Results 111 to 120 of about 272,931 (273)
Schichten mit geschätzten Schichtgrößen II
(Eine Weiterentwicklung und eine Korrektur zum Artikel des gleichen Autors im Heft 1/1996 der Österreichischen Zeitschrift für Statistik)
Andreas Quatember
doaj +1 more source
Beyond the Ban—Shedding Light on Smallholders' Price Vulnerability in Indonesia's Palm Oil Industry
ABSTRACT The Indonesian government imposed a palm oil export ban in April 2022 to address rising cooking oil prices. This study explores oil palm smallholders' vulnerability to the policy using descriptive statistics, Lasso, and post‐Lasso OLS regressions.
Charlotte‐Elena Reich +3 more
wiley +1 more source
Markovian acyclic directed mixed graphs for discrete data
Acyclic directed mixed graphs (ADMGs) are graphs that contain directed ($\rightarrow$) and bidirected ($\leftrightarrow$) edges, subject to the constraint that there are no cycles of directed edges.
Evans, Robin J., Richardson, Thomas S.
core +1 more source
Climate Change Agricultural Comparative Advantage and the US Trade Balance
ABSTRACT Current science indicates that warming and elevated atmospheric CO2 will have ambiguous results for crop productivity depending on crop type and geographic location, whereas increased heat stress makes livestock and human labor less productive.
Elizabeth A. Fraysse +2 more
wiley +1 more source
Minimally invasive anatomic liver resection (AR) including major hepatectomy and liver parenchyma‐sparing AR is technically complex and demanding. This systematic review with meta‐analysis including 15 studies comparing 2042 robotic AR and 2129 laparoscopic AR patients demonstrated largely comparable perioperative outcomes and partly better outcomes ...
Yutaro Kato +3 more
wiley +1 more source
Posterior consistency of Gaussian process prior for nonparametric binary regression
Consider binary observations whose response probability is an unknown smooth function of a set of covariates. Suppose that a prior on the response probability function is induced by a Gaussian process mapped to the unit interval through a link function ...
Ghosal, Subhashis, Roy, Anindya
core +1 more source
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +1 more source
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
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia +3 more
wiley +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source

