PARAFAC Analysis Research Articles

The complexation between transition metals and water-soluble organic compounds (WSOC) and its effect on reactive oxygen species (ROS) formation

Both Transition Metals (TMs) and Water–Soluble Organic Compounds (WSOC) in atmospheric particles can make a certain contribution to Reactive Oxygen Species (ROS), but the complexation between them and its subsequent effects on ROS formation are still unclear. Three typical TMs (Fe(II), Cu(II), Mn(II)) and two types of WSOCs (SRHA (Suwannee River Humic Acid) and SRFA (Suwannee River Fulvic Acid)) were chosen to study their complexation process and its effects on generation of ROS. The excitation-emission matrix (EEM) was used to obtain the three-dimensional fluorescence spectra of WSOC during complexation process, and the fluorescence regional integration method (FRI) and parallel factor analysis (PARAFAC) were used to quantitatively characterize the changes of different compositions of WSOC during complexation process. The results showed that the complexation between WSOC and Cu or Mn exhibit synergistic effects on ROS generation, while WSOC and Fe has a negative effect even though ROS produced by Fe is the highest among the three TMs. The hydrophobic fraction of WSOC and ROS generation rate decreased during the complexation process, despite ROS concentration increase. PARAFAC analysis results showed that the aromaticity of WSOC is greatly reduced by complexing with Cu, followed by Fe, and the least with Mn. Cu–WSOC exhibited the most significantly synergistic effect on ROS generation, suggesting aromatic and polar substituents (such as phenol and quinone groups) in WSOC dominated the complexation process. All of three TMs tend to form stable complexes with the polar groups in WSOC. Cu might be more capable of combining with the benzene ring by π-π electron transfer than Fe and Mn. The aromatic groups (π-π electron transfer) in WSOC could significantly enhance ROS generation, but polar groups not.

Peptidoglycan as major binding motif for Uranium bioassociation on Magnetospirillum magneticum AMB-1 in contaminated waters

The U(VI) bioassociation on Magnetospirillum magneticum AMB-1 cells was investigated using a multidisciplinary approach combining wet chemistry, microscopy, and spectroscopy methods to provide deeper insight into the interaction of U(VI) with bioligands of Gram-negative bacteria for a better molecular understanding. Our findings suggest that the cell wall plays a prominent role in the bioassociation of U(VI). In time-dependent bioassociation studies, up to 95 % of the initial U(VI) was removed from the suspension and probably bound on the cell wall within the first hours due to the high removal capacity of predominantly alive Magnetospirillum magneticum AMB-1 cells. PARAFAC analysis of TRLFS data highlights that peptidoglycan is the most important ligand involved, showing a stable immobilization of U(VI) over a wide pH range with the formation of three characteristic species. In addition, in-situ ATR FT-IR reveals the predominant strong binding to carboxylic functionalities. At higher pH polynuclear species seem to play an important role. This comprehensive molecular study may initiate in future new remediation strategies on effective immobilization of U(VI). In combination with the magnetic properties of the bacteria, a simple technical water purification process could be realized not only for U(VI), but probably also for other heavy metals.

A 3D Fluorescence Classification and Component Prediction Method Based on VGG Convolutional Neural Network and PARAFAC Analysis Method

Three-dimensional fluorescence is currently studied by methods such as parallel factor analysis (PARAFAC), fluorescence regional integration (FRI), and principal component analysis (PCA). There are also many studies combining convolutional neural networks at present, but there is no one method recognized as the most effective among the methods combining convolutional neural networks and 3D fluorescence analysis. Based on this, we took some samples from the actual environment for measuring 3D fluorescence data and obtained a batch of public datasets from the internet species. Firstly, we preprocessed the data (including two steps of PARAFAC analysis and CNN dataset generation), and then we proposed a 3D fluorescence classification method and a components fitting method based on VGG16 and VGG11 convolutional neural networks. The VGG16 network is used for the classification of 3D fluorescence data with a training accuracy of 99.6% (as same as the PCA + SVM method (99.6%)). Among the component maps fitting networks, we comprehensively compared the improved LeNet network, the improved AlexNet network, and the improved VGG11 network, and finally selected the improved VGG11 network as the component maps fitting network. In the improved VGG11 network training, we used the MSE loss function and cosine similarity to judge the merit of the model, and the MSE loss of the network training reached 4.6 × 10−4 (characterizing the variability of the training results and the actual results), and we used the cosine similarity as the accuracy criterion, and the cosine similarity of the training results reached 0.99 (comparison of the training results and the actual results). The network performance is excellent. The experiments demonstrate that the convolutional neural network has a great application in 3D fluorescence analysis.

Determination of the number of components in the PARAFAC model with a nonnegative tensor structure: a simulated EEG data study

Parallel factor analysis (PARAFAC) is a powerful tool for detecting latent components in human electroencephalogram (EEG) in the time-space-frequency domain. As an essential parameter, the number of latent components should be set in advance. However, any component number selection method already proposed in the literature became a rule of thumb. Existing studies have demonstrated the methods’ performance on artificial data with a simplified structure, often not mimicking a real data character. On the other hand, the ground-truth latent structure is not always known for real-world data. With the objective to provide a comprehensive overview of component number selection methods and discuss their applicability to EEG, our study focuses on nontrivial and nonnegative simulated data structures resembling real EEG properties as closely as possible. This is achieved through an accurate head model and well-controlled cortical activation sources. By considering different noise levels and disruptions from the optimal structure, the performance of the twelve component number selection methods is closely inspected. Moreover, we validate a new approach for component number selection, which we recently proposed and applied to EEG tasks. We found that methods based on the eigenvalue analysis, variance explained, or presence of redundant components are inappropriate for component number selection in EEG tensor decomposition. On the other hand, three existing methods and the newly proposed approach produced promising results on nontrivial simulated EEG data. Nevertheless, component number selection for PARAFAC analysis of EEG is a complex yet unresolved problem, and new approaches are needed.

Identification of visible colored dissolved organic matter in biological and tertiary municipal effluents using multiple approaches including PARAFAC analysis

This study provided insights into the persistent yellowish color in biological and tertiary effluents of municipal wastewater through a multi-characterization approach and fluorescence excitation-emission matrix-parallel factor (EEM-PARAFAC) analysis. The characterization was performed on three to five full-scale municipal wastewater treatment plants (WWTPs), including differential log-transformed absorbance (DLnA) spectroscopy, resin fractionation, size-exclusion chromatography for apparent molecular weight analysis (SEC-AMW), and X-ray photoelectron spectroscopy (XPS) analysis. Hydrophobic acids (HPOA) were abundant in visible colored dissolved organic matter (DOM). The SEC-AMW result showed that the molecular weight of the colored substances in the secondary effluents is mainly distributed in the range of 2–3 kDa. Through XPS analysis, C-O/C-N and pyrrolic/pyridonic (N-5) were found to be positively correlated with chroma. PARAFAC component models were built on biological (two components) and tertiary effluent (three components) and the correlation analysis revealed that PARAFAC component 2 in biological effluent (BE-C2) and component 1 in tertiary effluent (TE-C1), which were ascribed to Hydrophobic acids and Humic acid-like, were the responsible visible colored DOM components cause yellowish color. In addition, component similarity testing found that the identified visible colored DOM PARAFAC BE-C2, and PARAFAC TE-C1 were identical (0.96) in physicochemical properties, with 4% removal efficacy on average, compared with 11% for invisible colored DOM. This implied that tertiary effluents containing colorants (TE-C1) were resistant to degradation/removal using different disinfection and filtration processes in advanced treatments. This sheds light on many physicochemical aspects of PARAFAC-identified visible colored DOM components and provides spectral data to build an online monitoring system.

Characterization of colored dissolved organic matter along the western continental shelf of India during the seasonal hypoxia

In recent years the number of hypoxic zones in the world is rising, which has been attributed to the increase in nutrients and organic matter due to anthropogenic activities. Here we present results on the variations in absorption and fluorescent characteristics of colored dissolved organic matter (CDOM) along the western continental shelf of India (WCSI) during the southwest monsoon (SWM). WCSI hosts the world's largest, natural, seasonal hypoxic zone covering 180,000 km2. Water samples were collected along 4 transects off Kochi, Mangalore, Karwar, and Goa during SWM (June–July 2018) for CDOM and other hydrographic parameters. Also, the Goa transect was sampled during late SWM (September–November 2016 and September 2018) when the bottom waters experienced low oxygen conditions. The onset of upwelling was observed in the hydrographical parameters with low temperature and dissolved oxygen (DO) in the sub-surface waters along the Kochi transect. DO decreased with depth and was hypoxic to suboxic in the bottom waters at most of the stations. The Highest CDOM absorption was observed at the nearshore stations of the Goa transect during July 2018. The waters along the Goa transect were highly stratified during the late SWM (September 2018) with low saline waters at the surface (due to heavy rainfall), with the development of hypoxia in the bottom waters. High CDOM absorption (ag412 m-1) was observed in the bottom waters, which coincided with hypoxic/suboxic conditions. Spectral slope S250-600 also showed a significant difference between the oxygen rich and low oxygenated waters. Three fluorescent DOM components were identified from PARAFAC analysis. Component 1 (C1) and 2 (C2) were humic-like with emissions in the longer wavelength, while component 3 (C3) was protein-like with excitation and emission in the UV region. CDOM absorption (ag412) and humic-like fluorescent component (C1) showed a positive correlation with apparent oxygen utilization (AOU), indicating the role of microbial respiration for CDOM production. Laboratory experiments also shed light on the CDOM production in low oxygenated waters when sufficient organic matter is available. This study gives insight into understanding dissolved organic matter's cycling under varying oxygen conditions prevailing in these waters.

Solid-liquid separation of real cellulose- containing wastewaters by extracellular polymeric substances: Mechanism and cost evaluation

• Crude EPS promotes the floc formation of the cellulose-containing wastewaters. • Hemiacetal and glucoside groups of EPS play a role in the interaction with cellulose. • A profit of $43.51 t −1 could be produced in the flocculation of LPW by crude EPS. • Liquid crude EPS retained 95% of flocculation ability after half a year of storage. The flocculation feasibilities of tobacco wastewater (TBW) and livestock and poultry wastewater (LPW) by the extracellular polymeric substances (EPS) of Bacillus sp. were evaluated in this study. The average particle sizes of flocs formed by the crude EPS were 45.83 mm and 41.67 mm in TBW and LPW, respectively, which were larger than that formed by chemical flocculants. The removal efficiencies of chemical oxygen demand, ammonia nitrogen and suspended solid achieved by crude EPS were increased more than 50% than that by chemical flocculants. Charge neutralization was dominant in the flocculation of LPW, while chemical reactions between the Fe(III) and reductive substances in TBW played an important role in the flocculation of TBW. The FTIR and XPS results indicated that the sugar derivatives of EPS, especially the hemiacetal and glucoside groups interacted with cellulose molecules. Three-dimensional EEM fluorescence spectra presented three peaks of tryptophan protein, aromatic polysaccharides and polysaccharides, and the peak intensities were enhanced with the addition of cellulose by PARAFAC analysis. Cost evaluation suggested that the generated flocs and supernatants could be further utilized as fertilizer after the solid–liquid separation of LPW, thus one ton of LPW after flocculation by crude EPS might generate a gross profit of $43.51, suggesting that advantages of crude EPS not only on environmental protection but also on flocculation cost. The results of present study implied that the crude EPS of Bacillus sp. have stronger competitiveness in the treatment of cellulose-containing wastewaters comparing to the chemical flocculants, which sheds lights on its potential usage as an alternative bio-flocculant.

3D front face fluorescence spectroscopy as a tool for monitoring the oxidation level of edible vegetable oil during storage at 60 °C

Fluorescence landscapes with excitation wavelengths varying between 280 and 400 nm, and emission wavelengths in the range of 300–650 nm were scanned directly on oil samples throughout storage in capped and uncapped flasks for 15 days at 60 °C. PARAFAC analysis of the fluorescence landscapes showed the presence of three fluorophores in the edible oils, which are strongly dependent on the storage conditions. The fluorescence spectra were resolved into excitation and emission profiles of the pure fluorescent compounds, which are ascribed to be oxidation products and vitamin E. The complexity of edible oil data sets was suitable for PARAFAC modelling. Problems with scattering were encountered, the use of missing values was tackled before obtaining a validated model with a criterion of similarity measurements of splits reaching the 83.8% and this allowed us to start getting through the model of interpretation.

New insights on aging mechanism of microplastics using PARAFAC analysis: Impact on 4-nitrophenol removal via Statistical Physics Interpretation

The aging effects of Polyethylene terephthalate (PET) microplastics were studied under Fenton process and Seawater. This research work mainly focuses on the aging mechanism of PET microplastics under two different conditions and their effect of aging on the adsorption of organic contaminants. The results of optical microscopic images, Scanning Electron Microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Raman Spectroscopy, carbonyl, carboxyl index, X-ray powder diffraction (XRD) and dissolved organic carbon (DOC) help to understand the aging mechanism of PET microplastics. Parallel factor analysis (PARAFAC) and two-dimensional correlation spectroscopy (2D-COS) were performed using 3D Excitation-Emission Matrix (3D-EEM) to understand the possible dissolved organic matter released during the Fenton process and seawater. The release of protein/phenol like components was observed in seawater whereas humic acid-like component was noted in the Fenton process. Later, the aged PET microplastics were tested for their adsorption capacity towards 4-nitrophenol at three different temperatures (15, 30 and 45 °C). The adsorption capacity of aged microplastics was found to be higher than the normal PET microplastics for all three different temperatures. Hydrogen bonding, n-pi interaction performed a significant role than pi-pi and hydrophobic interaction in the adsorption mechanism. A double layer with double energy model was found to be the best fit in the adsorption processes. The calculated adsorption energies (ΔE1, ΔE2) from the statistical physics modeling also confirms the physisorption mechanism. The above experimental results help to understand the behavior of microplastics at different aging period and how it acts as a carrier for pollutant in the marine environment.

Characterisation of Organic Matter and Its Transformation Processes in On-Site Wastewater Effluent Percolating through Soil Using Fluorescence Spectroscopic Methods and Parallel Factor Analysis (PARAFAC)

This research has used fluorescence spectroscopy and parallel factor analysis (PARAFAC) in order to characterize dissolved organic matter in septic tank effluent, as it passes through the biomat/biozone, infiltrating into the unsaturated zone beneath domestic wastewater treatment systems (DWWTSs). Septic tank effluent and soil moisture samples from the percolation areas of two DWWTSs have been analyzed using fluorescence excitation–emission spectroscopy. Using PARAFAC analysis, a six-component model was obtained whereby individual model components could be assigned to humified organic matter, fluorescent whitening compounds (FWCs), and protein-like compounds. This has shown that fluorescent dissolved organic matter (FDOM) in domestic wastewater was dominated by protein-like compounds and FWCs and that, with treatment in the percolation area, protein-like compounds and FWCs are removed and contributions from terrestrially derived (soil) organic decomposition compounds increase, leading to a higher degree of humification and aromaticity. The results also suggest that the biomat is the most important element determining FDOM removal and consequently affecting DOM composition. Furthermore, no significant difference was found in the FDOM composition of samples from the percolation area irrespective of whether they received primary or secondary effluent. Overall, the tested fluorometric methods were shown to provide information about structural and functional properties of organic matter which can be useful for further studies concerning bacterial and/or virus transport from DWWTSs.

Physicochemical properties of the dissolved organic carbon can lead to different physiological responses of zebrafish (Danio rerio) under neutral and acidic conditions.

Previous studies have suggested that the capacity of natural dissolved organic carbon (DOC) molecules to interact with biological membranes is associated with their aromaticity (SAC340 ); origin (allochthonous versus autochthonous, FI); molecular weight (Abs254/365 ); and relative fluorescence of DOC moieties (PARAFAC analysis). These interactions may be especially important when fish are challenged by acidic waters, which are known to inhibit the active uptake of Na+ and Cl- , while stimulating diffusive ion losses in freshwater fishes. Therefore, zebrafish were acclimated (7 days, pH 7.0) to five natural DOC sources (10 mg C/L), two from the Amazon Basin and three from Canada, together with a "no-added DOC" control. After the acclimation, fish were challenged by exposure to acidic water (pH 4.0) for 3 h. Osmoregulatory parameters were measured at pH 7.0 and 4.0. Acclimation to the five DOC sources did not disturb Na+ , Cl- and ammonia net fluxes, but resulted in differential elevations in Na+ , K+ ATPase and v-type H+ ATPase activities in fish at pH 7.0. However, after transfer to pH.4.0, the control fish exhibited rapid increases in both enzymes. In contrast the DOC- acclimated animals exhibited unchanged (Na+ , K+ ATPase) or differentially increased (v-type H+ ATPase) activities. Na+ , Cl- and ammonia net fluxes remained unchanged in the control fish, but were differentially elevated in most of the DOC treatments at pH 4.0, relative to the same DOC treatments at pH 7.0. Correlations between the osmoregulatory data the DOCs properties highlight that the DOC properties drive different effects on gill physiology.

Pathways and composition of dissolved organic carbon in a small agricultural catchment during base flow conditions

The amount and composition of organic carbon are major controls on water quality and ecological processes in streams. In this study we explored the fate of the quantity of dissolved organic carbon (DOC) and the composition of dissolved organic matter (DOM) in an agricultural hillslope - stream network system. We conducted our study in the 66 ha HOAL (Hydrological Open Air Laboratory) in Lower Austria. We measured DOC of the soil eluates from different land use units, water samples from the stream and from seven tributaries, and estimated DOM components by fluorescent spectrophotometry and PARAFAC analyses. Soil DOC shows the highest concentrations in summer, but DOC concentrations in the tributaries are lower in summer than in winter by between 19% and 31%. DOM composition of the soil eluate differs between land use units. The forest site exhibits the largest fractions of humic-like fluorophores and less labile DOM. DOM composition in the tributaries is, in addition to DOC, controlled by soil moisture. We estimated the DOC import from the tributaries into the stream as 125 kg during base flow conditions in the period February to December 2017 and the instream DOC production as 38 kg, considering mass balance and exchange with groundwater. Six out of seven DOM components have a positive net production along the stream, only aliphatic DOM with low molecular weight is consumed (65 % of its input). These findings suggest that agricultural land use increases DOC input into streams and alters their DOM quality. Instream processes modify DOM quality over short distances.

Parallel factor analysis of fluorescence excitation emissions to identify seasonal and watershed differences in trihalomethane precursors

Concentration and chemical composition of dissolved organic matter (DOM) play a major role in formation and speciation of disinfection by-products, such as trihalomethanes (THMs), in water treatment plants (WTPs) during disinfection. This study characterized DOM across the process trains of WTPs using fluorescence excitation emission matrices (EEMs) together with parallel factor analysis (PARAFAC). The PARAFAC model was developed from 216 EEMs of bimonthly water samples from three WTPs in Khon Kaen, Thailand, from May 2018 to Mar 2019. Three PARAFAC components identified were humic-like DOM of terrestrial, and microbial or agricultural origin, while the one protein-like component was previously defined as tryptophan-like fluorophore. The relationships between water quality parameters, including the maximum fluorescent intensities (Fmax) of PARAFAC components and THM formation potential (THM-FP) were investigated using Spearman's rank correlation. The Fmax of PARAFAC components, UVA254, DOC, and THM-FP were greater in dry season. Chloroform was the primary THM formed at two sites using surface water as their water source, while the site using surface water with saline groundwater intrusion had higher concentration of brominated THMs. Results indicated that Fmax of humic-like components extracted by PARAFAC analysis were the most accurate THM-FP surrogate parameter assessed for the water samples tested and the correlations between Fmax and THM-FP were site specific (ρ = 0.81–0.85). The result demonstrates that fluorescence spectroscopy analysis has yielded insights into relationships between the DOM optical characteristics and their total THM-FP even at sites with different speciation of THMs.

The impact of combining data sets of fluorescence excitation - emission matrices of dissolved organic matter from various aquatic sources on the information retrieved by PARAFAC modeling

Despite that fluorescence spectroscopy coupled with Parallel Factor Analysis (PARAFAC) has been widely used in the investigation of Fluorescent Dissolved Organic Matter (FDOM) in aquatic systems, the proper performance of PARAFAC analysis on datasets originating from various sources is not to be taken for granted. In this study, we examine the impact of the co-analysis of datasets from various natural water systems located in the same geographical region in the Eastern Mediterranean Sea. For this purpose three datasets were formed representative of open sea waters (SW), rivers and streams (RV) and lagoons (LG). The Excitation Emission Matrices (EEMs) derived from fluorescence analysis were subjected to individual PARAFAC analysis per dataset as well as combined analyses i.e.: SWRV, SWLG, RVLG, ALL (SW-RV-LG). We evaluated the reliability of the components that were validated in the combined models through the investigation of model’s residuals and components correlation. We also assessed the similarity of the common identified components among models in regards of: (a) spectral position, by calculating the Tucker congruence coefficient (TCC) of the excitation and emission loadings of the PARAFAC components, and (b) fluorescence intensity, through regression analysis of Fmax, among models. Our analysis showed that for natural waters of various sources within the same geographical region, combined PARAFAC modeling can have both negative as well as positive impact. In the case of the combined SWLG and RVLG models, the PARAFAC analysis was able to resolve the fulvic component that was initially observed only in the LG dataset and thus a new component for SW and RV datasets was resolved. The fulvic-like component was actually identified for the first time in the open sea using the combined datasets. Moreover in the combined SWRV analysis tyrosine-like component was resolved which was found initially only in the RV dataset. Contrary, tyrosine-like component was lost in the combined RVLG dataset. We also show that the resolution of extra components in a combined analysis is not always a good fit for the dataset and the model should be assessed in terms of residuals prior acceptance. Finally, our study proposes that the similarity of the common components between combined and individual models is largely dependent on the similarity between the components of the individual models and that the estimation of the Fmax of a component is probably less affected by data diversity compared to the estimation of its spectral position.

Insight into binding characteristics of copper(II) with water-soluble organic matter emitted from biomass burning at various pH values using EEM–PARAFAC and two-dimensional correlation spectroscopy analysis

The metal-binding characteristics of water-soluble organic matter (WSOM) emitted from biomass burning (BB, i.e., rice straw (RS) and corn straw (CS)) with Cu(II) under various pH conditions (i.e., 3, 4.5, and 6) were comprehensively investigated. Two-dimensional correlation spectroscopy (2D-COS) and excitation–emission matrix (EEM) –PARAFAC analysis were applied to investigate the binding affinity and mechanism of BB WSOM. The results showed that pH was a sensitive factor affecting binding affinities of WSOM, and BB WSOMs were more susceptible to bind with Cu(II) at pH 6.0 than pH 4.5, followed by pH 3.0. Therefore, the Cu(II)-binding behaviors of BB WSOMs at pH 6.0 were then investigated in this study. The 2D-absorption-COS revealed that the preferential binding with Cu(II) was in the order short and long wavelengths (237–239 nm and 307–309 nm) > moderate wavelength (267–269 nm). The 2D-synchronous fluorescence-COS results suggested that protein-like substances generally exhibited a higher susceptibility and preferential interaction with Cu(II) than fulvic-like substances. EEM–PARAFAC analysis demonstrated that protein-like (C1) substances had a greater complexation ability than fulvic-like (C2) and humic-like (C3) substances for both BB WSOM. This indicated that protein-like substances within WSOM played dominant roles in the interaction with Cu(II). As a comparison, RS WSOM generally showed stronger complexation capacity than CS WSOM although they exhibited similar chemical properties and compositions. This suggested the occurrence of heterogeneous active metal-binding sites even within similar chromophores for different WSOM. The results enhanced our understanding of binding behaviors of BB WSOM with Cu(II) in relevant atmospheric environments.

Applying EEM- PARAFAC Analysis With Quantitative Real-Time PCR to Monitor Methanogenic Activity of High-Solid Anaerobic Digestion of Rice Straw.

The methanogenic activity is an important indicator to assess the efficiency of high-solid anaerobic digestion. However, it is not yet elucidated clearly how to detect the parameter rapidly and reliably in the rice straw feeding reactor. Co-inoculated with ruminal digesta and anaerobic sludge, the digestion performance was studied at three different organic loading rates (OLRs). The excitation emission matrix–parallel factor analysis (EEM–PARAFAC) was used to detect dynamic changes in the characteristic of fluorescence components. Our results revealed that CH4 productivity reached 280.90 mL/g volatile solid (VS) with a 54.39% CH4 content under the OLR of 2.26 g/(L⋅d), which amount to 80.29% of its theoretical value. At the OLR of 2.47 g/(L⋅d), the average accumulated NH4+ concentration was 1082.63 mg/L, which resulted in the hydrogenotrophic Methanobacteriales decreasing from 1.70 × 109 to 1.04 × 106 copies/g in the solid residues, whereas the acetotrophic Methanosarcinales increased from 7.89 × 106 to 9.44 × 106 copies/g. The dynamics of the methanogenic community consequently influenced the bioconversion efficiency of rice straw, and CH4 productivity was reduced to 256.54 mL/g VS. The three fluorescent components, at the excitation/emission wavelength of 420 nm/470 nm, 340 nm/430 nm, and 280 nm/340 nm, were decomposed by PARAFAC model in the digestate. Fluorescence intensities of coenzyme F420 and NADH reflected the dynamic changes of CH4-producing activity and anaerobic digestion efficiency, respectively. The coenzyme F420, unique to hydrogenotrophic methanogens, was correlated with methane yield, suggesting they played a dominant role in the anaerobic reactor. This study demonstrates that the EEM–PARAFAC combined with Q-PCR can be used to characterize methanogenic activity variation during the high-solid anaerobic digestion of rice straw with 15% total solid (TS).

Variations of disinfection byproduct precursors through conventional drinking water treatment processes and a real-time monitoring method

In this investigation, raw water (RW), settled water (SW), and filtered water (FW) collected from a drinking water treatment plant were fractionated into 24 natural organic matter (NOM) fractions with varying molecular weights and hydrophobicity. The yields of disinfection byproducts (DBPs) obtained during the chlorination of the NOM fractions were explored. Results revealed that the 0–1 kDa, 5–10 kDa, and hydrophobic DBP precursors dominated RW. Hydrophobic fractions cannot be effectively removed, which contributed to the high DBP precursors remaining in the FW. The optional optical parameters, including UVA (UV340, UV360, and UV380), UVB (UV280, UV300, and UV310), and UVC (UV254, UV260, and UV272), were analyzed to determine the DBP yields during chlorination of different NOM fractions. Results revealed that UVC could be applied to indicate the regulated DBP yields of the humified precursors. Contrary to the generally accepted view, for biologically derived precursors, their regulated DBPs and dichloroacetonitrile correlated better with UVA (e.g. UV340). Moreover, PARAFAC analysis was applied to decompose an array of 24 EEM spectra. Good linear correlations were found between the PARAFAC components and most DBP yields. Furthermore, four fluorescence parameters were proposed via a modified fluorescence picking method, which can serve as excellent surrogates of PARAFAC components. These fluorescence parameters were found to be effective in indicating most DBP yields. Finally, the fluorescence intensity at excitation wavelength/emission wavelength = 310/416 nm was found to be a promising built-in parameter for the real-time monitoring of DBP precursors, regardless of the humification degree of the precursors.

Contrasting responses of DOM leachates to photodegradation observed in plant species collected along an estuarine salinity gradient

A series of abiotic processes affected by salinity changes involve light-mediated reactions and different degradation pathways of organic compounds, including altered photo-oxidation, photo-degradation, and photolysis of organic matter (OM). Sunlight is known to degrade, oxidize, or mineralize dissolved organic matter (DOM) in waterways, creating large changes in compositional structure of DOM near the water surface and ultimately in the mixed layer. DOM derived from various vegetation types has differing levels of susceptibility to photolytic degradation depending on initial chemical composition and in what matrix degradation takes place (e.g., salinity). The effect of sunlight and salinity on degradation of leached DOM derived from three dominant vegetative species, Avicennia germinans, Juncus romerianus, and Taxodium distichum, along a riverine continuum in northeast Florida was determined. Leachates from these three sources in a deionized or seawater matrix were irradiated in a continuous flow-through photolytic system over the course of 20 h. Avicennia germinans and Juncus roemerinaus DOM readily degraded as indicated by decreases in absorbance across all wavelengths during the irradiation period, while Taxodium distichum DOM was found to increase in absorbance across all wavelengths in the freshwater matrix, but not in seawater. PARAFAC analysis indicated differences in photochemical components and % change of absorbance and fluorescence over time indicate the importance and variability of individual contributions to the DOM pool across an estuarine continuum. This work characterizes the photochemical properties of three individual DOM sources, exhibits the need for further research on this topic, and explores the salinity effect on photo-degradation of DOM from unique plant-derived DOM.

A pilot study on parallel factor analysis as a diagnostic tool for oral cancer diagnosis: A statistical modeling approach

AbstractExcitation‐emission matrix (EEM) has been extensively used as the comprehensive diagnostic tool to extract the biochemical fingerprint of the intrinsic fluorophores in a single scan window. However, there is a gap between the rigorous applications of the statistical tool with respect to discrimination of different stages of the disease which has been the subject for many years. Parallel factor analysis (PARAFAC) is one among the powerful statistical modeling approaches among others. In the present study, a total of 70 EEM matrices of normal, premalignant, and malignant oral tissues were given as a input, and seven intrinsic fluorophores were extracted as “components.” The extracted components were well correlated with respect to the appropriate excitation and emission spectral characteristics of the multiple intrinsic fluorophores such as tryptophan, flavin adenine dinucleotide (FAD), nicotinamide adenine dinucleotide (NADH), collagen‐1, porphyrin, tyrosine, and collagen. Subsequently, the student's t test and linear discriminant analysis (LDA) have been carried out with respect to the fluorescence intensity scores between normal vs. premalignant, normal vs. cancer, and premalignant vs. malignant groups. In normal vs. premalignant, all the seven fluorophores exhibit good statistical accuracy except porphyrin; normal vs. cancer exhibits higher statistical significance for tryptophan, NADH, and FAD than rest of the fluorophores, and premalignant vs. malignant shows proper classification in discriminating FAD, collagen‐1, and collagen. In summary, based on positive predictive value, the normal vs. premalignant exhibits 100% classification than the other two groups. Hence, the PARAFAC analysis could be the alternative and useful diagnostic tool in oral cancer diagnosis.

Refractory Humic-like Substances: Tracking Environmental Impacts of Anthropogenic Groundwater Recharge.

To unravel the crucial components of natural organic matter that respond to the process of anthropogenic groundwater recharge (AGR) from different recharge water sources, dissolved organic matter (DOM) and base-extractable particulate organic matter (POM) in groundwater and surface water were analyzed using excitation-emission matrix spectroscopy coupled with parallel factor analysis (EEM-PARAFAC). The EEM and traditional spectral indices of samples show that the fluorescent intensity, molecular weight, and humification degree of the DOM were relatively higher than those of the POM, and the groundwater in the reclaimed water recharge area (RWRA) was more contaminated than in the south-to-north water recharge area (SNWRA). PARAFAC analysis indicates that the DOM was dominated by an allochthonous humic-like substance (C1), whereas the POM was dominated by tryptophan-like substances associated with microbial activity (C2). Partitioning of PARAFAC components between DOM and POM showed that the humic-like substances (C1 and C4) were more likely to be distributed into a dissolved phase compared to the protein-like substances (C2 and C3), which suggested the potential use of C1 and C4 as a tracking indicator. In particular, the clear gradient distributions along both the hydrogeological profile and different aquifer systems in terms of the concentration and composition of C1 also discriminated between the RWRA and SNWRA with regard to the effects of various AGRs on the groundwater. The association between C1 and water-quality indicators revealed by principal component analysis further indicated that refractory humic-like substances would track the environmental impacts of intentional AGR processes.