Causal Artificial Intelligence Models of Food Quality Data.

Research Background: The aim of this study is to emphasize the importance of artificial intelligence (AI) and causality modelling of food quality and analysis with 'big data'. AI with structural causal modelling (SCM), based on Bayesian networks and deep learning, enables the integration of theoretical field knowledge in food technology with process production, physicochemical analytics and consumer organoleptic assessments. Food products have complex nature and data are highly dimensional, with intricate interrelations (correlations) that are difficult to relate to consumer sensory perception of food quality.

Application of Causality Modelling for Prediction of Molecular Properties for Textile Dyes Degradation by LPMO.

The textile industry is one of the largest water-polluting industries in the world. Due to an increased application of chromophores and a more frequent presence in wastewaters, the need for an ecologically favorable dye degradation process emerged. To predict the decolorization rate of textile dyes with Lytic polysaccharide monooxygenase (LPMO), we developed, validated, and utilized the molecular descriptor structural causality model (SCM) based on the decision tree algorithm (DTM).

New approach to the evaluation of lignocellulose derived by-products impact on lytic-polysaccharide monooxygenase activity by using molecular descriptor structural causality model.

Lytic-polysaccharide monooxygenase (LPMO) is one of the most important enzyme involved in biocatalytic lignocellulose degradation, and therefore inhibition of LPMO has significant effects on all related processes. Structural causality model (SCM) were established to evaluate impact of phenolic by-products in lignocellulose hydrolysates on LPMO activity. The molecular descriptors GATS4c, ATS2m, BIC3 and VR2_Dzs were found to be significant in describing inhibition.

Current state and prospects of biotechnology in Central and Eastern European countries. Part II: new and preaccession EU countries(CRO, RO, B&H, SRB).

Innovation holds the potential for economic prosperity. Biotechnology (BT) has proved to be a viable vehicle for the development and utilization of technologies, which has brought not only advances to society, but also career opportunities to nation-states that have enabling conditions. In this review, we assess the current state of BT-related activities within selected new and preaccession EU countries (NPA) of CEE region namely Croatia, Romania, Bosnia and Herzegovina and Serbia, examining educational programs, research activity, enterprises, and the financing systems.

Near-Infrared Spectroscopic Analysis of Total Phenolic Content and Antioxidant Activity of Berry Fruits.

This study evaluates the feasibility of using near-infrared (NIR) spectroscopy as a rapid and environmentally friendly technique for validation and prediction of the total phenolic content (TPC) and antioxidant activity (AOA) indices (as 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, inhibition time (IT) of the Briggs-Rauscher oscillating reaction, and relative antioxidant capacity (RAC)) of berry fruit extracts. The analysed berry samples originated from Croatia (blackberries, wild blueberries, raspberries, red currants and strawberries) and Bulgaria (wild blueberries, raspberries and strawberries). Principal component analysis and partial least squares (PLS) regression were used from the set of chemometric tools in distinguishing and validating the measured berry fruit extract.

Reliability of a decision-tree model in predicting occupational lead poisoning in a group of highly exposed workers.

Objective: This study aimed to provide the toxicological profile of some lead-exposed workers and obtain a predictive model for lead poisoning.

Methods: Data regarding external and absorbed exposure were collected from 585 subjects employed in ten metallurgical production departments. Airborne lead concentration, blood lead level (BLL), cumulative blood lead index (CBLI), urine delta-aminolevulinic acid (DALA), age, workplace/section, exposure period, and whether reported lead poisoning as occupational disease were examined using ANOVA, and, post-ANOVA, Pearson correlation matrix, PCA (principal component analysis), decision-tree modeling, and logistic modeling.

Catabolism of terbuthylazine by mixed bacterial culture originating from s-triazine-contaminated soil.

The s-triazine herbicide terbuthylazine (TERB) has been used as the main substitute of atrazine in many EU countries for more than 10 years. However, the ecological consequences of this substitution are still not fully understood. Since the fate of triazine herbicides is primarily dependent on microbial degradation, in this paper, we investigated the ability of a mixed bacterial culture, M3-T, originating from s-triazine-contaminated soil, to degrade TERB in liquid culture and soil microcosms.

Effect of different variables on the efficiency of the Baker's yeast cell disruption process to obtain alcohol dehydrogenase activity.

Cell disruption process of dry baker's yeast was studied in this work to obtain maximum activity of alcohol dehydrogenase (ADH). Disruption by ultrasonication, glass beads, and combination of these two methods was compared. A 1.

Lin-log Model of E. coli Central Metabolism.

Mathematical models of dynamics of metabolic pathways are used for analysis of complex regulations of biochemical reactions as an intrinsic property of a metabolism. The models are derived under assumptions of kinetic rate functions and usually result in simplification in view of the model theoretical scope and/or its practical application. The main obstacle in kinetic modeling is the dimensionality of the parametric space, its nonlinearity and ill-conditioned relations for kinetic parameter estimation.

Principal component ANN for modelling and control of baker's yeast production.

Modelling of baker's yeast production by the principal component based artificial neural networks (ANN) is presented. The models are derived for their application in adaptive control of fermentation by the internal model control (IMC) method. Modelling data are from industrial production in 40 m3 deep jet bioreactor and from computer simulations.

Optimal nonsingular control of fed-batch fermentation.

Presented is a new simple method for multidimensional optimization of fed-batch fermentations based on the use of the orthogonal collocation technique. Considered is the problem of determination of optimal programs for fermentor temperature, substrate concentration in feed, feeding profile, and process duration. By reformulation of the state and control variables is obtained a nonsingular form of the optimization problem which has considerable advantage over the singular case since a complicated procedure for determination of switching times for feeding is avoided.