Unsupervised Clustering-Assisted Method for Consensual Quantitative Analysis of Methanol-Gasoline Blends by Raman Spectroscopy.

Methanol-gasoline blends have emerged as a promising and environmentally friendly bio-fuel option, garnering widespread attention and promotion globally. The methanol content within these blends significantly influences their quality and combustion performance. This study explores the qualitative and qualitative analysis of methanol-gasoline blends using Raman spectroscopy coupled with machine learning methods.

Regulation of Chirality in Metal-Organic Frameworks (MOFs) Based on Achiral Precursors through Substituent Modification.

The generation and regulation of chirality are closely related to the origin of life. Using achiral precursors to spontaneously build chiral MOFs remains a major challenge. Here, a method to synthesize chiral MOFs from achiral precursors by utilizing chiral fragments was achieved.

Consensual Regression of Soluble Solids Content in Peach by Near Infrared Spectrocopy.

In order to reduce the uncertainty of the genetic algorithm (GA) in optimizing the near-infrared spectral calibration model and avoid the loss of spectral information of the unselected variables, a strategy of fusing consensus models is proposed to measure the soluble solids content (SSC) in peaches. A total of 266 peach samples were collected at four arrivals, and their interactance spectra were scanned by an integrated analyzer prototype, and then an internal index of SSC was destructively measured by the standard refractometry method. The near-infrared spectra were pre-processed with mean centering and were selected successively with a genetic algorithm (GA) to construct the consensus model, which was integrated with two member models with optimized weightings.

Using one-class autoencoder for adulteration detection of milk powder by infrared spectrum.

Food adulteration detection requires quick and simple methods. Spectral detection can significantly reduce the analysis time, but it needs to construct a detection model. In this study, a one-class classification method based on an autoencoder is proposed for the detection of food adulteration by spectroscopy.

Recent Advances in Silver and Gold Nanoparticles-Based Colorimetric Sensors for Heavy Metal Ions Detection: A Review.

Silvetr and gold nanoparticles-based colorimetric sensors (Ag/Au-NPs-CSns) allow potential prospects for the development of efficient sensors owing to their unique shape- and size-dependent optical properties. In this review, recent (2020) advances in morphology-controllable synthesis, shape/size-dependent performance, sensing mechanism, challenges and prospects of Ag/Au-NPs-CSns for the detection of heavy metals are discussed. The size/shape-controlled synthesis of innovative Ag/Au-NPs-CSns is reviewed critically and the possible role of different parameters like temperature, time, pH, stabilizing/capping agents, reducing agents and concentration/nature of precursors are discussed.

Molecular engineering in a family of pillared-layered metal-organic frameworks for tuning gas adsorption behavior.

In this work, inspired by a water-assisted three-dimensional supramolecular structure 1, we use a mixed-ligand strategy to form a 3D pillared-layered matrix by the introduction of linear ligands to compete against the water molecules. The resulting analogue microporous MOFs of 2-H, 2-F and 2-N, decorated with different functional groups, similarly show the CO2 uptake. Thanks to the negligible N2 adsorption capacity, enhanced selective adsorption towards CO2 is achieved in compound 2-N.

Degradation degree analysis of environmental microplastics by micro FT-IR imaging technology.

The degradation potential of microplastics remains a critical issue for researching marine litter, and it is one of the most important factors that can be used for calculating the persistence time of microplastics in certain conditions. However, there are lack of standard or approved methods for estimating the ageing stage of environmental microplastics. In this study, the potential of spectral-image fusion strategy was investigated to analyze the degradation degree of polyethylene microplastics in natural exposure of coastline.

Rapid Assessment of Exercise State through Athlete's Urine Using Temperature-Dependent NIRS Technology.

Athletes usually take nutritional supplements and perform the specialized training to improve the performance of sport. A quick assessment of their athletic status will help to understand the current physical function of athletes' status and the effect of nutritional supplementation. Human urine, as one of the most important body indicators, is composed of many metabolites, which can provide effective monitoring information for physical conditions.

Synthetic spectra generated by boundary equilibrium generative adversarial networks and their applications with consensus algorithms.

One of the major restrictions in spectroscopic analysis is the limited number of calibrations, especially for biological samples. Meanwhile, there is a lack of effective algorithms to simulate synthetic spectra from the real spectra of limited samples. Thus in this work, a boundary equilibrium generative adversarial network (BEGAN) was proposed to automatically generate synthetic spectra and successfully produce spectra from two datasets.

Using Class-Specific Feature Selection for Cancer Detection with Gene Expression Profile Data of Platelets.

A novel multi-classification method, which integrates the elastic net and probabilistic support vector machine, was proposed to solve this problem in cancer detection with gene expression profile data of platelets, whose problems mainly are a kind of multi-class classification problem with high dimension, small samples, and collinear data. The strategy of one-against-all (OVA) was employed to decompose the multi-classification problem into a series of binary classification problems. The elastic net was used to select class-specific features for the binary classification problems, and the probabilistic support vector machine was used to make the outputs of the binary classifiers with class-specific features comparable.

A two-dimensional cadmium(II) coordination polymer based on 5-(pyridin-4-yl)isophthalic acid: poly[[tetraaquabis[μ₃-5-(pyridin-4-yl)isophthalato]dicadmium(II)] pentahydrate].

The title Cd(II) compound, {[Cd2(C13H7NO4)2(H2O)4]·5H2O}n, was synthesized by the hydrothermal reaction of Cd(NO3)2·4H2O and 5-(pyridin-4-yl)isophthalic acid (H2L). The asymmetric unit contains two crystallographically independent Cd(II) cations, two deprotonated L(2-) ligands, four coordinated water molecules and five isolated water molecules. One of the Cd(II) cations adopts a six-coordinate octahedral coordination geometry involving three O atoms from one bidentate chelating and one monodentate carboxylate group of two different L(2-) ligands, one N atom of another L(2-) ligand and two coordinated water molecules.

[Simplification of NIR model for citrus's sugar content based on sensory methods].

The prediction of sugar content (SC) in citrus by near-infrared spectroscopy (NIRS) and sensory test was investigated the validation whether the result of non-destructive determination methods by NIRS can meet the request of consumers' sensory or not, and the simplification of the prediction model of NIRS for citrus's SC with variables selection on the basis of meeting their demands. Result of the latter analyzed by one-way ANOVA shows that there was a significant difference influenced by individual diversity, but not by gender. After excluding the sensuous outliers, root mean standard error of deviation (RMSED) of every participator was calculated and the minimum equaled to 0.