Evaluation of Front-Face Fluorescence for Assessing Cyanobacteria Fouling in Ultrafiltration.

Cyanobacteria fouling in ultrafiltration (UF) drinking water treatment poses a significant threat to the stability and sustainability of the process. Both phycocyanin found in cyanobacteria and the polymer membrane exhibit strong fluorescence, which could be readily detected using front-face excitation-emission matrix (FF-EEM) spectroscopy. In this study, FF-EEM was employed for the nondestructive and in situ characterization of algae fouling evolution in UF, while also analyzing fouling mechanisms and reversibility. The results indicated that phycocyanin fluorescence on the membrane surface showed a linear correlation with the specific algal cell count on the membrane surface before reaching saturation. As fouling progressed, membrane fluorescence decreased, which was associated with the extent of the surface coverage on the membrane. The plateau in membrane fluorescence indicated full coverage, coinciding with the cake filtration mechanism, cake compression, and deterioration of fouling reversibility. These findings highlight the promise of FF-EEM as a valuable tool for monitoring and evaluating fouling of cyanobacteria in UF systems.

Pedestrian Safety in Frontal Tram Collision, Part 1: Historical Overview and Experimental-Data-Based Biomechanical Study of Head Clashing in Frontal and Side Impacts.

This article represents the first paper in a two-part series dealing with safety during tram-pedestrian collisions. This research is dedicated to the safety of trams for pedestrians during collisions and is motivated by the increased number of lethal cases. The first part of this paper includes an overview of tram face development from the earliest designs to the current ones in use and, at the same time, provides a synopsis and explanation of the technical context, including a link to current and forthcoming legislation. The historical design development can be characterised by three steps, from an almost vertical front face, to leaned and pointed shapes, to the current inclined low-edged windshield without a protruding coupler. However, since most major manufacturers now export their products worldwide and customisation is only of a technically insignificant nature, our conclusions are generalisable (supported by the example of Berlin). The most advantageous shape of the tram's front, minimising the effects on pedestrians in all collision phases, has evolved rather spontaneously and was unprompted, and it is now being built into the European Commission regulations. The goal of the second part of this paper is to conduct a series of tram-pedestrian collisions with a focus on the frontal and side impacts using a crash test dummy (anthropomorphic test device-ATD). Four tram types approaching the collision at four different impact speeds (5 km/h, 10 km/h, 15 km/h, and 20 km/h) were used. The primary outcome variable was the resultant head acceleration. The risk and severity of possible head injuries were assessed using the head injury criterion (HIC15) and its linkage to the injury level on the Abbreviated Injury Scale (AIS). The results showed increasing head impacts with an increasing speed for all tram types and collision scenarios. Higher values of head acceleration were reached during the frontal impact (17-124 g) compared to the side one (2-84 g). The HIC15 values did not exceed the value of 300 for any experimental setting, and the probability of AIS4+ injuries did not exceed 10%. The outcomes of tram-pedestrian collisions can be influenced by the ATD's position and orientation, the impact speed and front-end design of trams, and the site of initial contact.

Pedestrian Safety in Frontal Tram Collision, Part 2: Laminated Glass as a Crucial Part of the Absorption and Deformation Zone-Its Impact Test and Analysis.

As was shown in the previous part of the study, windshields are an important part of the passive safety means of modern low-floor trams with an extraordinary effect on pedestrian safety in a pedestrian-tram collisions. Therefore, maximum attention must be paid to the definition of tram windshield characteristics. This article describes a windshield crash test, from which data are obtained to verify the feasibility of the applied computational approaches. A developed analytical model is utilised for a simple description of the energy balance during collision with an illustrative definition of the important parameters of laminated glass as well as their clear physical interpretations. The finite element analysis (FEA) performed in Ansys software using two versions of material definition, namely a simpler (*MAT_ELASTIC with nonlocal failure criterion) and a more complex (*MAT_GLASS with brittle stress-state-dependent failure) material model, which are presented as suitable for obtaining a detailed description of the shattering process of laminated glass, which can also be used effectively in windshield engineering.

Does Variability Affect the Performance of Front-Face Fluorescence Spectroscopy? A Study Case on Commercial Lebanese Olive Oil.

The potential of front-face fluorescence spectroscopy coupled with chemometric techniques, namely multiple linear regression (MLR) applied on parallel factor (PARAFAC) scores and partial least squares (PLS), was tested on Lebanese olive oil samples possessing natural variability within their chemical parameters. Ninety-six olive oil samples have been harvested at different dates and from two seasons, processed using different extraction methods, collected from different altitudes and other factors that can increase the variability of the samples' chemical composition. Fluorescence excitation-emission matrices (EEM) of the collected samples were measured, and the relationship between them and the chemical parameters was examined. Twenty-two MLR regression models based on PARAFAC scores were generated, the majority of which showed a good correlation coefficient (R > 0.7 for ten predicted variables). A second model using PLS on the unfolded EEM was also conducted to improve the regression and to assess if it can handle the variability in hand. However, similar results, with a slight improvement over the MLR model, were obtained. In a non-experimental design, such variability may hinder the potentials of front-face fluorescence; however average to good MLR and PLS models were obtained, predicting the Lebanese olive oil deterioration quality parameters and fatty acid content.

Rapid Identification of Dendrobium officinale from Other Species Using 3D Front-Face Fluorescence Technique.

Dendrobium officinale is a rare and endangered perennial herb in China, which have been used in preparing Chinese tonic medicine for hundreds of years. The severe shortage of this herb and high price have caused that many similar plants were processed as an adulterant and it became difficult to distinguish genuine D. officinale by traditional authentication methods. A sensitive, convenient, and specific method for rapid identification of D. officinale is urgently needed. In the present study, 3D front-face fluorescence technique merged with Independent Component Analysis was used to get the "pure" independent fluorescence signals. The overall 3D-FFF spectra were decomposed into seven independent components (IC). To distinguish D. officinale from other species, IC1 and IC4 were chosen as fluorescence markers and the fluorescence intensity (FI) value at 340 nm/ 442 nm (excitation /emission wavelength) of IC1and 315 nm/ 468 nm of IC4 were used to build a linear model for identifying D. officinale successfully. Compared with other Dendrobium species, D. officinale showed much higher FI1 and FI4 value which is a direct criterion for identification. Meanwhile, even though the FI values of D. officinale may fluctuate due to the difference of growing conditions, the relation between FI1 and FI4 amazingly always fit the linear model constructed (FI4 = 9.9046 + 0.6119FI1, R2 = 0.9811). The linear model is an important finding and specific for D. officinale. Based on the FI value and the goodness of fit in the linear model, D. officinale can be identified quickly.

A 3D-Fluorescence Fingerprinting Approach to Detect Physiological Modifications Induced by Pesticide Poisoning in Apis mellifera: A Preliminary Study.

The combined use of 3D-fluorescence spectroscopy and independent component analysis using a differential fingerprinting approach has been applied with success to detect physiological effects of dimethoate in honeybees. Biochemical determinations combined with the identification of fluorescence zones that may correspond to proteins, NADH or neurotransmitters/neurohormones (octopamine, dopamine and serotonin) related to the physiological stress caused by the pesticide enabled phenomenological modeling of the physiological response in the honeybee using a simple and rapid method. The signals associated with the fluorophores involved in the response to stress were extracted from the fluorescence spectra using an unsupervised algorithm such as independent component analysis. The signals of different neurotransmitters were isolated on separated factorial components, thus facilitating their biochemical interpretation.

A simple light path modifying device to reduce scattering in front-face fluorescence spectra.

This technical note presents a device to diminish scattering signal in front-face fluorescence spectra while obtaining fluorescence signal. The beam path in a commercial fluorescence spectrometer was modified by two deflecting mirrors, leading reflections away from the sensor. This light path modifying (LPM) device was tested with two fluid and three solid substances, where the scattering-to-fluorescence ratio improved by a factor of 1.7 to 7.6. The spectra obtained with the LPM were much clearer, and distortion of the fluorescence peaks was avoided. Scans of quinine sulphate complied well with reference spectra.

Synchronous Front-Face Fluorescence Spectra: A Review of Milk Fluorophores.

Milk is subjected to different industrial processes, provoking significant physicochemical modifications that impact milk's functional properties. As a rapid and in-line method, front-face fluorescence can be used to characterize milk instead of conventional analytical tests. However, when applying fluorescence spectroscopy for any application, it is not always necessary to determine which compound is responsible for each fluorescent response. In complex matrixes such as milk where several variables are interdependent, the unique identification of compounds can be challenging. Thus, few efforts have been made on the chemical characterization of milk' fluorescent spectrum and the current information is dispersed. This review aims to organize research findings by dividing the milk spectra into areas and concatenating each area with at least one fluorophore. Designations are discussed by providing specific information on the fluorescent properties of each compound. In addition, a summary table of all fluorophores and references cited in this work by area is provided. This review provides a solid foundation for further research and could serve as a central reference.

Rapid, simultaneous and non-destructive determination of multiple adulterants in Panax notoginseng powder by front-face total synchronous fluorescence spectroscopy.

The authentication of traditional herbal medicines in powder form is of great significance, as they are always of high values but vulnerable to adulteration. Based on the distinct fluorescence of protein tryptophan, phenolic acids and flavonoids, front-face synchronous fluorescence spectroscopy (FFSFS) was applied for the fast and non-invasive authentication of Panax notoginseng powder (PP) adulterated with the powder of rhizoma curcumae (CP), maize flour (MF) and whole wheat flour (WF). For either single or multiple adulterants in the range of 5-40% w/w, prediction models were built based on the combination of unfolded total synchronous fluorescence spectra and partial least square (PLS) regression, and were validated by both five-fold cross-validation and external validation. The constructed PLS2 models simultaneously predicted the contents of multiple adulterants in PP and gave suitable results, with most of the determination coefficients of prediction (Rp2) >0.9, the root mean square error of prediction (RMSEP) no >4% and residual predictive deviation (RPD) >2. The limits of detections (LODs) were 12.0, 9.1 and 7.6% for CP, MF and WF, respectively. All the relative prediction errors for simulated blind samples were between -22% and + 23%. FFSFS offers a novel alternative to the authentication of powdered herbal plants.

Non-invasive analysis of natural textile dyes using fluorescence excitation-emission matrices.

Multidimensional fluorescence spectroscopy was assessed as a non-invasive and non-destructive method for the analysis of components in natural textile dyes. Results demonstrate that components in the natural dyes fluoresce and wool's intrinsic fluorescence is, in many cases, not a considerable analytical interferent. In the case of some self-dyed reference yarns, like those dyed with northern and lady's bedstraws, wood horsetail, safflower, salted shield lichen, dyer's madder and cochineal, the fluorescence excitation-emission matrices (EEMs) are sufficiently characteristic for using them as a primary means of identification (or assignment to a family of dyes). With most of the studied yellow and green dyes (heather, silver birch, some bloodred webcap treatments, alkanet), however, the spectra can be used as additional information for identification. This study reports multidimensional fluorescence data for a collection of wools dyed with natural dyes (31 dyed wool yarn samples that were self-dyed with 18 different natural dyes) that were used as references in a case study of two historical textiles for which liquid chromatography-mass spectrometry was used as a confirmatory technique. Given its utility as a rapid and non-destructive/non-invasive method with information-rich multidimensional EEM output, the front-face fluorescence spectroscopy of surfaces using a fiber optic probe is a promising technique for the analysis of dyes on cultural heritage textiles.

A practical application of front-face synchronous fluorescence spectroscopy to rapid, simultaneous and non-destructive determination of piperine and multiple adulterants in ground black and white pepper (Piper nigrum L.).

Based on the distinct fluorescence of piperine and tryptophan, and their different profiles in pepper and several possible adulterants, front-face synchronous fluorescence spectroscopy (FFSFS) was applied for the fast and non-invasive authentication of ground black pepper adulterated with papaya seed powder and buckwheat flour, and ground white pepper adulterated with whole wheat and maize flours. For either single adulterant or dual adulterants in the range of 10-40% w/w, prediction models were constructed based on the combination of unfolded total synchronous fluorescence spectra and partial least square (PLS) regression, and were validated by both five-fold cross-validation and external validation. The built PLS2 models produced suitable results, with most of the determination coefficients of prediction (Rp2) greater than 0.8, the root mean square error of prediction (RMSEP) < 5% and residual predictive deviation (RPD) greater than 2. The limits of detection (LODs) were 11.1, 5.5, 10.6 and 12.0% for papaya seed powder, buckwheat, whole wheat and maize flours, respectively. Most relative prediction errors for simulated blind samples were within ± 30%. Besides, piperine in ground black and white pepper was also determined with acceptable PLS results.

Anti-interference and non-destructive identification of textile fabrics using front-face excitation-emission matrix fluorescence spectroscopy combined with multi-way chemometrics.

The identification of trace textile fabrics discovered at crime scenes plays a crucial role in the case of forensic investigations. Additionally, in practical situations, fabrics may be contaminated, making identification more challenging. To address the aforementioned issue and promote the application of fabrics identification in forensic analysis, front-face excitation-emission matrix (FF-EEM) fluorescence spectra coupled with multi-way chemometric methods were proposed for the interference-free and non-destructive identification of textile fabrics. Common commercial dyes in the same color range under different materials (cotton, acrylic, and polyester) that cannot be visually distinguished were investigated, and several binary classification models for the identification of dye were established using partial least squares discriminant analysis (PLS-DA). The identification of dyed fabrics in the presence of fluorescent interference was also taken into consideration. In each kind of pattern recognition model mentioned above, the classification accuracy (ACC) of the prediction set was 100%. The alternating trilinear decomposition (ATLD) algorithm was executed to separate mathematically and remove the interference, and the classification model based on the reconstructed spectra attained an accuracy of 100%. These findings indicate that FF-EEM technology combined with multi-way chemometric methods has broad prospects for forensic trace textile fabric identification, especially in the presence of interference.

Front-face excitation-emission matrix fluorescence spectroscopy combined with interpretable deep learning for the rapid identification of the storage year of Ningxia wolfberry.

Ningxia wolfberry stored for many years may be disguised as fresh wolfberry by unscrupulous traders and sold for huge profits. In this work, the front-face excitation-emission matrix (FF-EEM) fluorescence spectroscopy coupled with interpretable deep learning was proposed to identify the storage year of Ningxia wolfberry in a lossless, fast and accurate way. Alternating trilinear decomposition (ATLD) algorithm was used to decompose the three-way data array obtained by Ningxia wolfberry samples, extracting the chemically meaningful information. Meanwhile, a convolutional neural network (CNN) model for the identification of the storage year of Ningxia wolfberry, called EEMnet, was proposed. The model successfully classified wolfberry samples from different storage years by extracting the subtle feature differences of the spectra, and the correct classification rate of the training set, test set and prediction set was more than 98%. In addition, a series of interpretability analyses were implemented to break the "black box" of the deep learning model. These results indicated that the method based on FF-EEM fluorescence spectroscopy combined with EEMnet could quickly and accurately identify the year of Ningxia wolfberry in a green way, providing a new idea for the identification of the storage years of Chinese medicinal materials.

A novel method for real-time prediction of the shelf life of pork at different storage temperatures using front-face fluorescence excitation-emission matrices.

This study presents a novel method for predicting the shelf life of pork in real-time based on front-face fluorescence excitation-emission matrices (EEMs). The total viable count (TVC) of bacteria was used as the indicator of microbial spoilage in the pork samples. Modified Gompertz and square root equations were used to establish models for the trends in microbial growth and for predicting the shelf life, the R2 values of the fitting equation at different temperatures were all greater than 0.95. The fluorescence intensity ratio of oxidation product to tryptophan (FOX/Trp) was highly correlated with the quality deterioration of pork and was therefore used to establish a quantitative model of TVC values by linear regression with Rc2 and Rp2 values of 0.914 and 0.906, respectively. The mean absolute errors between the remaining shelf life predicted by fluorescence EEMs and the measured values at three storage temperatures were less than 1 day.

Determination of Adulteration of Chicken Meat into Minced Beef Mixtures using Front Face Fluorescence Spectroscopy Coupled with Chemometric.

The objective of this study was to explore the potential of front face fluorescence spectroscopy (FFFS) as rapid, non-destructive and inclusive technique along with multi-variate analysis for predicting meat adulteration. For this purpose (FFFS) was used to discriminate pure minced beef meat and adulterated minced beef meat containing (1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%) of chicken meat as an adulterant in uncooked beef meat samples. Fixed excitation (290 nm, 322 nm, and 340 nm) and fixed emission (410 nm) wavelengths were used for performing analysis. Fluorescence spectra were acquired from pure and adulterated meat samples to differentiate pure and binary mixtures of meat samples. Principle component analysis, partial least square regression and hierarchical cluster analysis were used as chemometric tools to find out the information from spectral data. These chemometric tools predict adulteration in minced beef meat up to 10% chicken meat but are not good in distinguishing adulteration level from 1% to 5%. The results of this research provide baseline for future work for generating spectral libraries using larger datasets for on-line detection of meat authenticity by using fluorescence spectroscopy.

Japanese dace (Tribolodon hakonensis) fish freshness estimation using front-face fluorescence spectroscopy coupled with chemometric analysis.

Although fish and its related products are good sources of protein and unsaturated fatty acids, like omega-3 in the human diet, their shelf-life is limited by biochemical and microbial changes. In this study, a front-face fluorescence spectroscopy technique was used to acquire Excitation-emission matrices (EEM) to monitor Japanese dace (Tribolodon hakonensis) fish freshness degradation during storage. EEM of Japanese dace fish parts (intact eyeball and surface-containing scales), excitation from 220 to 585 nm and emissions from 250 to 600 nm, were measured at different times during storage. To simplify the acquired complex spectra datasets from each fish part, the variables were reduced to those that were only significant/important (those with higher positive or negative correlation) for K value prediction, and as an index of freshness. Partial least square regression (PLSR) results demonstrated that combining the fluorescence EEM of the eyeball and surface-containing scales the best monitoring of fish freshness; excitation at 280 and 350 nm for both the eyeball and surface-containing scales, with 2.84 and 0.96 as RMSE and R2, respectively. These findings demonstrate that multiple excitation fluorescence approaches can be convenient for the freshness evaluation of fish.

Use of front face fluorescence spectroscopy coupled with multivariate data analysis for monitoring biscuits' quality during aging.

In this study, the potentiality of front face fluorescence spectroscopy (FFFS) for the evaluation of the quality of biscuits manufactured with butylated hydroxytoluene and pomegranate peel extract during aging was investigated. By using the principal component analysis, vitamin A and tryptophan spectra allowed a clear discrimination between biscuit samples according to the nature of antioxidants, while fluorescent Maillard reaction products spectra showed clear differentiation between samples according to the storage time. Clear differentiation between biscuits according to the used antioxidants and storage time was achieved by using common components and specific weights analysis. Using partial least-squares regression, excellent prediction of water activity (R 2 = 0.95), and L* values (R 2 = 0.92), and approximate prediction of hardness (R 2 = 0.78), b* values (R 2 = 0.74), and moisture content (R 2 = 0.74) were shown. However, the FFFS failed to predict a* values, primary and secondary oxidation products (R 2 < 0.6).

Fluorescence quenching by competitive absorption between solid foods: Rapid and non-destructive determination of maize flour adulterated in turmeric powder.

Fluorescence quenching induced by competitive absorption between different components of solid foods was observed for the first time. By using front-face synchronous fluorescence spectroscopy (FFSFS) and fluorescence titration, competitive absorption between maize flour and turmeric powder was proven to occur between phenolic acids in maize flour and curcumin in turmeric powder. FFSFS was applied for the rapid and non-destructive determination of maize flour adulterated in turmeric powder. Prediction models were constructed by partial least square (PLS) regression based on unfolded total synchronous fluorescence spectra, and were validated by five-fold cross-validation and external validation, with the determination coefficient of prediction (Rp2) greater than 0.95, root mean square error of prediction (RMSEP) < 6%, relative error of prediction (REP) < 15% and residual predictive deviation (RPD) greater than 5. The limit of detection (LOD) of maize flour was approximately 9%. In addition, most relative errors for test samples were from -20% to 20%.

Front-Face Fluorimeter for the Determination of Cutting Time of Cheese Curd.

The yield of product (cheese) during the cheese-making process depends on the cutting time of the cheese curd. However, the determination of optimal cutting time on an industrial scale is difficult as current standard methods are destructive or analyse only small volumes and not the entire milk to be curdled into cheese. This paper presents a novel front-face fluorimeter (FFF) that is designed to be immersed into a milk batch to enable the determination of the cutting time of cheese curd without the destruction of the sample. The FFF sensor signal corresponds to physical changes in milk during cheese formation and has high predictive power (r > 0.85) and good accuracy (RSE = 30%, considering daily variation between milk samples). The performance of the presented fluorimeter was on par with standard rheological and Berridge methods.

Front-face synchronous fluorescence spectroscopy for rapid and non-destructive determination of free capsanthin, the predominant carotenoid in chili (Capsicum annuum L.) powders based on aggregation-induced emission.

Capsanthin is the major natural carotenoid pigment in red chili pepper possessing important bioactivity. Its conventional determination method is high performance liquid chromatography (HPLC) with complex and tedious sample pretreatment. In this study, synchronous front-face fluorescence spectroscopy (FFFS) was applied for the fast and non-invasive detection of free capsanthin in chili powders. Although capsanthin was only weak fluorescent in solution state, it showed strong fluorescence in two separated regions in front-face geometry which could also be clearly observed in chili powders. The mechanisms of these emissions are revealed to be aggregation-induced emission (AIE) and J-aggregate formation (JAF). The free capsanthin in 85 chili powder samples were determined by HPLC as in the range of 0.6-3.0 mg/g. The total synchronous FFFS spectra of these samples were scanned. Simple first-order models were built by partial least square regression (PLSR), and were validated by 5-fold cross-validation and external validation. The coefficients of determination (R2) were higher than 0.9, and the root mean square errors (RMSE) were less than 0.2 mg/g. The relative error of prediction (REP) was 9.9%, and the residual predictive deviation (RPD) was 3.7. The method was applied for the estimation of free capsanthin in several real-world samples with satisfactory analytical results. The average relative error to HPLC reference values was -11.8%.