Rapid Characterization Research Articles

Comparable analysis of flavor compounds and quality assessment of fermented bean curd using HS-SPME-GC/MS and colorimetric sensor array

This study aims to develop an effective tool by integrating traditional analysis methods with advanced sensor array technology and multiple algorithms, to achieve rapid characterization, qualitative identification, and flavor quality evaluation of fermented bean products. Firstly, the flavor compounds and flavor profiles of fermented bean curd from different manufacturers were identified using headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) and quantitative descriptive analysis (QDA). A total of 63 volatile compounds were identified, of which 13 volatile compounds were identified as the key differential compounds in selected samples. Eight descriptors were selected to represent the aroma characteristics of fermented bean curd. Based on the key differential compounds, a low-cost colorimetric sensor array (CSA) was designed and constructed. Furthermore, the feasibility of CSA combined with multiple algorithms was investigated for brand discrimination and flavor quality assessment. Linear discriminant analysis (LDA) exhibited a better performance in distinguishing different flavor quality samples, and the recognition accuracy of its prediction set was 97.22%. The study suggests that CSA combined with multiple algorithms can be an effective tool for flavor characterization and qualitative discrimination of fermented bean curd, and can provide a new multi-dimensional analysis method for food analysis.

Rapid standoff spectroscopic characterization of plastic waste using quartz tuning fork

Standoff molecular identification of chemicals finds immense applications in homeland security, forensic investigation and plastic recycling industries. Although, standoff detection using mid-infrared radiation offers excellent molecular selectivity, sensitive detection of mid-IR radiation using inexpensive detectors is a challenge. In the present work, we show commercially available inexpensive Quartz Tuning Fork (QTF) can be effectively used for rapid standoff detection of solid samples using mid-IR radiation. In this method, a plastic sample placed 40 cm away was excited with tunable infrared (IR) radiation pulsed at the resonance frequency of the QTF. The IR radiation scattered off the plastic sample was used for exciting the QTF into resonance. Plotting the QTF resonant amplitude as a function of irradiating IR wavelength represents the unique IR spectrum of the plastic sample under study. The resolution of spectra recorded using QTF was found to be superior to those collected with ATR-FTIR and the technique based on QTF was 103 times faster than microcantilever-based photothermal deflection techniques. By combining simple machine learning algorithms with QTF standoff resonance IR spectra, various plastic samples can be effectively classified with 100% accuracy. Also, this technique was found to be capable of identifying black plastics without any further sample preparation requirements.

In-situ rapid nondestructive characterization of multiple irregular three-dimensional grain boundary structures and electrical properties by nanorobot with SEM in ZnO

To address the problem of spatial quantification of irregular grain boundaries, a unique approach for the nondestructive characterization of multiple irregular three-dimensional grain boundaries is proposed using nanorobots with scanning electron microscopy (SEM) to accomplish in-situ rapid synchronized quantification of structures and electrical properties. By constructing a three-dimensional trigonometric geometric mapping relationship, multiple irregular three-dimensional grain boundary structures and electrical properties can be rapidly quantified. Experimental results demonstrate that it is feasible to accomplish in-situ rapid nondestructive characterizations. The two-dimensional profile shapes of the targeted grain boundaries at each layer exhibit irregular and non-uniform features in the Y-Z plane. The hypotenuse length between the virtual space tilting lines presents a three-dimensional characteristic in the X-Z plane. The spatial tilt angle of the virtual space tilting line can be calculated using the right-triangle relation. The unequal numbers of grains along the same tilted hypotenuse direction with equal lengths directly illustrate the existence of irregular and nonlinear grain boundaries in bulk ZnO ceramics. The relatively uniform spatial sizes of the grain boundary illustrate the coupled spatial characteristics existing in the irregular micro-structures. The relatively uniform equivalent circuit fitting parameters confirm the existence of relatively uniform doping components in bulk ZnO ceramics. Furthermore, this method provides a unique approach for the rapid nondestructive quantitative analysis of multiple three-dimensional irregular grain boundaries in bulk polycrystalline materials.

Rapid characterization of kraft lignin depolymerisation products by high-resolution mass spectrometry with visualization of mass spectrometric data

Rapid characterization of kraft lignin depolymerisation products by high-resolution mass spectrometry with visualization of mass spectrometric data

High-throughput tagging of endogenous loci for rapid characterization of protein function.

To facilitate the interrogation of protein function at scale, we have developed high-throughput insertion of tags across the genome (HITAG). HITAG enables users to rapidly produce libraries of cells, each with a different protein of interest C-terminally tagged. HITAG is based on a modified strategy for performing Cas9-based targeted insertions, coupled with an improved approach for selecting properly tagged lines. Analysis of the resulting clones generated by HITAG reveals high tagging specificity, with most successful tagging events being indel free. Using HITAG, we fuse mCherry to a set of 167 stress granule-associated proteins and elucidate the features that drive a subset of proteins to strongly accumulate within these transient RNA-protein granules.

Characterisation and critical processes identification for production of herbal preparations using 1H-NMR and chemometrics: A case study of Trichosanthis Pericarpium injection.

Herbal preparations are extensively utilised for the treatment of diseases in Asian countries. However, the variations in origin, climate, and production processes can lead to inconsistencies in the quality of herbal preparations. Existing quality control methods only target a few components in the finished product but ignore the control in the pharmaceutical process. Therefore, this study intends to develop a comprehensive component analysis method for intermediates in the pharmaceutical process to reveal the change patterns of substances and deepen the process understanding. This study aims to develop a rapid and comprehensive process characterisation and critical process identification method for herbal preparations. Six batches of Trichosanthis Pericarpium injection (TPI) intermediates were collected from the production process. Proton nuclear magnetic resonance (1H-NMR) spectra were acquired for qualitative and quantitative analysis of the se intermediates. Subsequently, chemometrics were used to identify critical processes and potential chemical markers. A total of 39 components in intermediates were identified, and the transfer of 25 components during the production process was investigated. Column chromatography was determined as the critical process. Nine components were identified as chemical markers. The application of 1H-NMR facilitated a comprehensive reflection of the chemical composition information of process intermediates, enabling investigations into the transfer of multi-component substances and accurate identification of critical processes and chemical markers.

Interfacial Second-Harmonic Generation via Superposition of Symmetries in a Double-Resonance-Enhanced Plasmonic Nanocavity.

Second-harmonic generation (SHG) has rapidly advanced with the miniaturization of on-chip devices and has found many applications, including optical frequency conversion, nonlinear imaging, and quantum technology. However, owing to the obvious phase-matching constraints involved in nonlinear optical interactions in bulk crystals and the decrease in the length and strength of nonlinear interactions in nanophotonic and surface/interface systems, improving the SHG efficiency and manipulating its optical properties at the nanoscale are challenging tasks. Herein, a monocrystalline silver microplate and nanocube-coupled nanocavity with double-resonance plasmonic modes and an ultrasmall gap were constructed, resulting in efficiently enhanced SHG. In particular, the SHG from the silver microplate (111) is polarization-dependent, and the anisotropy of the SHG in the plasmonic nanocavity can be further controlled via the superposition of symmetries at the interface and plasmonic waveguide-cavity modes. The interfacial SHG provides technology for developing lattice surface atomic arrangement and nanostructure rapid characterization, nonlinear light sources, and on-chip nonlinear nanophotonic devices.

Innovative methods for microplastic characterization and detection: Deep learning supported by photoacoustic imaging and automated pre-processing data

Plastic products' widespread applications and their non-biodegradable nature have resulted in the continuous accumulation of microplastic waste, emerging as a significant component of ecological environmental issues. In the field of microplastic detection, the intricate morphology poses challenges in achieving rapid visual characterization of microplastics. In this study, photoacoustic imaging technology is initially employed to capture high-resolution images of diverse microplastic samples. To address the limited dataset issue, an automated data processing pipeline is designed to obtain sample masks while effectively expanding the dataset size. Additionally, we propose Vqdp2, a generative deep learning model with multiple proxy tasks, for predicting six forms of microplastics data. By simultaneously constraining model parameters through two training modes, outstanding morphological category representations are achieved. The results demonstrate Vqdp2's excellent performance in classification accuracy and feature extraction by leveraging the advantages of multi-task training. This research is expected to be attractive for the detection classification and visual characterization of microplastics.

A feasibility study on phase characterisation of nickel-based superalloys using ultrasound

The use of nickel-based superalloys, such as Inconel 718, Udimet 720Li and Waspaloy, is widespread across the engineering industry due to their superior mechanical properties at elevated temperatures and excellent resistance to creep and fatigue under harsh working conditions. The microstructure of these materials, such as the precipitates and grain sizes, strongly influence the materials’ performance. Currently, existing materials characterisation methods are time-consuming, costly and destructive, as well as only capable of taking measurements of surface or near-surface properties.This paper presents a novel ultrasonic technique for bulk materials characterisation of nickel-based superalloys, based on a spherical harmonic convolution theory which has been successfully used to quantify texture in various metals; it is applied here to study a nickel-based superalloy, with a specific focus on the phase changes when subject to thermal loading. The key parameter used to interpret phase information of a material is the zeroth spherical harmonic coefficient of ultrasonic wave velocities, V00, which corresponds to the average velocities across all directions in 3D space and is independent of crystallographic texture. Experimental investigation using samples of a representative material, Inconel 718, with contrasting microstructures, has shown a clear and quantifiable sensitivity of this coefficient to microstructural changes occurring within the material, and has thus laid the foundations for the development of a rapid phase characterisation technique for nickel-based superalloys using ultrasound.

Prediction of Total Petroleum Hydrocarbons and Heavy Metals in Acid Tars Using Machine Learning

Hazardous petroleum wastes are an inevitable source of environmental pollution. Leachates from these wastes could contaminate soil and potable water sources and affect human health. The management of acid tars, as a byproduct of refining and petrochemical processes, represented one of the major hazardous waste problems in Romania. Acid tars are hazardous and toxic waste and have the potential to cause pollution and environmental damage. The need for the identification, study, characterization, and subsequently either the treatment, valorization, or elimination of acid tars is determined by the fact that they also have high concentrations of hydrocarbons and heavy metals, toxic for the storage site and its neighboring residential area. When soil contamination with acid tars occurs, sustainable remediation techniques are needed to restore soil quality to a healthy production state. Therefore, it is necessary to ensure a rapid but robust characterization of the degree of contamination with hydrocarbons and heavy metals in acid tars so that appropriate techniques can then be used for treatment/remediation. The first stage in treating these acid tars is to determine its properties. This article presents a software program that uses machine learning to estimate selected properties of acid tars (pH, Total Petroleum Hydrocarbons—TPH, and heavy metals). The program uses the Automatic Machine Learning technique to determine the Machine Learning algorithm that has the lowest estimation error for the given dataset, with respect to the Mean Average Error and Root Mean Squared Error. The chosen algorithm is used further for properties estimation, using the R2 correlation coefficient as a performance criterion. The dataset used for training has 82 experimental points with continuous, unique values containing the coordinates and depth of acid tar samples and their properties. Based on an exhaustive search performed by the authors, a similar study that considers machine learning applications was not found in the literature. Further research is required because the method presented therein can be improved because it is dataset dependent, as is the case with every ML problem.

Simultaneous magnitude and slip distribution characterization from high-rate GNSS using deep learning: case studies of the 2021 Mw 7.4 Maduo and 2023 Turkey doublet events

SUMMARY Rapid and accurate characterization of earthquake sources is crucial for mitigating seismic hazards. In this study, based on 18 000 scenario ruptures ranging from Mw 6.4 to Mw 8.3 and corresponding synthetic high-rate Global Navigation Satellite System (HR-GNSS) waveforms, we developed a multibranch neural network framework, the continental large earthquake agile response (CLEAR), to simultaneously determine the magnitude and slip distributions. We apply CLEAR to recent large strike-slip events, including the 2021 Mw 7.4 Maduo earthquake and the 2023 Mw 7.8 and Mw 7.6 Turkey doublet. The model generally estimates the magnitudes successfully at 32 s with errors of less than 0.15, and predicts the slip distributions acceptably at 64 s, requiring only approximately 30 ms on a single CPU (Central Processing Unit). With optimal azimuthal coverage of stations, the system is relatively robust to the number of stations and the time length of the received data.

Viroids of the Mediterranean Basin.

There has been substantial progress in the Mediterranean countries regarding research on viroids. Twenty-nine viroid species, all belonging to Pospiviroidae and Avsunviroidae genera, have been detected in the Mediterranean Basin. Not only have detection methods, such as reverse transcription-quantitative polymerase chain reaction and next-generation sequencing, been used for viroid detection, along with molecular hybridization techniques allowing for rapid detection, identification, and characterization of known and novel viroids in these countries, but eradication measures have also been taken that allowed for the efficient elimination of certain viroids in a number of Mediterranean countries. The eradication measures were followed as recommended by the European and Mediterranean Plant Protection Organization, which is known by its abbreviation, EPPO. The Mediterranean Region has been a niche for viroids since ancient times due to the warm climate and the socio-cultural conditions that facilitate viroid transmission among different host plant species.

Rapid Characterization of Undeclared Pharmaceuticals in Herbal Preparations by Ambient Ionization Mass Spectrometry for Emergency Care.

In Asia, some herbal preparations have been found to be adulterated with undeclared synthetic medicines to increase their therapeutic efficiency. Many of these adulterants were found to be toxic when overdosed and have been documented to bring about severe, even life-threatening acute poisoning events. The objective of this study is to develop a rapid and sensitive ambient ionization mass spectrometric platform to characterize the undeclared toxic adulterated ingredients in herbal preparations. Several common adulterants were spiked into different herbal preparations and human sera to simulate the clinical conditions of acute poisoning. They were then sampled with a metallic probe and analyzed by the thermal desorption-electrospray ionization mass spectrometry. The experimental parameters including sensitivity, specificity, accuracy, and turnaround time were prudently optimized in this study. Since tedious and time-consuming pretreatment of the sample is unnecessary, the toxic adulterants could be characterized within 60 s. The results can help emergency physicians to make clinical judgments and prescribe appropriate antidotes or supportive treatment in a time-sensitive manner.

Distribution, Migration and Ecological Effects of Microplastics in Marine Environment

The issue of microplastic pollution has garnered significant attention from governments worldwide and the academic community. Numerous scholarly investigations and regulatory frameworks have been developed pertaining to microplastics. This article presents a comprehensive survey of the advancements made in the investigation and study of microplastics in the global marine ecosystem. It introduces the fundamental characteristics of microplastics, including definitions, classifications, and sources, as well as the patterns of distribution and migration observed in the marine environment. This study also presents the harmful effects of microplastics on marine animals and the resulting ecological impacts on marine systems. Additionally, it discusses worldwide strategies for managing microplastics in marine environments and explores potential avenues for future research in this field. Studies revealed that microplastics are mostly generated and released as a result of human activities. These microplastics tend to gather predominantly on the surface of the North Pacific and North Atlantic regions, which have the highest population density. Once marine species consume microplastics and other harmful pollutants transported by microplastics, these substances have the potential to be transferred down the biological food chain and ultimately enter the human body. Future studies of microplastics should prioritize the rapid characterization and quantification of microplastics in intricate samples, the biological interventions to influence the destiny of microplastics, and the examination of the interplay between microplastics and other contaminants. This article provides a comprehensive overview of the potential outcomes of microplastics and the associated factors and consequences at each stage.

Shotgun proteomic analyses of Pseudomonas species isolated from fish products

Numerous Pseudomonas species can infect aquatic animals, such as farmed rainbow trout, sea trout, sea bass, and sea bream, by causing disease or stress reactions. In aquaculture facilities, a number of Pseudomonas species have been isolated and identified as the main pathogens. The present study describes the characterization of 18 Pseudomonas strains, isolated from fish products using shotgun proteomics. The bacterial proteomes obtained were further analyzed to identify the main functional pathway proteins involved. In addition, this study revealed the presence of 1015 non-redundant peptides related to virulence factors. An additional 25 species-specific peptides were identified as putative Pseudomonas spp. biomarkers. The results constitute the largest dataset, described thus far for the rapid identification and characterization of Pseudomonas species present in edible fish; furthermore, these data can provide the basis for further research into the development of new therapies against these harmful pathogens.

Mapping and monitoring peatlands in the Belgian Hautes Fagnes: Insights from Ground-penetrating radar and Electromagnetic induction characterization

Peatlands are vital ecosystems providing crucial ecological services such as significant carbon storage in the context of climate change. These sensitive ecosystems are subjected to degradation due to land use change. In this context, it is important to understand the actual state of degraded peatlands and their recovery potential for regaining important functions. This study focuses on a disturbed peatland in the Belgian Hautes Fagnes, previously drained and planted with spruce, and characterized by a topographic gradient. We aimed to elucidate the use of Ground-penetrating radar (GPR) and Electromagnetic induction (EMI) techniques in characterizing such peatlands, with a specific focus on their implications for peat depth and electrical conductivity assessment, related to peatland degradation. The GPR revealed a high spatial heterogeneity in peat depth, ranging from 0.2 to more than 2 m on the site. In contrast, an EMI instrument used with single coil spacing proved to be unsuccessful to deduce peat depth but demonstrated potential for the delineation of zones of mineral soil. It is also shown that the links between soil physical and chemical properties and its bulk soil electrical conductivity (ECa) measured by EMI are complex in zones of shallower peat. Additionally, this study highlights the role of pore water conductivity in influencing temporal variations in ECa. Our findings explain the intricate interplay between peat depth, topography and ECa in disturbed peatlands. The results of this study may be of substantial societal interest, as it provides insights into techniques for the rapid non destructive characterization of the conditions of previously drained peatlands.

Numerical study on the characterization of NdFeB permanent magnets with fast-neutrons induced (n, n′γ) reactions

The potential of prompt gamma analysis based on inelastic scattering of 2.5 MeV neutrons for a rapid characterization of NdFeB permanent magnets is investigated by means of numerical simulations using an HPGe detector and a CZT detector-array. The results show that rapid assay of a 42 g magnet can be achieved in some minutes when the neutron flux at sample position is about 1.6 × 109 cm−2 s−1 and the detector count rate limited to 500 kcps. Such a high neutron flux could be delivered by a compact 5 MeV proton accelerator with a thick beryllium target for neutron production through the 9Be(p,xn)9Be.

Unlocking the distinctive enzymatic functions of the early plant biomass deconstructive genes in a brown rot fungus by cell-free protein expression.

Saprotrophic fungi that cause brown rot of woody biomass evolved a distinctive mechanism that relies on reactive oxygen species (ROS) to kick-start lignocellulosic polymers' deconstruction. These ROS agents are generated at incipient decay stages through a series of redox relays that shuttle electrons from fungus's central metabolism to extracellular Fenton chemistry. A list of genes has been suggested encoding the enzyme catalysts of the redox processes involved in ROS's function. However, navigating the functions of the encoded enzymes has been challenging due to the lack of a rapid method for protein synthesis. Here, we employed cell-free expression system to synthesize four redox or degradative enzymes, which were identified, by transcriptomic data, as conserved players of the ROS oxidation phase across brown rot fungal species. All four enzymes were successfully expressed and showed activities that enable confident assignment of function, namely, benzoquinone reductase (BQR), ferric reductase, α-L-arabinofuranosidase (ABF), and heme-thiolate peroxidase (HTP). Detailed analysis of their catalytic features within the context of brown rot environments allowed us to interpret their roles during ROS-driven wood decomposition. Specifically, we validated the functions of BQR as the driver redox enzyme of Fenton cycles and reconstructed its interactions with the co-occurring HTP or laccase and ABF. Taken together, this research demonstrated that the cell-free expression platform is adequate for synthesizing functional fungal enzymes and provided an alternative route for the rapid characterization of fungal proteins, escalating our understanding of the distinctive biocatalyst system for plant biomass conversion.IMPORTANCEBrown rot fungi are efficient wood decomposers in nature, and their unique degradative systems harbor untapped catalysts pursued by the biorefinery and bioremediation industries. While the use of "omics" platforms has recently uncovered the key "oxidative-hydrolytic" mechanisms that allow these fungi to attack lignocellulose, individual protein characterization is lagging behind due to the lack of a robust method for rapid synthesis of crucial fungal enzymes. This work delves into the studies of biochemical functions of brown rot enzymes using a rapid, cell-free expression platform, which allowed the successful depictions of enzymes' catalytic features, their interactions with Fenton chemistry, and their roles played during the incipient stage of brown rot when fungus sets off the reactive oxygen species for oxidative degradation. We expect this research could illuminate cell-free protein expression system's use to fulfill the increasing need for functional studies of fungal enzymes, advancing the discoveries of novel biomass-converting catalysts.

Fast T1 mapping MRI in preclinical and clinical settings using subspace-constrained joint-domain reconstructions

This work aims to develop fast T1 mapping methods for preclinical and clinical scanners based on subspace-constrained reconstructions. Two sequences are explored for rapid T1 characterizations: 1) Interleaved spatiotemporal encoding incorporating variable repetition times. 2) Inversion recovery gradient echo with random sampling of the phase-encoding (PE) dimension. For both sequences, the subspace reconstruction of the signal recovery was applied, to jointly reconstruct the down-sampled images while characterizing the T1 relaxation. In vivo scans on human brains and abdomens confirmed the efficiency of the proposed methods, including compatibility with breath-holding. In addition, Scans on animals with abdominal tumors and dynamic contrast-enhanced T1 mapping on kidneys support the applicability of the proposed methods also in preclinical settings.

The clinical value of optical genome mapping in the rapid characterization of RB1 duplication and 15q23q24.2 triplication, for more appropriate prenatal genetic counselling.

Despite recent advances in prenatal genetic diagnosis, medical geneticists still face considerable difficulty in interpreting the clinical outcome of copy-number-variant duplications and defining the mechanisms underlying the formation of certain chromosomal rearrangements. Optical genome mapping (OGM) is an emerging cytogenomic tool with proved ability to identify the full spectrum of cytogenetic aberrations. Here, we report on the use of OGM in a prenatal diagnosis setting. Detailed breakpoint mapping was used to determine the relative orientations of triplicated and duplicated segments in two unrelated foetuses harbouring chromosomal aberrations: a de novo 15q23q24.2 triplication and a paternally inherited 13q14.2 duplication that overlapped partially with the RB1 gene. OGM enabled us to suggest a plausible mechanism for the triplication and confirmed that the RB1 duplication was direct oriented and in tandem. This enabled us to predict the pathogenic consequences, refine the prognosis and adapt the follow-up and familial screening appropriately. Along with an increase in diagnostic rates, OGM can rapidly highlight genotype-phenotype correlations, improve genetic counselling and significantly influence prenatal management.