Feasible band boundaries computation in bilinear matrix decomposition using essential data.

Background: Multivariate curve resolution methods are usually confronted with non-unique pure component factors. This rotational ambiguity can be represented by ranges of feasible profiles, which are equally compatible with the imposed constraints. Sensor-wise N-BANDS is an effective algorithm for the calculation of the bounds of feasible profiles in the presence of noise, but suffers from high computational cost.

Novel Data Fusion Strategy for Second-Order Data: Multivariate Curve Resolution for the Determination of Pharmaceuticals by Means of Fluorimetric Measurements.

A new strategy is proposed for second-order data fusion based on the simultaneous modeling of two data sets using the multivariate curve resolution-alternating least-squares (MCR-ALS) model, applying a new constraint during the ALS stage, called "Proportionality of Scores". This approach allows for the fusion of data from different sources, without requiring common dimensionality, and enables the application of specific constraints to each data set. This strategy was applied to the determination of five pharmaceutical contaminants (naproxen, danofloxacin, ofloxacin, sarafloxacin, and enoxacin) in environmental water samples, by fusing two sets of excitation-emission fluorescence matrices, measured before and after photochemical derivatization.

Assessing the basis for regulatory crediting of virus LRVs for secondary biological wastewater treatment: A systematic review.

Regulatory frameworks for potable reuse often include stringent log reduction value (LRV) targets to ensure public health protection against exposure to viruses and protozoa. To achieve overall LRV targets and reduce associated capital and operational costs, it is important to maximize LRV credits awarded to each unit process in a potable reuse treatment train. This may include processes that are historically uncredited or undercredited, such as secondary biological wastewater treatment incorporating activated sludge and secondary clarification.

Cement classification and characterization using Non-Invasive techniques.

Cement is one of the most widely used materials in the global construction industry, serving as an adhesive and binder in projects that require strength and durability. Additionally, cement production indicates a country's development and economic activity, with global production reaching approximately 4 billion tons annually. It is a fine powder composed mainly of lime, silica, iron oxide, and alumina.