Mutual factor analysis for quantitative analysis by temperature dependent near infrared spectra

Aquaphotomics—Exploring Water Molecular Systems in Nature

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Water as a Probe for Standardization of Near-Infrared Spectra by Mutual-Individual Factor Analysis

The standardization of near-infrared (NIR) spectra is essential in practical applications, because various instruments are generally employed. However, standardization is challenging due to numerous perturbations, such as the instruments, testing environments, and sample compositions. In order to explain the spectral changes caused by the various perturbations, a two-step standardization technique was presented in this work called mutual–individual factor analysis (MIFA). Taking advantage of the sensitivity of a water probe to perturbations, the spectral information from a water spectral region was gradually divided into mutual and individual parts. With aquaphotomics expertise, it can be found that the mutual part described the overall spectral features among instruments, whereas the individual part depicted the difference of component structural changes in the sample caused by operation and the measurement conditions. Furthermore, the spectral difference was adjusted by the coefficients in both parts. The effectiveness of the method was assessed by using two NIR datasets of corn and wheat, respectively. The results showed that the standardized spectra can be successfully predicted by using the partial least squares (PLS) models developed with the spectra from the reference instrument. Consequently, the MIFA offers a viable solution to standardize the spectra obtained from several instruments when measurements are affected by multiple factors.

Revealing the interactions of water with cryoprotectant and protein by near-infrared spectroscopy

Taking formamide (FA) as a model compound of protein, the water structure in the ternary mixtures of dimethyl sulfoxide (DMSO)-water-FA was studied by near-infrared (NIR) spectroscopy. The interaction of DMSO and water, and the effect of FA on the interaction, were analyzed with the help of chemometric methods. Continuous wavelet transform (CWT) was used to enhance the resolution of the spectra. A peak at 6437 cm^-1 depicting the interaction of DMSO and water through hydrogen bonding (SO…HO) was observed in the transformed spectra. When FA exists in the mixture, the intensity of the peak decreases with the increase of formamide content, showing that FA may replace the water to form the hydrogen bond of SO and HN. In addition, temperature-dependent NIR spectroscopy was used to analyze the effect of the three components on the spectral variation with temperature. Analyzing the spectral data by alternating trilinear decomposition (ATLD) and multiple linear regression, two varying spectral features were obtained that are related to water and DMSO, but no spectral feature was found that significantly varies with the content of FA. The result implies that DMSO is still the key component to prevent the water from icing, although FA may reduce slightly the anti-freezing effect.

Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy

Temperature-dependent near-infrared (NIR) spectroscopy has been developed and taken as a powerful technique for analyzing the structure of water and the interactions in aqueous systems. Due to the overlapping of the peaks in NIR spectra, it is difficult to obtain the spectral features showing the structures and interactions. Chemometrics, therefore, is adopted to improve the spectral resolution and extract spectral information from the temperature-dependent NIR spectra for structural and quantitative analysis. In this review, works on chemometric studies for analyzing temperature-dependent NIR spectra were summarized. The temperature-induced spectral features of water structures can be extracted from the spectra with the help of chemometrics. Using the spectral variation of water with the temperature, the structural changes of small molecules, proteins, thermo-responsive polymers, and their interactions with water in aqueous solutions can be demonstrated. Furthermore, quantitative models between the spectra and the temperature or concentration can be established using the spectral variations of water and applied to determine the compositions in aqueous mixtures.

Aquaphotomics Reveals Subtle Differences between Natural Mineral, Processed and Aged Water Using Temperature Perturbation Near-Infrared Spectroscopy

Current approaches to the quality control of water are unsatisfying due to either a high cost or the inability to capture all of the relevant information. In this study, near-infrared spectroscopy (NIRS) with aquaphotomics as a novel approach was assessed for the discrimination of natural, processed and aged water samples. Temperature perturbation of water samples was employed to probe the aqueous systems and reveal the hidden information. A radar chart named an aquagram was used to visualize and compare the absorbance spectral patterns of waters at different temperatures. For the spectra acquired at a constant temperature of 30 °C, the discrimination analysis of different water samples failed to produce satisfying results. However, under perturbation by increasing the temperature from 35 to 60 °C, the absorbance spectral pattern of different waters displayed in aquagrams revealed different, water-specific dynamics. Moreover, it was found that aged processed water changed with the temperature, whereas the same processed water, when freshly prepared, had hydrogen bonded structures unperturbed by temperature. In summary, the aquaphotomics approach to the NIRS analysis showed that the water absorbance spectral pattern can be used to describe the character and monitor dynamics of each water sample as a complex molecular system, whose behavior under temperature perturbation can reveal even subtle changes, such as aging and the loss of certain qualities during storage.

Water Spectral Patterns Reveals Similarities and Differences in Rice Germination and Induced Degenerated Callus Development

In vivo monitoring of rice (Oryza sativa L.) seed germination and seedling growth under general conditions in closed Petri dishes containing agar base medium at room temperature (temperature = 24.5 ± 1 °C, relative humidity = 76 ± 7% (average ± standard deviation)), and induced degenerated callus formation with plant growth regulator, were performed using short-wavelength near-infrared spectroscopy and aquaphotomics over A period of 26 days. The results of spectral analysis suggest changes in water absorbances due to the production of common metabolites, as well as increases in biomass and the sizes of the samples. Quantitative models built to predict the day of the development provided better accuracy for rice seedlings growth compared to callus formation. Eight common water bands were identified as presenting prominent changes in the absorbance pattern. The water matrix of only rice seedlings showed three developmental stages: firstly expressing a predominantly weakly hydrogen-bonded state, then a more strongly hydrogen-bonded state, and then, again, a weakly hydrogen-bonded state at the end. In rice callus induction and proliferation, no similar change in water absorbance pattern was observed. The presented findings indicate the potential of aquaphotomics for the in vivo detection of degeneration in cell development.

Early Diagnosis of Type 2 Diabetes Based on Near-Infrared Spectroscopy Combined With Machine Learning and Aquaphotomics

Early diagnosis is important to reduce the incidence and mortality rate of diabetes. The feasibility of early diagnosis of diabetes was studied via near-infrared spectra (NIRS) combined with a support vector machine (SVM) and aquaphotomics. Firstly, the NIRS of entire blood samples from the population of healthy, pre-diabetic, and diabetic patients were obtained. The spectral data of the entire spectra in the visible and near-infrared region (400–2,500 nm) were used as the research object of the qualitative analysis. Secondly, several preprocessing steps including multiple scattering correction, variable standardization, and first derivative and second derivative steps were performed and the best pretreatment method was selected. Finally, for the early diagnosis of diabetes, models were established using SVM. The first overtone of water (1,300–1,600 nm) was used as the research object for an aquaphotomics model, and the aquagram of the healthy group, pre-diabetes, and diabetes groups were drawn using 12 water absorption patterns for the early diagnosis of diabetes. The results of SVM showed that the highest accuracy was 97.22% and the specificity and sensitivity were 95.65 and 100%, respectively when the pretreatment method of the first derivative was used, and the best model parameters were c = 18.76 and g = 0.008583.The results of the aquaphotomics model showed clear differences in the 1,400–1,500 nm region, and the number of hydrogen bonds in water species (1,408, 1,416, 1,462, and 1,522 nm) was evidently correlated with the occurrence and development of diabetes. The number of hydrogen bonds was the smallest in the healthy group and the largest in the diabetes group. The suggested reason is that the water matrix of blood changes with the worsening of blood glucose metabolic dysfunction. The number of hydrogen bonds could be used as biomarkers for the early diagnosis of diabetes. The result show that it is effective and feasible to establish an accurate and rapid early diagnosis model of diabetes via NIRS combined with SVM and aquaphotomics.

Multilevel LASSO-based NIR temperature-correction modeling for viscosity measurement of bisphenol-A

Temperature variation will affect the prediction accuracy when using the near-infrared (NIR) analytical model to measure the viscosity of bisphenol-A. In order to correct the effect of temperature on the prediction performance of NIR model, a multilevel least-absolute shrinkage and selection operator (LASSO) is proposed in this paper. The multilevel LASSO algorithm combines LASSO with the multilevel simultaneous component analysis (MLSCA) to enhance the robustness of the model under temperature changes and external disturbances. MLSCA is applied to decompose the molecular spectral data into two parts. One part denotes the property caused by temperature, the other means the changes of concentration. LASSO, a sparse regression model, is used to select the variables and perform the regularization to further enhance the robustness and interpretability of the model. Experimental results demonstrate the effectiveness of the proposed model in measuring bisphenol-A viscosity, which provides a more stable prediction result compared with the existing ones without temperature corrections.

Three-level simultaneous component analysis for analyzing the near-infrared spectra of aqueous solutions under multiple perturbations

Quantitative analysis under various perturbations is a difficult problem because the analytical signal changes with different factors. In this work, three-level simultaneous component analysis (3-MSCA) was used for analyzing the near-infrared (NIR) spectra of aqueous solutions under different perturbations. The spectral data of aqueous proline solutions at different pH, concentration and temperature were measured, and a three-level model was built to describe the effects of the three perturbations on the spectra, respectively. The first level model describes the change of the spectra with pH, from which significant aggregation of proline was observed around the isoelectric point. The second and third level model show the spectral change with concentration and temperature, respectively, and the spectral feature has a very good linear relationship with the corresponding influencing factors. Therefore, the pH and concentration scores can be used as the calibration curve for quantitative analysis of the pH and the content of proline, and the temperature scores can be used to predict the temperature of the solutions. In addition, the structural change of water molecules under different conditions is obtained from the loadings. A decline of the bulk water was found with the increase of concentration, implying an ascending trend of the bonded water due to the interaction of proline and water. The dissociation of water clusters with the increase of temperature is also displayed.

Interaction between tau and water during the induced aggregation revealed by near-infrared spectroscopy

Near-infrared (NIR) spectra are sensitive to the variation of water structure. In this work, NIR spectroscopy was used to investigate the variation of hydration water during the aggregation of R2/wt induced by heparin. The osmolytes, urea and trehalose, were used to slow down and speed up the aggregation. The spectra of R2/wt aqueous solution obtained by NIR spectroscopy at 37 °C were adopted to analyze the structure of water during the aggregation. The spectral features of different water species were observed by principal component analysis (PCA) from the resolution enhanced NIR spectra. The existence of the water molecules with one and two hydrogen bonds around the NH and CH groups of R2/wt, respectively, was suggested, and the variation of the hydrogen-bonded water was found to be an indicator to monitor the process of aggregation. Then, the variation of the water species during the aggregation was analyzed by two-dimensional correlation spectroscopy. The water hydrogen bonded with NH group was found to change earlier than the water around the hydrophobic groups. The results suggest that β-sheet forms though the hydrogen bonds of amide groups in the early stage of the aggregation, and the destruction of the hydrogen bond network of the water around the side chains maybe the main reason for the formation of the ordered amyloid fibers.

Aquaphotomics-From Innovative Knowledge to Integrative Platform in Science and Technology

Aquaphotomics is a young scientific discipline based on innovative knowledge of water molecular network, which as an intrinsic part of every aqueous system is being shaped by all of its components and the properties of the environment. With a high capacity for hydrogen bonding, water molecules are extremely sensitive to any changes the system undergoes. In highly aqueous systems-especially biological-water is the most abundant molecule. Minute changes in system elements or surroundings affect multitude of water molecules, causing rearrangements of water molecular network. Using light of various frequencies as a probe, the specifics of water structure can be extracted from the water spectrum, indirectly providing information about all the internal and external elements influencing the system. The water spectral pattern hence becomes an integrative descriptor of the system state. Aquaphotomics and the new knowledge of water originated from the field of near infrared spectroscopy. This technique resulted in significant findings about water structure-function relationships in various systems contributing to a better understanding of basic life phenomena. From this foundation, aquaphotomics started integration with other disciplines into systematized science from which a variety of applications ensued. This review will present the basics of this emerging science and its technological potential.

Water as a probe for serum-based diagnosis by temperature- dependent near-infrared spectroscopy

Diagnosis based on the compositional variation of biological liquids such as serum has drawn much attention. For exploring the potential diagnostic information from serum samples, temperature-dependent near-infrared (NIR) spectroscopy was developed to obtain the spectral change of water reflecting the interactions in serum solution, and chemometric methods were employed to mine the information from the temperature-dependent NIR spectra. The spectra of 68 healthy controls, 42 patients with the type II diabetes and 16 patients with coronary heart disease were measured and analyzed by chemometric calculations. Continuous wavelet transform (CWT) was used to enhance the resolution of the spectra. From the processed spectra, the information of non-hydrogen-bonded (NHB), weakly hydrogen-bonded (WHB) and strongly hydrogen-bonded (SHB) water species was observed. For explaining the variation of the spectra with temperature, two-dimensional (2D) correlation analysis was adopted. A clear difference in SHB/NHB ratio in the synchronous maps was found between the spectra of the patients and the controls. 86.8% of the controls and 98.3% of the patients can be correctly identified. Furthermore, combining the maps of the synchronous and asynchronous analysis, the correlation between SHB and WHB water species was discovered to have an ability to discriminate the patients of diabetes and heart disease with an accuracy of 83.7% and 75.0%, respectively. Therefore, water may be a probe for providing diagnostic information by temperature-dependent NIR spectroscopy.

High order derivative to investigate the complexity of the near infrared spectra of aqueous solutions

Derivative calculation is a powerful method for resolution enhancement in spectral analysis. A high order derivative method based on continuous wavelet transform (CWT) is discussed in the analysis of near infrared (NIR) spectra. The results for a simulated spectrum obtained from conventional numerical differentiation (NM), Fourier transform (FT), Savitzky-Golay (SG) and CWT method were compared. CWT method was found to be as efficient as FT and SG, but easier for high order derivative computation, and the fourth order derivative was proved to be a good choice for resolution enhancement as well as reduction of noise and sidelobe effects. For the NIR spectra of water-ethanol mixtures, the complexity of the spectra can be observed from the fourth derivative, including the spectral features of OH and CH with various intermolecular interactions. Fitting the derivative spectra of the mixtures by those of pure water and ethanol, the obtained coefficients for ethanol show a linear relation with the content but that for water exhibit a non-linear relation, which reveals the influence of ethanol on water structure in the mixture. Furthermore, the information of the water-ethanol clusters was found in the residual spectra after the fitting. Therefore, high order derivative can be an efficient way to improve the resolution of NIR spectra for understanding the interactions in aqueous solutions.

Essentials of Aquaphotomics and Its Chemometrics Approaches

Aquaphotomics is a novel scientific discipline involving the study of water and aqueous systems. Using light-water interaction, it aims to extract information about the structure of water, composed of many different water molecular conformations using their absorbance bands. In aquaphotomics analysis, specific water structures (presented as water absorbance patterns) are related to their resulting functions in the aqueous systems studied, thereby building an aquaphotome-a database of water absorbance bands and patterns correlating specific water structures to their specific functions. Light-water interaction spectroscopic methods produce complex multidimensional spectral data, which require data processing and analysis to extract hidden information about the structure of water presented by its absorbance bands. The process of extracting information from water spectra in aquaphotomics requires a field-specific approach. It starts with an appropriate experimental design and execution to ensure high-quality spectral signals, followed by a multitude of spectral analysis, preprocessing and chemometrics methods to remove unwanted influences and extract water absorbance spectral pattern related to the perturbation of interest through the identification of activated water absorbance bands found among the common, consistently repeating and highly influential variables in all analytical models. The objective of this paper is to introduce the field of aquaphotomics and describe aquaphotomics multivariate analysis methodology developed during the last decade. Through a worked-out example of analysis of potassium chloride solutions supported by similar approaches from the existing aquaphotomics literature, the provided instruction should give enough information about aquaphotomics analysis i.e. to design and perform the experiment and data analysis as well as to represent water absorbance spectral pattern using various forms of aquagrams-specifically designed aquaphotomics graphs. The explained methodology is derived from analysis of near infrared spectral data of aqueous systems and will offer a useful and new tool for extracting data from informationally rich water spectra in any region. It is the hope of the authors that with this new tool at the disposal of scientists and chemometricians, pharmaceutical and biomedical spectroscopy will substantially progress beyond its state-of-the-art applications.

The Value of Public Sector Risk Management: An Empirical Assessment of Ghana

This study investigates risk management practices in public entities in the Ghana. We relied on the popular framework designed by the Committee of Sponsoring Organizations of the Treadway Commission—COSO, to advocate for possible ways to minimize the occurrence and effects of risk in public organizations. The internal control elements used include: control environment, commitment to ethics, segregation of duties, review and information and communication. These constitute the explanatory variables used in performing multivariate data analysis to determine the dimensionality of the data set and possible outcomes. The exploratory research followed a quantitative approach using the survey method and a structured equation model. We established that, due to globalization and increases in the scale of operations, it is practically impossible for management through the help of auditors and those in charge of governance to validate the entire operations of the public sector to ensure strict compliance to internal control principles, in order to minimize the detrimental impacts of risk. However, an alternative sustainability depends on the prominence of quality financial reporting, compliance, commitment to ethical values and consistency in pursuit of the strategic and operational objectives based on good corporate governance. On the other hand, the implications of risks should be embedded in the minds of public servants as part of the organizational culture that will complement existing tools and techniques of internal control.