AIMC Topic: Least-Squares Analysis

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From root to result: Portable NIRS-based non-destructive prediction of cassava quality traits.

PloS one
Cassava (Manihot esculenta Crantz) is a staple food and a key industrial crop across tropical regions, but traditional phenotyping for critical quality traits like dry matter content (DMC) and starch content (StC) is a laborious and low-throughput pr...

Influence of leadership on the adoption of circular and digital business models using PLS-SEM analysis.

Scientific reports
In a business environment characterised by growing pressure towards sustainability and digital transformation, leadership emerges as a determining factor in the adoption of sustainable, technology-driven business models. This study analyses how leade...

Multi-marker discovery for mild cognitive impairment in metabolomics using machine learning with a global surrogate model via partial least squares.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: Dementia can be prevented through early intervention; hence, there is an urgent need for biomarkers to help diagnose mild cognitive impairment (MCI).

Porosity prediction from well logging data via a hybrid MABC-LSSVM model.

PloS one
Porosity is a key parameter for evaluating reservoir performance, but high-precision prediction is highly challenging in complex shale reservoirs due to the strong heterogeneity of the formation and the highly nonlinear relationship between logging p...

Research on egg yolk color detection based on near infrared spectroscopy and machine vision.

Analytical methods : advancing methods and applications
Yolk color is a key indicator of egg quality, as customers prefer eggs with intensely yellow yolks, which also signal nutrient richness. At present, the commonly used method for yolk color detection is to open the eggs and evaluate the yolk color usi...

Rapid Screening and Prioritization of Culture Conditions for Natural Product Discovery using the Liquid Microjunction Surface Sampling Probe.

Journal of the American Society for Mass Spectrometry
The discovery of novel bioactive compounds remains a cornerstone of natural product (NP) chemistry. However, traditional NP discovery workflows are time- and resource-intensive, hindering sustainability and efficiency of multicondition screening proj...

ADPO: automatic-differentiation-assisted parametric optimization.

Journal of pharmacokinetics and pharmacodynamics
Automatic differentiation (AD), a key method for accurately and efficiently computing derivatives in modern machine learning, is now implemented in Phoenix® NLME™ 8.6 for the first time and applied to the first-order conditional estimation extended l...

FTIR spectroscopy imaging coupled with machine learning reveals biochemical changes in the brains of diabetic mice.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Diabetic encephalopathy is a progressive complication of type 2 diabetes, yet its region-specific biochemical changes remain unclear. In this study, we applied Fourier Transform Infrared Microspectroscopy (FTIRM) to assess metabolic alterations in th...

Predicting fracture toughness of human cortical bone from donors with and without type 2 diabetes using Raman spectroscopy and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Type 2 diabetes mellitus (T2DM) is associated with increased skeletal fragility, yet standard clinical assessments often fail to detect diabetes-induced changes in bone quality. Raman spectroscopy (RS), a label-free and non-destructive technique, off...

Species discrimination and VIP-stacking quantitative models for Curcumae Rhizoma utilizing multi-modal spectra combined with machine learning algorithm.

Journal of pharmaceutical and biomedical analysis
Curcumae Rhizoma (Ezhu) is a multi-species herbal medicine with excellent medicinal value and development potential. However, challenges such as the difficulty in differentiating its varieties and the limitations of current methods for determining mi...