Results 121 to 130 of about 5,059,929 (339)

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

open access: yesMolecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova   +14 more
wiley   +1 more source

Linear estimation in Krein spaces. Part II. Applications [PDF]

open access: yes, 1996
We have shown that several interesting problems in H∞-filtering, quadratic game theory, and risk sensitive control and estimation follow as special cases of the Krein-space linear estimation theory developed in Part I. We show that all these problems can
Hassibi, Babak   +2 more
core  

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

open access: yesMolecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh   +12 more
wiley   +1 more source

An Adaptive Filtering Approach Based on the Dynamic Variance Model for Reducing MEMS Gyroscope Random Error

open access: yesSensors, 2018
To improve the dynamic random error compensation accuracy of the Micro Electro Mechanical System (MEMS) gyroscope at different angular rates, an adaptive filtering approach based on the dynamic variance model was proposed.
Yanshun Zhang   +4 more
doaj   +1 more source

A kepstrum approach to filtering, smoothing and prediction [PDF]

open access: yes, 2002
The kepstrum (or complex cepstrum) method is revisited and applied to the problem of spectral factorization where the spectrum is directly estimated from observations.
Barrett, J.F., Moir, T.J.
core  

Kalman-Takens filtering in the presence of dynamical noise

open access: yes, 2016
The use of data assimilation for the merging of observed data with dynamical models is becoming standard in modern physics. If a parametric model is known, methods such as Kalman filtering have been developed for this purpose.
Berry, Tyrus   +2 more
core   +1 more source

CD47 promotes mitogen‐activated protein kinase and epithelial‐to‐mesenchymal transition molecular programs to drive prometastatic phenotypes in non‐small cell lung cancer

open access: yesMolecular Oncology, EarlyView.
Beyond its role in immune evasion, this study identified that CD47 drives tumor‐intrinsic signaling in non‐small cell lung cancer (NSCLC). Transcriptomic profiling and functional studies revealed that CD47 regulates cell adhesion, migration, and metastasis through an ERK–EMT signaling axis.
Asa P.Y. Lau   +8 more
wiley   +1 more source

KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer

open access: yesMolecular Oncology, EarlyView.
Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan   +16 more
wiley   +1 more source

A GNSS Anti-jamming Technology of UAV for Geological Hazard Monitoring

open access: yesJournal of Harbin University of Science and Technology
In this paper,a GNSS anti-jamming technology of UAV for geological hazard survey is designed to realize adaptive interference suppression without vacuum loss under strong jamming environment.
ZHANG Yonggang, ZHOU Chaorong, SHEN Feng
doaj   +1 more source

Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods

open access: yes, 2019
We formulate the problem of neural network optimization as Bayesian filtering, where the observations are the backpropagated gradients. While neural network optimization has previously been studied using natural gradient methods which are closely related
Aitchison, Laurence
core  

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