Results 51 to 60 of about 9,231,625 (296)

Sampling and Π-sampling expansions

open access: yesProceedings Mathematical Sciences, 2000
Using the hyperfinite representation of functions and generalized functions, this paper develops a rigorous version of the so-called ``delta method'' approach to sampling theory. (For a derivation of the delta method using standard analysis, see \textit{M. Z. Nashed} and \textit{G. G. Walter} [Math. Control Signals Syst.
Sousa Pinto, J., Hoskins, R. F.
openaire   +1 more source

Sampling Correctors [PDF]

open access: yesSIAM Journal on Computing, 2016
In many situations, sample data is obtained from a noisy or imperfect source. In order to address such corruptions, this paper introduces the concept of a sampling corrector. Such algorithms use structure that the distribution is purported to have, in order to allow one to make "on-the-fly" corrections to samples drawn from probability distributions ...
Clément L. Canonne   +2 more
openaire   +5 more sources

sample

open access: yes, 2022
this is a sample.
Yumiko Tamura (13158249)
core   +1 more source

Heterogeneity in the Global Practice of Central Nervous System Staging in Pediatric Acute Lymphoblastic Leukemia

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Central nervous system (CNS) involvement in childhood acute lymphoblastic leukemia (ALL) is assessed by cell counting and cytomorphology from cerebrospinal fluid (CSF) and is used for treatment stratification worldwide. The ratio of “CNS2” patients in clinical trials ranges from 3% to 40%, with unclear prognostic significance ...
Laura Almási   +14 more
wiley   +1 more source

Potential of introduced oat samples under the conditions of the southern part of the Forest-Steppe zone of Ukraine

open access: yesPlant Varieties Studying and Protection, 2017
Purpose. To make comprehensive assessment of introduced oat samples of various eco-geographical origin under the conditions of the Forest-Steppe zone of Ukraine for the set of productivity and adaptability indices in order to define the most valuable ...
С. М. Холод
doaj   +1 more source

Mismatch Sampling

open access: yesInformation and Computation, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Raphaël Clifford   +4 more
openaire   +2 more sources

Emapalumab for Immune Effector Cell‐Associated Hemophagocytic Lymphohistiocytosis‐Like Syndrome Following CD19‐Directed CAR‐T in Two Patients With B‐ALL: Clinical and Biomarker Correlates

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Immune effector cell‐associated hemophagocytic lymphohistiocytosis‐like syndrome (IEC‐HS) is a life‐threatening hyperinflammatory toxicity distinct from cytokine release syndrome (CRS) and neurotoxicity following chimeric antigen receptor T‐cell (CAR‐T) therapy. In a single‐institution retrospective cohort of pediatric and young adult patients
Thomas J. Galletta   +6 more
wiley   +1 more source

On unlimited sampling [PDF]

open access: yes2017 International Conference on Sampling Theory and Applications (SampTA), 2017
Shannon's sampling theorem provides a link between the continuous and the discrete realms stating that bandlimited signals are uniquely determined by its values on a discrete set. This theorem is realized in practice using so called analog--to--digital converters (ADCs). Unlike Shannon's sampling theorem, the ADCs are limited in dynamic range. Whenever
Ayush Bhandari   +2 more
openaire   +3 more sources

The Role of Hematopoietic Cell Transplantation in Ataxia‐Telangiectasia

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Ataxia‐telangiectasia (A‐T) is a DNA repair disorder characterized by neurodegeneration, immunodeficiency, and cancer predisposition. Hematopoietic cell transplantation (HCT) is an established therapy in related disorders such as Fanconi anemia (FA) and Nijmegen breakage syndrome (NBS), but its role in A‐T is unclear.
Laila Alkhouli   +3 more
wiley   +1 more source

Sample-level predictor: Sample-level embedding.

open access: yes, 2021
Sample-level embedding is calculated by averaging all the read-level embedding vectors per sample. Then, a random forest classifier is trained based on the sample embedding matrix (an N by Nh matrix where N is the total number of samples in training set ...
Felix Agbavor (11467482)   +5 more
core   +1 more source

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