Results 41 to 50 of about 1,141,332 (255)

Aboveground and belowground tree biomass and carbon stocks in the miombo woodlands of the Copperbelt in Zambia

open access: yesCarbon Management, 2021
Globally, belowground biomass (BGB) accounts for 20–26% of total biomass, and as such it is an important carbon (C) pool for many vegetation types. However, large uncertainty exists for belowground biomass C compared to aboveground stocks.
Ferdinand Handavu   +3 more
doaj   +1 more source

iDNA6mA-Rice: A Computational Tool for Detecting N6-Methyladenine Sites in Rice

open access: yesFrontiers in Genetics, 2019
DNA N6-methyladenine (6mA) is a dominant DNA modification form and involved in many biological functions. The accurate genome-wide identification of 6mA sites may increase understanding of its biological functions.
Hao Lv   +7 more
doaj   +1 more source

Procrustes Cross-Validation — a Bridge Between Cross-Validation and Independent Validation Set [PDF]

open access: yesAnalytical Chemistry, 2020
In this paper we propose a new approach for validation of chemometric models. It is based on k-fold cross-validation algorithm, but, in contrast to conventional cross-validation, our approach makes possible to create a new dataset, which carries sampling uncertainty estimated by the cross-validation procedure. This dataset, called
Sergey Kucheryavskiy   +3 more
openaire   +2 more sources

Scale Issues Related to the Accuracy Assessment of Land Use/Land Cover Maps Produced Using Multi-Resolution Data: Comments on “The Improvement of Land Cover Classification by Thermal Remote Sensing”. Remote Sens. 2015, 7(7), 8368–8390

open access: yesRemote Sensing, 2015
Much remote sensing (RS) research focuses on fusing, i.e., combining, multi-resolution/multi-sensor imagery for land use/land cover (LULC) classification. In relation to this topic, Sun and Schulz [1] recently found that a combination of visible-to-near
Brian A. Johnson
doaj   +1 more source

Multifidelity Cross-Validation

open access: yesAIAA AVIATION FORUM AND ASCEND 2024
arXiv admin note: text overlap with arXiv:2203 ...
Renganathan, S. Ashwin, Carlson, Kade
openaire   +2 more sources

Bridging the Loneliness Gap: Depression, Connectivity, and Isolation in Pediatric Oncology Patients and Their Peers

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Loneliness is associated with adverse physical and mental health outcomes and remains understudied in children and adolescents undergoing cancer therapy. Pediatric oncology patients may be at increased risk due to medical isolation and disruption of social networks.
Charlotte N. Stahlfeld   +5 more
wiley   +1 more source

Data-driven insight into groundwater potential: A generalized additive model application for hilly region river catchment, central Nepal

open access: yesEnvironmental Challenges
Groundwater is one of the most important natural resources in many parts of the world and requires new and advanced technologies for monitoring and control.
Ananta Man Singh Pradhan   +4 more
doaj   +1 more source

Machine Learning of Raman Spectroscopy Data for Classifying Cancers: A Review of the Recent Literature

open access: yesDiagnostics, 2022
Raman Spectroscopy has long been anticipated to augment clinical decision making, such as classifying oncological samples. Unfortunately, the complexity of Raman data has thus far inhibited their routine use in clinical settings.
Nathan Blake   +4 more
doaj   +1 more source

Comparative Drug Response Profiling in Neuroblastoma Cell Lines and Patient‐Derived Tumor Organoids

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT High‐risk neuroblastoma remains a leading cause of pediatric cancer mortality, and improved preclinical models are needed to guide therapeutic developments. We screened seven high‐risk neuroblastoma cell lines and three patient‐derived tumor organoids with 528 compounds alongside bone marrow controls, and compared them with external datasets ...
Krzysztof Wierbiłowicz   +12 more
wiley   +1 more source

Cross-validation

open access: yes, 2017
This text is a survey on cross-validation. We define all classical cross-validation procedures, and we study their properties for two different goals: estimating the risk of a given estimator, and selecting the best estimator among a given family. For the risk estimation problem, we compute the bias (which can also be corrected) and the variance of ...
  +7 more sources

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