The present invention relates to the use of Raman spectroscopy for the monitoring and assessment of viral titre.

An etalon-based mid-infrared probe can be configured for spectroscopic tissue discrimination, such as between non-normal (e.g., cancerous) and normal (e.g., healthy) tissue. A broadband light source can be applied to the etalon to generate fringes at spectroscopic wavelengths of interest, which can be delivered to a tissue specimen via a fiber loop probe. A response signal can be spectral dispersed across a parallel array of detector pixels, such as using a diffraction grating, and signal processed for performing the tissue classification. A learning model can be trained, using full IR spectral data, for applying a reduced set of wavelengths for performing the spectroscopic tissue analysis and classification.

This disclosure relates to methods of characterizing a urine sample from a subject.

An analyzer that analyzes a measurement sample on the basis of spectrum data obtained by irradiating the measurement sample with light and includes a total analysis value calculation part that, on the basis of the total analysis value of a reference sample of which the total analysis value of multiple predetermined components are preliminarily obtained, calculates the total analysis value of the multiple components in the measurement sample from the spectrum data of the measurement sample.

Performing multivariate spectral analysis to determine relationships between chemical species in a sample, includes: providing intensity measurement data as plural measured spectra from the sample, each spectrum having unique identifier and intensity values for bins of a binned spectral range; expressing the intensity measurement data as an m×n matrix V, m and n respectively represents number of bins of the spectral range and number of unique identifiers; performing non-negative factorisation of the matrix V to obtain an m×p derived spectra matrix W and a p×n spectral weightings matrix H minimizing an error function |V−WH|, p representing a number of derived spectra and is selected such that the non-negative factorisation over-fits WH to V; identifying correlations between the p derived spectra of the derived spectra matrix W which explain variance in the intensity measurement data; and determining chemical relationships between chemical species in the sample.

A spectroscopic analysis apparatus, a spectroscopic analysis method, and a program capable of appropriately analyzing a sample are provided. The spectroscopic analysis apparatus according to an embodiment includes: a light source (13) generates light to be incident on a sample including a plurality of substances labeled by a plurality of labeled substances; a spectrometer (14) disperse observed light generated in the sample by the light incident on the sample; a detector (15) detects the observed light dispersed by the spectrometer (14) to output observed spectral data; and a processor (16) analyzes the plurality of substances included in the sample based on the observed spectral data output from the detector (15), the processor (16) analyzing the substances included in the sample using a generalized inverse of a matrix having, as elements, reference spectral data set for the plurality of labeled substances and data of a noise component.

A method of determining components present in a sample from spectral data obtained from the sample including resolving each of a plurality of models of the spectral data, the plurality of models including models having a different number of component reference spectra selected from a set of predetermined component reference spectra; selecting a one of the plurality of models based upon a model selection criterion and determining one or more components present in the sample based upon the selected model. The model selection criterion includes a measure for each model, which balances improvements in fit quality of the model to the spectral data against a complexity penalty determined from the number of component reference spectrum used in the model.

Systems and methods for implicit chemical resolution of vacuum gas oils and fit quality determination are disclosed. The systems and methods include utilizing an FT-IR spectrum of an unknown VGO composition, and a database of FT-IR spectra of known VGO compositions, to determine a model of composition for the unknown VGO composition. Additionally, the fit quality for the model of composition is determined by performing a partial least squares analysis on specific spectral regions of interest in the FT-IR spectrum of the unknown VGO composition.

The invention relates to the detection, assessment and mitigation of harmful water-borne bacteria such as cyanobacteria. Multiple apparatus embodiments and variations are described. One apparatus can apply at least one of UV-C irradiation, microbubbles containing ozone and ultrasonic sound to mitigate the harmful water-borne bacteria. The systems and methods of the invention can be applied to bodies of water, including fresh water and salt water, and can be applied to wastewater treatment. The systems and methods of the invention can be used to reduce the concentration of algae directly and can be used to reduce the concentration of nutrients in water that algae use to grow. Methods of mitigation of the harmful bacteria are described that do not involve the introduction of chemicals into the environment.

The invention relates to the detection, assessment and mitigation of harmful water-borne bacteria such as cyanobacteria. Multiple apparatus embodiments and variations are described. One apparatus can apply at least one of UV-C irradiation, microbubbles containing ozone and ultrasonic sound to mitigate the harmful water-borne bacteria. The systems and methods of the invention can be applied to bodies of water, including fresh water and salt water, and can be applied to wastewater treatment. The systems and methods of the invention can be used to reduce the concentration of algae directly and can be used to reduce the concentration of nutrients in water that algae use to grow. Methods of mitigation of the harmful bacteria are described that do not involve the introduction of chemicals into the environment.