem from output values in the corresponding network.
Hirota, Kaoru, Ikoma, Norikazu
core   +1 more source

PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping

open access: yesAdvanced Science, EarlyView.
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su   +7 more
wiley   +1 more source

PREDIKSI KETERSEDIAAN BERAS DI MASYARAKAT DENGAN MENGGUNAKAN LOGIKA FUZZY DAN JARINGAN SYARAF TIRUAN DALAM UPAYA MENINGKATKAN KETAHANAN PANGAN

open access: yesAgrointek, 2016
Development to predicted Handling availability of food stocks need to be done, one by combining model predictions using fuzzy logic and artificial neural network or more in the know with ANFIS (Adaptive Neuro Fuzzy Inference System).
M FM Fuad
doaj  

Gaussian Artmap: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps [PDF]

open access: yes, 1995
A new neural network architecture for incremental supervised learning of analalog multidimensional maps is introduced. The architecture, called Gaussian ARTMAP, is a synthesis of a Gaussian classifier and an Adaptive Resonance Theory (ART) neural network,
Williamson, James R.
core   +1 more source

Deep Volumetric Super‐Resolution Imaging in Thick Biological Specimens With Sparse Scanning SIM

open access: yesAdvanced Science, EarlyView.
Sparse scanning structured illumination microscopy (SS‐SIM) extends the axial depth in super‐resolution fluorescence imaging by combining rapid laser scanning, pixel‐addressed intensity modulation, and sCMOS camera detection. SS‐SIM yields 1.6× lateral and 1.7× axial resolution gains over wide‐field microscopy and enables imaging through 300–600 µm ...
Sha An   +8 more
wiley   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

open access: yesAdvanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren   +6 more
wiley   +1 more source

Perancangan dan Implementasi Sistem Pengaturan Kecepatan Motor BLDC Menggunakan Kontroler PI Berbasiskan Neural-Fuzzy Hibrida Adaptif [PDF]

open access: yes, 2016
Mobil listrik menjadi inovasi terbaru dengan tujuan utama untuk melepaskan ketergantungan pada bahan bakar minyak. Penelitian yang telah ada memaparkan bahwa motor listrik yang sesuai untuk menggerakkan mobil listrik adalah motor Brushless Direct Current
Wicaksono, A. S. (Agung)
core   +2 more sources

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

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