Results 101 to 110 of about 3,016,682 (331)

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian   +6 more
wiley   +1 more source

Analysis and Design of High Order Active Filter Circuit

open access: yesKongzhi Yu Xinxi Jishu
In analog sampling circuits, filters are essential for processing sampled signals before they are sent to DSP for further processing, to avoid clutter interference on them.
LIU Yuran   +4 more
doaj   +3 more sources

Design method for VDCC-based analog comb filter for power line interference cancellation

open access: yesMethodsX
An analog comb filter is implemented by linking multiple VDCC-based notch filters in a cascading fashion (N in total), eliminating N different pole frequencies. This study focuses on suppressing a fundamental frequency of power-line interference of 50 Hz
Chandan Kumar Choubey   +2 more
doaj   +1 more source

Intracerebral Hemorrhage Induces Monocyte TNF Signaling in Patients That Is Suppressed by BAF312

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Intracerebral hemorrhage (ICH) causes high morbidity and mortality, with neurotoxic inflammation driven by infiltrating monocytes. This study is an in‐depth longitudinal examination of the immune response during the first week of ICH in the presence and absence of the immunomodulatory drug BAF312 (Siponimod).
Jonathan Howard DeLong   +10 more
wiley   +1 more source

Headphone with Active Noise Control using Analog Adaptive Filters

open access: yes, 2008
Traditional methods of acoustic noise control are based on materials that absorb sound waves. These methods employ relatively bulky materials, and present some deficiencies that become more important at low frequencies.
Alex José Veloso A   +1 more
core  

Region Specific miRNA–mRNA Networks in Gray and White Matter Lesions of Progressive Multiple Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Multiple sclerosis (MS) is a neurodegenerative demyelinating disease of the central nervous system. This study aimed to identify micro‐RNA (miRNA)–mRNA regulatory networks underlying region‐specific molecular mechanisms in white matter and gray matter lesions in progressive MS.
Adya Sapra   +5 more
wiley   +1 more source

Linear circuit design handbook

open access: yes, 2008
This book enables design engineers to be more effective in designing discrete and integrated circuits by helping them understand the role of analog devices in their circuit design.
Zumbahlen, Hank, Analog Devices, inc
core  

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella   +5 more
wiley   +1 more source

Complementary Metal Oxide Semiconductor Circuit Realization of Inverse Chebyshev Low-Pass Filter of Order (1 + α)

open access: yesFractal and Fractional
This paper presents the CMOS circuit realization of a low-pass Inverse Chebyshev fractional-order filter (FOF) of order (1 + α) using the inverse-follow-the-leader feedback (IFLF) topology.
Soubhagyaseetha Nettar   +3 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

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