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Baseline Correction with Asymmetric Least Squares Smoothing

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Abstract

Most baseline problems in instrumental methods are characterized by a smooth baseline and a superimposed signal that carries the analytical information: a se-ries of peaks that are either all positive or all negative. We combine a smoother with asymmetric weighting of deviations from the (smooth) trend get an effective baseline estimator. It is easy to use, fast and keeps the analytical peak signal in-tact. No prior information about peak shapes or baseline (polynomial) is needed by the method. The performance is illustrated by simulation and applications to real data.

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... Our particular interest is in the class of derivative smoothers that has its roots in the penalized least squares approach of Eilers [11]. Later variants extended the Eilers approach by using weighted least squares generalizations that iteratively update the baseline for a given spectrum [12][13][14]. What is peculiar about these state-of-the-art penalized baseline correction methods is the following observation: they do not consider analyte concentrations across samples. 1 This is curious 1 An earlier paper [3] does consider analyte concentrations via a different class of smoothing, but its regime because strongly absorbing or scattering analytes, possibly distinct from the response variable or analyte of interest, can dominate or strongly influence the observed spectral variability. ...
... Subsequent PBC variants of [12][13][14] (known as ASLS, AIRPLS and ARPLS, respectively) go much further and construct a separate weight matrix for each sample x :i . Moreover, each sample-specific weight matrix is also iteratively updated such that the normal equations in Eq.(4) become ...
... Hence, small values of λ (λ ≪ 1) are not warranted. The solution of Z(I + λ 2 C)X is equivalent to a sum involving the loading vectors v :j of the derivative operator D-see Eq. (12) in the Supplement. The filter factors f j = 1/(1 + λ 2 s 2 j ) in Eq. (12) can only damp or filter the corresponding loading vector v :j when λ is sufficiently large, i.e. (λ ≫ 1). ...
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Spectroscopic measurements can show distorted spectra shapes arising from a mixture of absorbing and scattering contributions. These distortions (or baselines) often manifest themselves as non-constant offsets or low-frequency oscillations. As a result, these baselines can adversely affect analytical and quantitative results. Baseline correction is an umbrella term where one applies pre-processing methods to obtain baseline spectra (the unwanted distortions) and then remove the distortions by differencing. However, current state-of-the art baseline correction methods do not utilize analyte concentrations even if they are available, or even if they contribute significantly to the observed spectral variability. We examine a class of state-of-the-art methods (penalized baseline correction) and modify them such that they can accommodate a priori analyte concentration such that prediction can be enhanced. Performance will be access on two near infra-red data sets across both classical penalized baseline correction methods (without analyte information) and modified penalized baseline correction methods (leveraging analyte information).
... Critical time-consuming functions have been rewritten in C++ and integrated as a static library into the application. In particular, the Asymmetric least square smoothing (ALS) method, implemented according to the algorithm proposed in [Eilers, 2005] with minor modifications, is used for baseline calculation. HDF5 format databases (https://www. ...
... An important function of this module is the decomposition of the loaded spectrum into components and the calculation of the baseline (Fig. 3). The baseline calculation is performed using the ALS method [Eilers, 2005] with minor modifications. In this method, the baseline parameters are set by only two values: p -asymmetry and λ -smoothness, which is an absolute advantage in automatic parameter selection. ...
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ArDI (Advanced spectRa Deconvolution Instrument) is a web-application for processing and analyzing of vibrational spectra of minerals (https://ardi.fmm.ru/). It is designed for express and reliable identification of minerals in geological samples. ArDI allows processing of spectra, searching for similar spectra in databases, and loading reference spectra into the database for its expansion. ArDI has prospects for development in several directions, including the improvement of the interface ergonomics and further development of algorithms for automatic processing of Raman spectra, filling the database with reference spectra, and integration the reference spectra database with the information system of Fersman Mineralogical Museum of the Russian Academy of Sciences and other mineralogical information systems. ArDI can be used for quick identification of minerals and interpretation of separate spectral bands. It can be useful in mineralogy, the examination of raw materials and gemstones, as well as in medicine, pharmacy, and criminalistics.
... Considering the spectral profiles shown in Figure 3, two commonly used preprocessing methods, baseline correction and normalization, were applied for comparison. Baseline corrections with asymmetric least squares smoothing [56] and total area normalization [57] were performed. In this part, the effect of crater compensation on the single-point signal was explored, which did not involve other variables. ...
... Considering the spectral profiles shown in Figure 3, two commonly used preprocessing methods, baseline correction and normalization, were applied for comparison. Baseline corrections with asymmetric least squares smoothing [56] and total area normalization [57] were performed. The results based on the calibration curve model can be seen in Table 8; we can see that total area normalization pretreatment obtained better results than no pretreatment at the wavelength of Cd II 226.50 nm and at Cd I 228.80 nm to some extent. ...
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Panax notoginseng (P. notoginseng) is a valuable herbal medicine, as well as a dietary food supplement known for its satisfactory clinical efficacy in alleviating blood stasis, reducing swelling, and relieving pain. However, the ability of P. notoginseng to absorb and accumulate cadmium (Cd) poses a significant environmental pollution risk and potential health hazards to humans. In this study, we employed laser-induced breakdown spectroscopy (LIBS) for the rapid detection of Cd. It is important to note that signal uncertainty can impact the quantification performance of LIBS. Hence, we proposed the crater–spectrum feature fusion method, which comprises ablation crater morphology compensation and characteristic peak ratio correction (CPRC), to explore the feasibility of signal uncertainty reduction. The crater morphology compensation method, namely, adding variables using multiple linear regression (MLR) analysis, decreased the root-mean-square error of the prediction set (RMSEP) from 7.0233 μg/g to 5.4043 μg/g. The prediction results were achieved after CPRC pretreatment using the calibration curve model with an RMSEP of 3.4980 μg/g, a limit of detection of 1.92 μg/g, and a limit of quantification of 6.41 μg/g. The crater–spectrum feature fusion method reached the lowest RMSEP of 2.8556 μg/g, based on a least-squares support vector machine (LSSVM) model. The preliminary results suggest the effectiveness of the crater–spectrum feature fusion method for detecting Cd. Furthermore, this method has the potential to be extended to detect other toxic metals in addition to Cd, which significantly contributes to ensuring the quality and safety of agricultural production.
... FTIR-ATR spectra of each sample (unaged and aged) were collected in triplicates corresponding to three different measurement spots on the sample surface. For better visualisation and comparability, the spectra (unaged and aged) were baseline corrected using asymmetric least squares smoothing by Eilers and Boelens (λ = 10 5 , p = 0.0001, 10 iterations) [44] and normalised to area = 1 ( Figure 1). To reduce the dimensionality of the dataset, specific wavenumbers were carefully selected for the data analysis. ...
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Vinyl acetate (VAc)-based emulsions represent one of the main media used by modern and contemporary artists. Their long-term behaviour is still not completely understood, especially due to the scarce knowledge on the influence of other compounds in the formulation, which may impact ageing over time. Besides the polymer backbone based on vinyl acetate, other co-monomers and additives can be added to the emulsion to alter the final film’s physical, chemical, and optical properties. By extension, the formulation will also impact the long-term stability of artworks and objects on which it has been applied, as well as possible current and future conservation interventions such as cleaning. For those reasons, studies shedding light on the correlation between composition and long-term stability are largely necessary. In this study, different emulsions, including homopolymers, copolymers, plasticised, and un-plasticised compositions, were gathered and artificially aged. A multivariate analyses approach based on the application of principal component analyses (PCA) and hierarchical cluster analyses (HCA) was employed for the first time on the combination of data obtained by pH, contact angle (CA), colour measurements, Fourier transform infrared spectroscopy in attenuated total reflection (FTIR-ATR), and size exclusion chromatography (SEC). This approach helped to highlight the changes that occurred during ageing and find correlations with the formulation compositions. The results further sustain the thesis that not all vinyl acetate-based emulsions are chemically the same and that their formulation deeply impacts their long-term behaviour.
... The spectral baseline was subtracted by an asymmetric least-squares smoothing algorithm in order to eliminate the auto fluorescence background. 20 And we randomly selected 5 points for each sample to obtain the SERS spectrum and calculated the average spectrum for subsequent data processing. ...
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We report the development and characterization of an optical nanosensor for the detection of labile zinc in biological environments. The readout is based on surface-enhanced Raman scattering promoted by a Raman reporter conjugated to the inner plasmonic cavity of hollow silica nanocapsules. We quantify Zn²⁺ by obtaining the ratio between a Zn²⁺-sensitive band and a Zn²⁺-insensitive band. The Raman reporter measures within the range from 10–5 to 10–11 M and exhibits a limit of detection of 10–11.72 M. The nanosensor discriminates between intracellular and extracellular Zn²⁺ concentrations.
... Data analysis was performed in MATLAB (Mathworks). Fluorescence traces were converted to the ratio of change in fluorescence over background fluorescence ( ∆ ⁄ ) , with background fluorescence estimated via asymmetric least squares smoothing (28). Fluorescence ratios used for spatial and temporal inference analysis were filtered with a high pass 6 th order Butterworth filter with a cut-off frequency of 0.05 Hz to eliminate slow variability at time scales of 20 sec or greater. ...
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Time-dependent features are present in many sensory stimuli. In the sensory cortices, timing features of stimuli are represented by spatial as well as temporal code. A potential mechanism by which cortical neuronal networks perform temporal-to-spatial conversion is ‘reservoir computing’. The state of a recurrently-connected network (reservoir) represents not only the current stimulus, or input, but also prior inputs. In this experimental study, we determined whether the state of an isolated cortical network could be used to accurately determine the timing of occurrence of an input pattern – or, in other words, to convert temporal input features into spatial state of the network. We used an experimental system based on patterned optogenetic stimulation of dissociated primary rat cortical cultures, and read out activity via fluorescent calcium indicator. We delivered input sequences of patterns such that a pattern of interest occurred at different times. We developed a readout function for network state based on a support vector machine (SVM) with recursive feature elimination and custom error correcting output code. We found that the state of these experimental networks contained information about inputs for at least 900 msec. Timing of input pattern occurrence was determined with 100 msec precision. Accurate classification required many neurons, suggesting that timing information was encoded via population code. Trajectory of network state was largely determined by spatial features of the stimulus, with temporal features having a more subtle effect. Local reservoir computation may be a plausible mechanism for temporal/spatial code conversion that occurs in sensory cortices. Significance Statement Handling of temporal and spatial stimulus features is fundamental to the ability of sensory cortices to process information. Reservoir computation has been proposed as a mechanism for temporal-to-spatial conversion that occurs in the sensory cortices. Furthermore, reservoirs of biological, living neurons have been proposed as building blocks for machine learning applications such as speech recognition and other time-series processing. In this work, we demonstrated that living neuron reservoirs, composed of recurrently connected cortical neurons, can carry out temporal-spatial conversion with sufficient accuracy and at sufficiently long time scale to be a plausible model for information processing in sensory cortices, and to have potential computational applications.
... Most of this background originates from recoil scattering of oxygen atoms in the sample; thus, restricting the integration of the whole S(|Q|,hω) to regions with |Q| < 15 Å −1 helps to improve the statistics. We removed this background, shown in red, estimated using an asymmetric least-squares algorithm with p = 5 and λ = 0.01 [9]. The resulting data are shown in figure 2. ...
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In a recent manuscript, Lawrence Bright et al (2023 J. Phys.: Condens. Matter 35 175501) reported the resonant inelastic x-ray scattering spectra of U3O8, as well as UN. Their goal was to identify electronic multiplets associated with a 5f¹ configuration with ground state 2F5/2 . Complete active space self-consistent field with spin–orbit coupling (CASSCF-SOC) predicted that 2F5/2 transitions should be observable at 190 and 328 meV. However, these energies were not accessible in their experiment. They suggested that the recent inelastic neutron scattering results of Miskowiec et al (2021 Phys. Rev. B 103 205101) could have been sensitive to these transitions. Here we show that transitions of this possible origin appear in that dataset near 198, 262, 362, and potentially 448 meV.
... Unlike the exchange interaction that leads to ferromagnetic order (a collinear spin arrangement), the DMI can tilt magnetic moments such that the combined interactions engender whirlpool-like spin structures that behave as particles that can be controlled by applied currents. [1][2][3][4][5] Skyrmions were first observed in B20-phase cubic materials, such as MnSi, 6 Fe 1−x Co x Si, 7 and FeGe, 1 due to isotropic DMI originating from the non-centrosymmetric crystal structure. On the other hand, if the DMI is anisotropic, nonsymmetric skyrmions or antiskyrmions -the antiparticles of skyrmions -can form. ...
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A promising architecture for next-generation, low energy spintronic devices uses skyrmions -- nanoscale whirlpools of magnetic moment -- as information carriers. Notably, schemes for racetrack memory have been proposed in which skyrmions and antiskyrmions, their antiparticle, serve as the logical bits 1 and 0. However, major challenges exist to designing skyrmion-antiskyrmion based computing. The presence of both particles in one material is often mutually exclusive such that few systems have been identified in which they coexist, and in these systems their appearance is stochastic rather than deterministic. Here, we create a tunable skyrmion-antiskyrmion system in FeGe films through ion-irradiation and annealing, and detail the structural properties of the films under these various conditions. Specifically, we irradiate epitaxial B20-phase FeGe films with 2.8 MeV Au$^{4+}$ ions, showing evidence that the amorphized regions preferentially host antiskyrmions at densities controlled by the irradiation fluence. In this work, we focus on a subsequent, systematic electron diffraction study with in-situ annealing, demonstrating the ability to recrystallize controllable fractions of the material at temperatures ranging from approximately 150$^{\circ}$ C to 250$^{\circ}$ C, enabling further tunability of skyrmion/antiskyrmion populations. We describe the crystallization kinetics using the Johnson-Mehl-Avrami-Kolmogorov model, finding that growth of crystalline grains is consistent with diffusion-controlled one-to-two dimensional growth with a decreasing nucleation rate. The procedures developed here can be applied towards creation of skyrmion-antiskyrmion systems for energy-efficient, high-density data storage, spin wave emission produced by skyrmion-antiskyrmion pair annihilation, and more generally testbeds for research on skyrmion-antiskyrmion liquids and crystals.
... The ALS method, used for baseline correction, was developed by Eilers and Boelens [23], and consists of a correction made to the original regularized least squares smoothing, shown as follows in equation (1): ...
... For infrared data sets, the following were tested: Savitzky-Golay (SG) smoothing, Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV), baseline offset, first and second derivative (SG, second polynomial order and different window sizes). In the case of the Raman data sets, Automatic Weighted Least Squares (AWLS) and Asymmetric Least Squares (ALS), besides normalization and the other mentioned preprocessing methods were tested (Eigenvector, 2019;Eilers, Boelens, 2005). ...
... Outlier pixels were determined as those where the difference (raw−median) values exceeded 100. 2. Baseline removal by asymmetric least-squares smoothing. 13 3. Savitzky-Golay filtering 14 with polynomial order 3 and window length 5. To obtain the calibration line slope, we integrated the signal intensities of the entire spectra to obtain a scalar number for varying concentrations (Figures 3 and S1). Then, the LODs of single and dual line probes were calculated as the following: 15 ...
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Optical fiber probe-based Raman spectroscopy systems are widely used for in situ measurements ranging from material characterization to biomedical applications. However, small Raman cross sections necessitate the use of high-power lasers or long exposure times that limit Raman’s larger application to multiple research fields. This limitation can be overcome by collecting more Raman photons through additional collection fibers with taller detectors. This system configuration requires replacement of the detector and modification of the spectrograph to incorporate larger optical components, making it a costly and cumbersome option. In probe-based Raman systems, a typical detector image shows stacked collection fibers on the vertical axis and Raman spectra on the horizontal axis. While the vertical pixels are fully packed with multiple collection fibers, horizontal pixels have broad silent regions due to the narrow bandwidth of Raman peaks, potentially wasting valuable detector pixels. Here, we propose a new approach utilizing horizontally shifted collection fibers rather than vertically stacked ones. We designed and fabricated a novel collection fiber bundle that has horizontally shifted optical fibers in two vertical lines at the spectrograph entrance. This custom-made fiber bundle was incorporated into the imaging spectrograph to provide multiple horizontally shifted spectra on the detector. Through deconvolution, the original spectra can be recovered with an improved detection limit from greater photon collection. We demonstrate an enhanced limit of detection on various bioanalytes, such as glucose, urea, and lactate. Further, we applied the probe to measure tissue Raman spectra and successfully decomposed them into basis spectra, demonstrating the potential application of high-throughput in vivo tissue diagnosis. Our approach provides a simple, cost-effective, and universal method to increase the throughput without modifying existing Raman spectrometers.
... Here, classes were set as bacterial strains. To minimise the risk of overtraining the model, the number of PCs used was such that each contributed >1% to the O-PTIR spectra were first baseline corrected using an asymmetric least squares baseline correction algorithm 24 , EMSC scaled and smoothed using a Gaussian smoothing algorithm 25 with a window width of 9. After this, spectra were once again analysed using mean centred PCA followed by DFA, once more ensuring that each PC contributed >1% to the TEV, and the last three spectra per day for each biological replicate were used as a test set. ...
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Fourier-transform infrared (FTIR) spectroscopy is a simple, fast and inexpensive method with a history of use for bacterial analysis. However, due to the limitations placed on spatial resolution inherent to infrared wavelengths, analysis has generally been performed on bulk samples, leading to biological variance among individual cells to be buried in averaged spectra. This also increases the bacterial load necessary for analysis, which can be problematic in clinical settings where limiting incubation time is valuable. Optical photothermal-induced resonance (O-PTIR) spectroscopy is a novel method aiming to bypass this limitation using a secondary lower wavelength laser, allowing for infrared measurements of a single bacterium. Here, using Staphylococcus capitis, Staphylococcus epidermidis and Micrococcus luteus strains as a model and FTIR as a benchmark, we examined O-PTIR's ability to discriminate single-cell samples at the intergenetic, interspecific and intraspecific levels. When combined with chemometric analysis, we showed that O-PTIR is capable of discriminating different between genera, species and strains within species to a degree comparable with FTIR. Furthermore, small variations in the amide bands associated with differences in the protein structure can still be seen in spite of smaller sample sizes. This demonstrates the potential of O-PTIR for single-cell bacterial analysis and classification.
... After the acquisition of spectra, range reductions (to 350-2700 cm −1 ) and baseline corrections were implemented. Asymmetric least-squares smoothing with a threshold of 0.01, a smoothing factor of 5, and 10 iterations was employed for the baseline corrections [95]. The data were smoothed using Savitzky-Golay filtering [96], available in the MATLAB ® Signal Processing Toolbox, based on a second-order polynomial and with a 17-point window. ...
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In small clinical studies, the application of transcranial photobiomodulation (PBM), which typically delivers low-intensity near-infrared (NIR) to treat the brain, has led to some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, despite the extensive literature detailing the mechanisms of action underlying PBM outcomes, the specific mechanisms affecting neurodegenerative diseases are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and thus provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer’s and other neurodegenerative diseases. Thus, we investigated the effects of PBM on these cellular structures in the quest for insights into the underlying therapeutic mechanisms. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm² dose). Peaks in the Raman fingerprint region (300–1900 cm⁻¹)—in particular, in the amide I band (1600–1700 cm⁻¹)—were used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed, producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of polymerized NIR-exposed tubulin, characterized by a notable decrease in α-helix content and a concurrent increase in β-sheets compared to the control samples. This PBM-induced α-helix to β-sheet transition connects to reduced microtubule stability and the introduction of dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer’s disease, through the introduction of an intervention following this transition.
... Tu and Wang (2023) introduced expectile correlation and expectile partial correlation to measure the importance of regressors, and propose the expectile partial correlation screening to detect important variables for ultrahigh dimensional data. More applications of expectile regression can be found in risk analysis (Kuan et al. 2009;Xie et al. 2014), medicine (Eilers and Boelens 2005), insurance (Gao and Yu 2023), among others. ...
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As an effective tool for data analysis, expectile regression is widely used in the fields of statistics, econometrics and finance. However, most studies focus on the case where the sample size is not massive and the dimension is low or fixed. This paper studies the parameter estimation and inference for large-scale expectile regression when the number of parameters grows to infinity. Specifically, an inverse probability weighted asymmetric least squares estimator based on Poisson subsampling (ALS-P) is proposed. Theoretically, the convergence rate and asymptotic normality for ALS-P are established. Furthermore, the optimal subsampling probabilities based on the L-optimality criterion are derived. Finally, extensive simulations and two real-world datasets are conducted to illustrate the effectiveness of the proposed methods.
... Since transient pressure events trigger bursts of afferent nerve activity, and indomethacin inhibits transient pressure events, it is possible that the indomethacin-induced decrease in afferent nerve activity simply reflects the decrease in the amplitude of transient pressure events. To address this possibility, we fitted the nerve and pressure recordings with a least squares baseline estimation model (30). When we examined the relationship between the baseline afferent nerve signal and the baseline pressure, we still observed a robust and significant decrease in nerve activity following indomethacin treatment (Fig. 8C). ...
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The transitional epithelial cells (urothelium) that line the lumen of the urinary bladder form a barrier between potentially harmful pathogens, toxins, and other bladder contents and the inner layers of the bladder wall. The urothelium, however, is not simply a passive barrier, as it can produce signaling factors, such as ATP, nitric oxide, prostaglandins and other prostanoids, that can modulate bladder function. We investigated whether select substances produced by the urothelium could directly modulate the contractility of the underlying urinary bladder smooth muscle. Force was measured in isolated strips of mouse urinary bladder with the urothelium intact or denuded. Bladder strips developed spontaneous tone and phasic contractions. In urothelium-intact strips, basal tone, as well as the frequency and amplitude of phasic contractions, were 25%, 32%, and 338% higher than in urothelium-denuded strips, respectively. Basal tone and phasic contractility in urothelium-intact bladder strips were abolished by the cyclooxygenase (COX) inhibitor indomethacin (10 mM) or the voltage-dependent Ca ²⁺ channel blocker diltiazem (50 mM), whereas blocking neuronal sodium channels with tetrodotoxin (1 mM) had no effect. These results suggest that prostanoids produced in the urothelium enhance smooth muscle tone and phasic contractions by activating voltage-dependent Ca ²⁺ channels in the underlying bladder smooth muscle. We went on to demonstrate that blocking COX inhibits the generation of transient pressure events in isolated pressurized bladders and greatly attenuates the afferent nerve activity during bladder filling, suggesting that urothelial prostanoids may also play a role in sensory nerve signaling.
... Критические по времени выполнения функции были переписаны на языке C++ и интегрированы в качестве статической библиотеки в приложение. В частности, для вычисления базовой линии используется метод Asymmetric least square smoothing (ALS), реализованный по алгоритму, предложенному в работе [Eilers, 2005], с небольшими модификациями. Для хранения спектров используются базы данных в формате HDF5 (https://www.hdfgroup.org/solutions/ ...
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ArDI (Advanced spectRa Deconvolution Instrument) – это веб-приложение для обработки и анализа колебательных спектров минералов (https://ardi.fmm.ru/). Приложение предназначено для быстрой и надежной идентификации минералов в геологических образцах. ArDI позволяет обрабатывать спектры, проводить поиск похожих спектров в базах данных и загружать эталонные спектры минералов в базу данных для ее расширения. ArDI имеет перспективы развития в нескольких направлениях, включая улучшение эргономики интерфейса и алгоритмов автоматической обработки спектров комбинационного рассеяния света (КРС), наполнение базы эталонных спектров и сопряжение базы данных эталонных спектров с информационной системой Минералогического музея им. А.Е. Ферсмана РАН и другими информационными системами, имеющими дело с минералами. Инструментарий ArDI может быть использован для быстрой диагностики минералов и интерпретации отдельных полос колебаний на спектрах. Он может быть полезен в минералогии, экспертизе сырья и ограненных драгоценных камней, а также в медицине, фармацевтике и криминалистике.
... Following frequency and phase alignment and normalisation steps described earlier, an additional 2 Hz Gaussian line broadening was applied to enhance spectral SNR. Spectra were cropped to the region between 0 and 4.3 ppm and asymmetric least squares baseline correction was applied (Eilers & Boelens, 2005). Since the true dynamic responses of lactate and glutamate to visual stimuli are yet to be established, a simple boxcar function was assumed, with values of 0 during rest blocks and 1 in the task block. ...
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Background Functional MRS (fMRS) is a technique used to measure metabolic changes in response to increased neuronal activity, providing unique insights into neurotransmitter dynamics and neuroenergetics. In this study we investigate the response of lactate and glutamate levels in the motor cortex during a sustained motor task using conventional spectral fitting and explore the use of a novel analysis approach based on the application of linear modelling directly to the spectro-temporal fMRS data. Methods fMRS data were acquired at a field strength of 3 Tesla from 23 healthy participants using a short echo-time (28ms) semi-LASER sequence. The functional task involved rhythmic hand clenching over a duration of 8 minutes and standard MRS preprocessing steps, including frequency and phase alignment, were employed. Both conventional spectral fitting and direct linear modelling were applied, and results from participant-averaged spectra and metabolite-averaged individual analyses were compared. Results We observed a 20% increase in lactate in response to the motor task, consistent with findings at higher magnetic field strengths. However, statistical testing showed some variability between the two averaging schemes and fitting algorithms. While lactate changes were supported by the direct spectral modelling approach, smaller increases in glutamate (2%) were inconsistent. Exploratory spectral modelling identified a 4% decrease in aspartate, aligning with conventional fitting and observations from prolonged visual stimulation. Conclusion We demonstrate that lactate dynamics in response to a prolonged motor task are observed using short-echo time semi-LASER at 3 Tesla, and that direct linear modelling of fMRS data is a useful complement to conventional analysis. Future work includes mitigating spectral confounds, such as scalp lipid contamination and lineshape drift, and further validation of our novel direct linear modelling approach through experimental and simulated datasets.
... To compute the noise, we fit the baseline of the spectra in the 1300-1600 cm -1 spectral range, which does not contain Raman modes for apatite with asymmetric least squares (AsLS) smoothing 74 ; the value of the noise is the standard deviation of the signal in that range after baseline subtraction. To compute the signal-to-noise ratio (SNR), we divided the height of the fitted peak by this noise value. ...
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Planetary exploration relies considerably on mineral characterization to advance our understanding of the solar system, the planets and their evolution. Thus, we must understand past and present processes that can alter materials exposed on the surface, affecting space mission data. Here, we analyze the first dataset monitoring the evolution of a known mineral target in situ on the Martian surface, brought there as a SuperCam calibration target onboard the Perseverance rover. We used Raman spectroscopy to monitor the crystalline state of a synthetic apatite sample over the first 950 Martian days (sols) of the Mars2020 mission. We note significant variations in the Raman spectra acquired on this target, specifically a decrease in the relative contribution of the Raman signal to the total signal. These observations are consistent with the results of a UV-irradiation test performed in the laboratory under conditions mimicking ambient Martian conditions. We conclude that the observed evolution reflects an alteration of the material, specifically the creation of electronic defects, due to its exposure to the Martian environment and, in particular, UV irradiation. This ongoing process of alteration of the Martian surface needs to be taken into account for mineralogical space mission data analysis.
... Our study follows the recommendations of the checklist "Minimum Information about the Clinical Artificial Intelligence Modeling" (51) for artificial intelligence modeling (see table S5). Several techniques were used to preprocess the mass spectra: smoothing using the moving average method, baseline correction using the asymmetric least squares method (52), and peak picking using the derivative method. These steps were intended to minimize noise while preserving low-intensity signals as much as possible (53). ...
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Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control strategies targeting mosquito longevity, as the risk of pathogen transmission increases with mosquito age. However, the available tools to estimate field mosquito age are often approximate and time-consuming. Here, we show a rapid method that combines matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry with deep learning for mosquito age prediction. Using 2763 mass spectra from the head, legs, and thorax of 251 field-collected Anopheles arabiensis mosquitoes, we developed deep learning models that achieved a best mean absolute error of 1.74 days. We also demonstrate consistent performance at two ecological sites in Senegal, supported by age-related protein changes. Our approach is promising for malaria control and the field of vector biology, benefiting other disease vectors like Aedes mosquitoes.
... To remove the sloping background remaining after spectral subtraction (as per Eq. (1)), an asymmetric least squares (AsLS) baseline correction algorithm 36,37 was applied. ...
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A fiber probe has been developed that enables simultaneous acquisition of mid-infrared (MIR) and Raman spectra in the region of 3100–2600 cm⁻¹. Multimodal measurement is based on a proposed ZrO2 crystal design at the tip of an attenuated total reflection (ATR) probe. Mid-infrared ATR spectra are obtained through a pair of chalcogenide infrared (CIR) fibers mounted at the base of the crystal. The probe enables both excitation and acquisition of a weak Raman signal from a portion of the sample in front of the crystal using an additional pair of silica fibers located in a plane perpendicular to the CIR fibers. The advantages of combining MIR and Raman spectra in a single probe have been discussed.
... The data collected from the Raman analysis was then processed using a custom python program in Jupyter Lab [38]. Each result was individually baseline corrected using asymmetric least square smoothing [39], with a p value of 0.1, a λ of 1000 and 10 iterations. After smoothing, each curve was split into four ranges which are listed in Table 2. ...
... , 10 stack of ten 40 × 40 raster scans, organized into a single volumetric hypercube for analysis. We preprocess the data before unmixing using the following protocol: 1) spectral cropping to the fingerprint region 700-1800 cm −1 ; 2) cosmic spike removal using the algorithm in [92] with kernel of size 3 and z-value threshold of 8; 3) denoising with Savitzky-Golay filter using a cubic polynomial kernel of size 7 [93]; 4) baseline correction using Asymmetric Least Squares (AsLS) with smoothing parameter λ = 10 6 , penalizing weighting factor p = 0.01, differential matrix of order 2, maximum iterations set to 50, exit criteria with tolerance threshold of t = 0.001 [94]; 5) global MinMax normalization to the interval [0, 1]. ...
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Raman spectroscopy is widely used across scientific domains to characterize the chemical composition of samples in a non-destructive, label-free manner. Many applications entail the unmixing of signals from mixtures of molecular species to identify the individual components present and their proportions, yet conventional methods for chemometrics often struggle with complex mixture scenarios encountered in practice. Here, we develop hyperspectral unmixing algorithms based on autoencoder neural networks, and we systematically validate them using both synthetic and experimental benchmark datasets created in-house. Our results demonstrate that unmixing autoencoders provide improved accuracy, robustness and efficiency compared to standard unmixing methods. We also showcase the applicability of autoencoders to complex biological settings by showing improved biochemical characterization of volumetric Raman imaging data from a monocytic cell.
... Although not as pronounced, the ABP signals are also affected by changes in intrathoracic pressure. Therefore, we investigated the efficacy of two different methods of baseline filtering on both CVP and ABP signals: Asymmetric Least Squares Smoothing (ALS) [10], and Discrete Wavelet Transform (DTW) [11]. In both cases, the baseline is substracted from the original signal, but also used as the respiratory trace in our analysis. ...
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Objective: Our group has shown that central venous pressure (CVP) can optimise atrioventricular (AV) delay in temporary pacing (TP) after cardiac surgery. However, the signal-to-noise ratio (SNR) is influenced both by the methods used to mitigate the pressure effects of respiration and the number of heartbeats analysed. This paper systematically studies the effect of different analysis methods on SNR to maximise the accuracy of this technique. Methods: We optimised AV delay in 16 patients with TP after cardiac surgery. Transitioning rapidly and repeatedly from a reference AV delay to different tested AV delays, we measured pressure differences before and after each transition. We analysed the resultant signals in different ways with the aim of maximising the SNR: (1) adjusting averaging window location (around versus after transition), (2) modifying window length (heartbeats analysed), and (3) applying different signal filtering methods to correct respiratory artefact. Results: (1) The SNR was 27 % higher for averaging windows around the transition versus post-transition windows. (2) The optimal window length for CVP analysis was two respiratory cycle lengths versus one respiratory cycle length for optimising SNR for arterial blood pressure (ABP) signals. (3) Filtering with discrete wavelet transform improved SNR by 62 % for CVP measurements. When applying the optimal window length and filtering techniques, the correlation between ABP and CVP peak optima exceeded that of a single cycle length (R = 0.71 vs. R = 0.50, p < 0.001). Conclusion: We demonstrated that utilising a specific set of techniques maximises the signal-to-noise ratio and hence the utility of this technique.
... Raman spectra contain desired signals and different distortions, such as fluorescent background noise and baseline shift. Eilers and Boelens proposed Raman spectra baseline correction using asymmetric least square smoothing (Eilers & Boelens, 2005). Asymmetric least square smoothing uses Whittaker smoother to calculate the baseline of the spectra: ...
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Advanced process control in the biopharmaceutical industry often lacks real‐time measurements due to resource constraints. Raman spectroscopy and Partial Least Squares (PLS) models are often used to monitor bioprocess cultures in real‐time. In spite of the ease of training, the accuracy of the PLS model is impacted if it is not used to predict quality attributes for the cell lines it is trained on. To address this issue, a deep convolutional neural network (CNN) is proposed for offline modeling of metabolites using Raman spectroscopy. By utilizing asymmetric least squares smoothing to adjust Raman spectra baselines, a generic training data set is created by amalgamating spectra from various cell lines and operating conditions. This data set, combined with their derivatives, forms a two‐dimensional model input. The CNN model is developed and validated for predicting different quality variables against measurements from various continuous and fed‐batch experimental runs. Validation results confirm that the deep CNN model is an accurate generic model of the process to predict real‐time quality attributes, even in experimental runs not included in the training data. This model is robust and versatile, requiring no recalibration when deployed at different sites to monitor various cell lines and experimental runs.
... Cosmic rays were eliminated through median filtering using the MAT-LAB built-in function medfilt1 with default settings. Next, an Alternating Least Squares (ALS) baseline correction was performed using parameters λ = 10 5 and p = 0.005 according to Eilers (2003) to reduce fluorescence contribution to the spectra (De Juan et al. 2014). Each image was clustered into two segments by use of k-means cluster analysis, which separated the lumina from the rest of the wood structure (i.e., the cell walls of tracheids and ray cells as well as the middle lamellae between cells, henceforth together denoted 'the cell wall cluster'). ...
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Acetylation is a commercialised chemical wood modification technology that increases the durability of wood against microbial attack. However , the details of how acetylation protects the wood structure from fungal degradation are still unclear. In this study, we tested the hypothesis that the resistance against microbial attack depends on the localisation of acetylation within the cell wall. The methodology involved two types of acetylation (uniform and lumen interface modification), which were analysed by lab-scale degradation with Rhodonia placenta, chitin quantification, infrared spectroscopy, and Raman microspectroscopy. The location of the acety-lation did not affect overall mass loss during degradation experiments. Instead, the mass loss was related to the intensity of the treatment. However, chemical imaging of the interface acetylated specimens showed that degradation primarily took place in cell wall regions that were less acetylated. It was also observed that the fungus required more fungal biomass (i.e., fungal mycelia) to degrade acetylated wood than untreated wood. Based on dimensions and comparison to a reference spectrum, several cross-sections of hyphae located within lumina were discovered in the Raman images. These hyphae showed presence of chitin, water and chelated metals within their walls, and could be separated into an inner and an outer part based on their chemistry as seen in the spectra. The outer part was distinguished by a relatively higher amount of water and less chelated iron than the inner part.
... As a prescreening method, the surface areas in each layer that showed traces of MP were identified and further analyzed individually using a spectral unmixing strategy. This spectral unmixing strategy, applied to each relevant surface region, consisted of a baseline removing preliminary step (using the Asymmetric Least Squares approach proposed by Eiliers et al. (Eilers and Boelens, 2005) followed by multivariate curve resolution-alternating least squares (de Juan, 2019), imposing a nonnegativity constraint in the spectral and concentration profiles. Moreover, after calculating the optimal model for each individual region, the concentration profile of the MP was isolated and scaled from 0 to 1 for better visualization (Fig. 1), and the spectral profile of the MP was validated by comparison with the corresponding standard spectrum (Fig. 2). ...
... The final step in our background fitting involves an asymmetric least squares smoothing. 33 The background fitting parameters sometimes need to be adjusted based on the type of data collected. For example, we use different parameters for different molecular spectra such as AlO. ...
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This article presents methodological advances in the state-of-the-art for making time-dependent, thermochemical measurements within kilogram-scale explosive post-detonation fireballs utilizing tunable laser absorption spectroscopy. This measurement capability is critical for validating multi-scale, multi-physics models of post-detonation dynamics. The technique is based on hardened gauges built around rapidly-tunable lasers and custom post-processing algorithms that provide quantitative thermochemical data interior to large and opaque explosive fireballs. The authors present a holistic overview of the technique including gauge design, the laser absorption diagnostic, and the custom data processing algorithms. Additionally, fielding high-bandwidth laser absorption probes at stand-off ranges presents new challenges in data processing that must compensate for long distance signal transmission effects. We highlight representative data from a hardened gauge measurement at 0.81 m stand-off from a 2.78 kg LX-14 explosive charge detonated in an outdoor test arena. We discuss progress in all-optical measurement of temperature, pressure, and water vapor number density at a 100 kHz repetition rate during the first 10 ms of the fireball evolution. We conclude the article with a brief discussion on our current approach for comparing hardened gauge measurements with computational fluid dynamic simulations.
... Initially, a background signal spectrum was obtained from a region without any analytical signal (e.g., at the end of the chromatographic region) and then subtracted from the raw data matrix. Subsequently, the asymmetric least-square algorithm proposed by Eilers [25] was used to correct the baseline drift caused by the variations of the mobile phase composition [31] (Figure S For the chemometric analysis, data modelling was accomplished by building an augmented column-wise data matrix (D a and D b for EDP-AVO-EHMC and HOMO region, respectively) containing the validation or milk sample data on the top and all the calibration data matrices below. The number of spectrally active components in D a and D b was estimated by applying singular value decomposition (SVD). ...
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Organic UV filters (UVFS) are used to mitigate the dermal effects associated with health risks from UV radiation, making them essential in personal care products. UVFS are frequently identified in environmental samples due to their high lipophilicity and persistence, underscoring the urgency of comprehensive assessments and regulatory measures aimed at safeguarding ecosystems and human health. The present study reports a multiclass analytical method for determining 16 UV sunscreens and metabolites in breast milk based on an ultrasound-assisted-dispersive liquid-liquid micro-extraction (UA-DLLME) with further chromatographic and chemometric resolution. The experimental conditions of the UA-DLLME were optimized through the implementation of the Design of Experiment tools. To model the responses, least-squares and artificial neural network methodologies were implemented. The optimal conditions were found by employing the desirability function. The samples were analyzed through reverse-phase liquid chromatographic separation, UV diode array, and fast-scanning fluorescence detection. The chromatographic analysis enabled the resolution of 16 analytes in a total time of 13.0 min. Multivariate curve resolution-alternating least-square (MCR-ALS) modelling was implemented to resolve analytes that were not fully resolved and to determine analytes that coeluted with endogenous components of the breast milk samples. An enrichment factor of 5-fold concentration was obtained with this methodology, reaching recoveries between 65 % and 105 % for 13 multiclass UV sunscreens and metabolites in breast milk samples with RSD % and REP % lower than 12 %.
... Background fluorescence was removed using an asymmetric least-squares smoothing method. 35 The spectra acquired for each sample were vectornormalized and averaged. Spectrum normalization and data analysis were performed using OriginPro, Version 2019 (OriginLab Corporation, Northampton, MA, USA). ...
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Extracellular vesicles (EVs) have mostly been investigated as carriers of biological therapeutics such as proteins and RNA. Nevertheless, small-molecule drugs of natural or synthetic origin have also been loaded into EVs, resulting in an improvement of their therapeutic properties. A few methods have been employed for EV cargo loading, but poor yield and drastic modifications of vesicles remain unsolved challenges. We tested a different strategy based on temporary pH alteration through incubation of EVs with alkaline sodium carbonate, which resulted in conspicuous exogenous molecule incorporation. In-depth characterization showed that vesicle size, morphology, composition, and uptake were not affected. Our method was more efficient than gold-standard electroporation, particularly for a potential therapeutic toxin: the plant Ribosome Inactivating Protein saporin. The encapsulated saporin resulted protected from degradation, and was efficiently conveyed to receiving cancer cells and triggered cell death. EV-delivered saporin was more cytotoxic compared to the free toxin. This approach allows both the structural preservation of vesicle properties and the transfer of protected cargo in the context of drug delivery.
... After the acquisition of spectra, range reductions (to 350-2700 cm −1 ) and baseline corrections were implemented. An asymmetric least-squares smoothing with a 0.01 threshold, a smoothing factor of 5, and 10 iterations was employed for the baseline corrections [89]. The data were smoothed using Savitzky-Golay filtering [90], available in the Matlab ® Signal Processing Toolbox, based on a second-order polynomial and with a 17-point window. ...
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In small clinical studies, the application of photobiomodulation (PBM), which typically delivers near-infrared (NIR) to treat the brain, has presented some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, while the literature is rich with the mechanisms of action underlying PBM outcomes, the underlying mechanisms affecting a neurodegenerative disease are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and hence provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer's and other neurodegenerative diseases. We investigated the effects of PBM on these structures in the quest for answers. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm2 dose). Peaks in the Raman fingerprint region (300–1900 cm−1), in particular, in the amide I band (1600–1700 cm−1), can be used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed—producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of NIR-exposed tubulin, characterized by a notable decrease in α-helix content and a concurrent increase in β-sheets compared to the control samples. The α-helix to β-sheet transition suggests that PBM reduces microtubule stability and introduces dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer's disease.
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Raman spectroscopy is widely used across scientific domains to characterize the chemical composition of samples in a nondestructive, label-free manner. Many applications entail the unmixing of signals from mixtures of molecular species to identify the individual components present and their proportions, yet conventional methods for chemometrics often struggle with complex mixture scenarios encountered in practice. Here, we develop hyperspectral unmixing algorithms based on autoencoder neural networks, and we systematically validate them using both synthetic and experimental benchmark datasets created in-house. Our results demonstrate that unmixing autoencoders provide improved accuracy, robustness, and efficiency compared to standard unmixing methods. We also showcase the applicability of autoencoders to complex biological settings by showing improved biochemical characterization of volumetric Raman imaging data from a monocytic cell.
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Raman spectroscopy, renowned for its unique ability to provide a molecular fingerprint, is an invaluable tool in industry and academic research. However, various constraints often hinder the measurement process, leading to artifacts and anomalies that can significantly affect spectral measurements. This review begins by thoroughly discussing the origins and impacts of these artifacts and anomalies stemming from instrumental, sampling, and sample-related factors. Following this, we present a comprehensive list and categorization of the existing correction procedures, including computational, experimental, and deep learning (DL) approaches. The review concludes by identifying the limitations of current procedures and discussing recent advancements and breakthroughs. This discussion highlights the potential of these advancements and provides a clear direction for future research to enhance correction procedures in Raman spectral analysis.
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Across vertebrate species, the olfactory epithelium (OE) exhibits the uncommon feature of lifelong neuronal turnover. Epithelial stem cells give rise to new neurons that can adequately replace dying olfactory receptor neurons (ORNs) during developmental and adult phases and after lesions. To relay olfactory information from the environment to the brain, the axons of the renewed ORNs must reconnect with the olfactory bulb (OB). In Xenopus laevis larvae, we have previously shown that this process occurs between 3 and 7 weeks after olfactory nerve (ON) transection. In the present study, we show that after 7 weeks of recovery from ON transection, two functionally and spatially distinct glomerular clusters are reformed in the OB, akin to those found in non‐transected larvae. We also show that the same odourant response tuning profiles observed in the OB of non‐transected larvae are again present after 7 weeks of recovery. Next, we show that characteristic odour‐guided behaviour disappears after ON transection but recovers after 7–9 weeks of recovery. Together, our findings demonstrate that the olfactory system of larval X. laevis regenerates with high accuracy after ON transection, leading to the recovery of odour‐guided behaviour.
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Protein production in the biopharmaceutical industry necessitates the utilization of multiple analytical techniques and control methodologies to ensure both safety and consistency. To facilitate real‐time monitoring and control of cell culture processes, Raman spectroscopy has emerged as a versatile analytical technology. This technique, categorized as a Process Analytical Technology, employs chemometric models to establish correlations between Raman signals and key variables of interest. One notable approach for achieving real‐time monitoring is through the application of just‐in‐time learning (JITL), an industrial soft sensor modeling technique that utilizes Raman signals to estimate process variables promptly. The conventional Raman‐based JITL method relies on the K‐nearest neighbor (KNN) algorithm with Euclidean distance as the similarity measure. However, it falls short of addressing the impact of data uncertainties. To rectify this limitation, this study endeavors to integrate JITL with a variational autoencoder (VAE). This integration aims to extract dominant Raman features in a nonlinear fashion, which are expressed as multivariate Gaussian distributions. Three experimental runs using different cell lines were chosen to compare the performance of the proposed algorithm with commonly utilized methods in the literature. The findings indicate that the VAE–JITL approach consistently outperforms partial least squares, convolutional neural network, and JITL with KNN similarity measure in accurately predicting key process variables.
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Chlamydia psittaci is an avian bacterial pathogen that can cause atypical pneumonia in humans via zoonotic transmission. It is a Gram-negative intracellular bacterium that proliferates inside membrane bound inclusions in the cytoplasm of living eukaryotic cells. The study of such cells with C. psittaci inside without destroying them poses a significant challenge. We demonstrated in this work the utility of a combined multitool approach to analyze such complex samples. Atomic force microscopy was applied to obtain high-resolution images of the surface of infected cells upon entrance of bacteria. Atomic force microscopy scans revealed the morphological changes of the cell membrane of Chlamydia infected cells such as changes in roughness of cell membrane and the presence of micro vesicles. 4Pi Raman microscopy was used to image and probe the molecular composition of intracellular bacteria inside intact cells. Information about the structure of the inclusion produced by C. psittaci was obtained and it was found to have a similar molecular fingerprint as that of an intracellular lipid droplet but with less proteins and unsaturated lipids. The presented approach demonstrates complementarity of various microscopy-based approaches and might be useful for characterization of intracellular bacteria.
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Here, Raman spectroscopy is used to develop a univariate partial least squares (PLS) calibration capable of quantifying geochemistry in synthetic and natural silicate glass samples. The calibration yields eight oxide-specific models that allow predictions of silicon dioxide (SiO 2 ), sodium oxide (Na 2 O), potassium oxide (K 2 O), calcium oxide (CaO), titanium dioxide (TiO 2 ), aluminum oxide (Al 2 O 3 ), ferrous oxide (FeO T ), and magnesium oxide (MgO) (wt%) in glasses spanning a wide range of compositions, while also providing correlation-coefficient matrices that highlight the importance of specific Raman channels in the regression of a particular oxide. The PLS suite is trained on 48 of the 69 total glasses, and tested against 21 validation samples (i.e., held out of training). Trends in root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), and root mean square error of prediction (RMSEP) model accuracy metrics are investigated to uncover the efficacy of utilizing multivariate analysis for such Raman data and are contextualized against recently produced strategies. The technique yields an average root mean of calibration (∼2.4 wt%), cross-validation (∼ 2.9 wt%), prediction (∼ 2.6 wt%), and normalized variance (∼ 28%). Raman band positional shifts are also mapped against underlying chemical variations; with major influences arising primarily as a function of overall oxidation state and silica concentration: via ferric cation (Fe ³⁺ )/ferrous cation (Fe ²⁺ ) ratios and SiO 2 (wt%). The algorithm is further validated preliminarily against a separate external set of 11 natural basaltic glasses to unravel the limitations of the synthetic models on natural samples, and to determine the suitability of “universal” Raman-model applications in scenarios where prior chemical contextualization of the target sample is possible. This study represents the first time Raman spectra of amorphous silicates have been paired with PLS, offering a foundation for future improvements utilizing these systems.
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One of the driving factors leading to the modernization in the agriculture sector is the era of sensors-driven technologies. Annually, as reported by the Associated Chambers of Commerce and Industry of India, $500 billion of crops are lost due to pests and plant diseases in a country like India, where at least 200 million Indians go to bed hungry every night. For the detection of plant disease, the measurement of leaf wetness duration (LWD) values becomes a crucial step. This requirement of measuring LWD values led to the development of an in situ IoT-enabled LW sensor earlier. The same LW sensor was deployed for about four months, and data for the same were collected. Furthermore, for extracting LWD information, smoothing algorithms like total variation denoising (TVD) are applied. However, our novelty lies in introducing the order of fractional derivative (α) in an already existing TVD algorithm, which is varied from 1 to 2, and results are found to be satisfying. To get an effective baseline, we combined this algorithm with three baseline correction techniques: asymmetric least squares, improved asymmetric least squares, and asymmetrically reweighted penalized least squares (arPLS). The optimal range of α lies in the range of 1.6 to 2 for getting the highest accuracy. This study demonstrates that our novel approach of integrating fractional derivatives into an existing TVD algorithm enhances its performance in identifying Leaf wetness events. The highest accuracy (i.e., the highest number of events detected) of 0.80 is found by total variation smoothing with the arPLS baseline correction technique.
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In this paper, the problem of estimating the background of a spectrum is addressed. We propose to fit this background to a low-order polynomial, but rather than determining the polynomial parameters that minimise a least-squares criterion (i.e. a quadratic cost function), non-quadratic cost functions well adapted to the problem are proposed. To minimise these cost functions, we use the half-quadratic minimisation. It yields a fast and simple method, which can be applied to a wide range of spectroscopic signal. Guidelines for the choice of the design parameters are given and illustrated on simulated spectra. Finally, the effectiveness of the method is shown by processing experimental infrared and Raman spectra.
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A technique entitled robust baseline estimation is introduced, which uses techniques of robust local regression to estimate baselines in spectra that consist of sharp features superimposed upon a continuous, slowly varying baseline. The technique is applied to synthetic spectra, to evaluate its capabilities, and to laser-induced fluorescence spectra of OH (produced from the reaction of ozone with hydrogen atoms). The latter example is a particularly challenging case for baseline estimation because the experimental noise varies as a function of frequency.
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To increase the power and the robustness of spectroscopic process analyzers, methods are needed that suppress the spectral variation that is not related to the property of interest in the process stream. An approach for the selection of a suitable method is presented. The approach uses the net analyte signal (NAS) to analyze the situation and to select methods to suppress the nonrelevant spectral variation. The empirically determined signal-to-noise of the NAS is used as a figure of merit. The advantages of the approach are (i). that the error of the reference method does not affect method selection and (ii). that only a few spectral measurements are needed. A diagnostic plot is proposed that guides the user in the evaluation of the particular suppression method. As an example, NIR spectroscopic monitoring of a mol-sieve separation process is used.
  • H F M Boelens
  • P H C Eilers
Boelens, H.F.M. ; Eilers, P.H.C. ; Hankemeier Th. Anal. Chem. 2005, (in press)
  • A Jirasek
  • G Schulze
  • M M L Yu
  • M W Blades
  • R F B Turner
Jirasek, A. ; Schulze G. ; Yu, M.M.L. ; Blades, M.W. ; Turner, R.F.B. Appl. Spectrosc. 2004, 58, 1488-1499
  • M Mazet
  • C Carteret
  • D Brie
  • J Idier
  • B Humbert
Mazet, M. ; Carteret, C. ; Brie, D. ; Idier, J. ; Humbert, B. Chemom. Intell. Lab. Syst. 2005, 76, 121-133
  • D A Mcnulty
  • H J H Macfie
McNulty, D.A. ; MacFie, H.J.H. J. of Chemom. 1997, 11, 1-11
  • P H C Eilers
  • R X De Menezes
Eilers, P.H.C. ; de Menezes, R.X. Bioinformatics, 2005, 21, 1146-1153
  • M A Knee
  • H J Annegarn
Knee, M.A. and Annegarn H.J. Nucl. Instrum. Methods Phys. Rese. Sect. B, 1996, 109, 201-213
  • A J Phillips
  • P Hamilton
Phillips A.J. ; Hamilton P.A Anal. Chem. 1996, 68, 4020-4025
  • B Bogaert
  • H F M Boelens
  • H C Smit
Bogaert, B. ; Boelens, H.F.M. ; Smit, H.C. Anal. Chim. Acta 1993, 274, 71-85
  • P H C Eilers
Eilers, P.H.C. Anal. Chem. 2004, 76, 404-411
  • V P Andreev
  • T Rejtar
  • H Chen
  • E V Mosovets
  • A R Ivanov
  • B L Karger
Andreev, V.P. ; Rejtar, T. ; Chen, H. ; Mosovets, E.V. ; Ivanov A.R. ; Karger B.L. Anal. Chem. 2003, 75, 6314-6326
  • P H C Eilers
Eilers, P.H.C. Anal. Chem. 2003, 75, 3631-3636