Fault detection in multi-rate process systems is a challenging task. To make such process plant available till the next shutdown it is essential to detect faults and take corrective measures before they lead to failure. Common techniques used for fault detection of multi-rate systems include threshold-based detectors, statistical detectors, and machine learning-based detectors, one such statistical detector technique is Multiple Probabilistic Principal Component Analysis (MPPCA). MPPCA uses probabilistic PCA to detect fault signals from multiple sensors without down-sampling or up-sampling It considers the inter-dependencies among the sensors and helps in detecting and diagnosing faults in a timely and accurate manner, in this work MPPCA is applied for fault detection of Two-Phase Reactor-Condenser system with Recycle (TPRCR) in which three different classes of measurement are considered. Temperature and pressure measurement are considered as fast rate measurements, Liquid holdups are considered as medium rate and mole fractions are available at slower rates. This measurement data is used for development of MPPCA model using Expectation-Maximization (EM) algorithm. Based on this T² and SPE statistics are developed which are used for Fault-detection in TPRCR system and efficacy of MPPCA method is found to be satisfactory.

Biopolymer-based edible films and coatings are vital in making the global food-packaging industry more sustainable. These films/coatings protect and extend the shelf life of food by acting as barriers to moisture, oxygen, microorganisms, and Ultra Violet light. Polysaccharides, due to abundant availability from natural plant-based resources and the tendency to form a gel in water, are excellent low-cost choices for packaging films. Additives such as hydrophobic agents, plasticizers, binders, and antimicrobial agents will improve the properties of films and coatings. The present work aims to develop pectin-based packaging film (from 5% w/v film forming solution) by adding castor oil as a hydrophobic agent, beeswax as a plasticizer, and Clove oil as an antimicrobial agent. Films were developed by using 2³ (two-level three-factor) statistical factorial design of experiments. The amount of castor oil (5% & 15%), beeswax (5% & 10%) and clove oil (2% and 4%) are taken as the three factors. The developed films were analyzed for physical, moisture barrier, morphological, thermal, tensile properties and resistance to microbial growth. The results indicated that clove is a good antimicrobial agent. Further, bees wax greatly changed by enhancing the anti-microbial activity, elongation, and moisture barrier properties. Castor oil integration remarkably lowered the moisture and oxygen transmission rates relative to pure pectin films and some other additives reported in the literature. The optimized biofilms had a thickness of ~0.10 ± 0.004 mm, pH=3, and transparency of ΔΕ= 9.15 to 25. The elongation at break increased at least four times. The films were thermally stable at 400 ℃. The detailed statistical analysis and analysis of various studies indicate that the amount of castor oil (p< 0.05), a combined effect of castor oil and beeswax (p< 0.05) is significant on barrier properties while the effect of beeswax (p< 0.05) is also significant on mechanical properties.

Helicobacter pylori (H. pylori) is a gram-negative, slow-growing bacterium, microaerophilic, and a unique gastric pathogen causing chronic inflammation in the gastric mucosa with a possibility of developing gastric cancer has one-third of its proteins still uncharacterized. In this study, computational analysis has been done on the structural, functional, and epitopic characteristics of a hypothetical protein (HP) from H. pylori named HPF63-1454. The model prediction and primary, secondary, and three-dimensional structures of the chosen HP were built. The newly created model appeared to have high quality once refinement and structure validation was completed. The anticipated tertiary structure was assessed using the Swiss Model assessment. The best materials are chosen using structural analyses considering data from the Z scores, Swiss Interactive Workplace, and Ramachandran plot statistics. This investigation aimed to determine the importance of the H. pylori protein HPF63-1454. Therefore, this research will increase our understanding of pathophysiology and allow us to target the protein complex specifically. H. pylori infections are now treated with readily available antibiotics and acid-suppressing medications, but the species soon established itself as a hardy pest. Long-term and taxing antibiotic therapy for H. pylori infection is increasingly beginning to fail, necessitating novel, creative therapeutic modalities.

This Proposed control design Linear Quadratic Gaussian (LQG) for the Grid-Connected and Is-landed mode – Microgrid composed of one network feeding and forming converter with one local load was designed in this paper. The LQG controller is designed for two different Microgrid modes: Grid-connected mode and Islanded mode. A separate LQG controller was designed for each mode and a comparative analysis was made. The LQG controller was designed using the State-Space variables determined by linearizing the model, controller consists of the optimal gain ‘K’, optimal Linear Quadratic Regulator (LQR), and the Kalman Filter. In both Microgrid modes, LQG will eliminate disturbance and noise in the system and makes the system optimal control. The Microgrid system also consists of another control system that comprises the subsequent control subsystem, i.e, Alpha-Beta control, Power and Current loop, and Space Vector Modulation. The steady-state response of the Microgrid system, noise, and disturbance present in the Grid-connected and Islanded mode was rectified by the LQG controller. The design Environment used for developing Microgrid and LQG controller is in the MATLAB / Simulink platform. The effective simulations have permitted and determined results that convey the optimal control and stable performance of the proposed system.

Lignocellulosic biomass is a powerful material for producing sustainable biofuels because it converts into second-generation clean energy capable of coping with the depletion of fossil reserves and rising energy demands. Pretreatment is required in the conversion process to overcome the recalcitrance of the lignocellulosic biomass, accelerate its disintegration into cellulose, hemicellulose, and lignin and obtain an optimal yield of fermentable sugars in the enzymatic hydrolysis. In addition, it should be industrially scalable and capable of improving fuel properties and feedstock processability. Despite its conventionality, steam explosion technology has stood out due to its results and advantages such as wide applicability, high efficiency in the short term, and lack of contamination. This gentle and quick pretreatment combines high-temperature autohydrolysis and structural alteration via explosive decompression. So, steam at high pressure (1-3.5 MPa) and temperature (180-240ºC) are pressed into the cell walls and plant tissues for a duration of seconds (30 s) to several minutes (20 min). The steam explosion method has been one of the most effective especially for the hydrolysis of cellulose from agricultural wastes due to the lower amount of acetyl groups in the composition of hemicellulose. In this aspect, sugarcane bagasse is a promising feedstock for bioethanol production due to its high cellulosic content and high availability. Thereby, by selecting sugarcane bagasse pretreated by steam explosion, it is possible to achieve yields of over 80% depending on the process conditions. The aim of this review was to show the potential application of steam explosion as a thermomechanical pretreatment applied in sugarcane bagasse for bioethanol production considering its high recovery profile and its economic feasibility in a large-scale process. The stages, equipment, variables involved, by-products generated, and advantages and disadvantages of the steam explosion were all considered in this study. Finally, the technique's efficacy with various feedstocks was evaluated, resulting in a novel approach to steam explosion pretreatment.

Supercritical fluid extraction (SFE) is a non-conventional extraction technique that that has the potential to be used in the food industry because it can recover both polar and non-polar compounds. This technique is carried out above the critical point of the extraction solvent, allowing for the control and manipulation of different properties such as diffusivity, viscosity, and density. This is possible due to the fluid's changes in pressure and temperature, which cause variations in selectivity and power. This eco-friendly extraction technique has several advantages, including high selectivity due to changes in pressure and temperature, as well as changes in the solvent’s polarity, by adding co-solvents. Thus, optimizing operational conditions is a critical step in achieving the highest yield recovery of the target compound. In this way, the main variables to be considered are temperature, pressure, time, and solvent extraction, and both diffusion and solubilization are processes that have a significant influence on the extraction. SFE has already been used in the food industry due to the benefits of this technique and its suitability for both polar and non-polar compound extraction. For example, the food industry employs this extraction technique in a variety of products, including decaffeinated coffee and tea, low fat products (such as, butter and meat products), and enriched flavor distillated drinks. Furthermore, this technique has been studied for the extraction of bioactive compounds that can be incorporated into food products to increase their nutritional value. Additionally, SFE has the potential to remove toxic compounds such as pesticides in fruits and vegetables and toxins in sea products. The goal of this work is to compile the most recent data on SFE applications in the food industry, thereby providing insight into SFE feasibility in a large-scale process.

The antimicrobial activity of plants, algae and derived extracts has been a subject of interest for the scientific community. In particular, algae extracts have demonstrated their potential as a source of natural antimicrobial agents (Silva et al., 2020). Because of their antibacterial capacity and low toxicity, algal extracts have been studied as natural preservatives in food and cosmetic formulations. The use of these extracts has the potential to minimize the use of synthetic preservatives, which may be harmful to both human health and the environment. Nonetheless, the use of end-point techniques to calculate the minimal inhibitory concentration instead of creating growth inhibition curves, usually leads to an almost absence of mathematical modelling procedures on the bacterial inhibition behavior of natural extracts.

The goal of mathematical modelling is to describe the relationship between the concentration of an inhibitory agent (such as a drug or a toxin) and the growth rate of a population. For this purpose, the data obtained during the growth of six different bacteria in the presence of different concentrations of Ascophyllum nodosum (L.) extracts were recorded over 24 h. Later, the collected data was modeled based on different classical sigmoidal models e.g., Weibull, logistic, Gompertz, and modified Hill were applied to define the critical growth phases and infer the kinetic parameters.

The obtained parameters allow to conclude that the inhibition mechanisms behind the antibacterial effects of the algae extracts are diverse towards different microorganisms. The presence of the extract led to a diminution of the specific growth velocity in some cases such as Staphylococcus aureus, whereas in the replication of other bacteria such as Bacillus cereus, the extension of the lag phase was the predominant inhibition mechanism.

Silva, A.,et al . (2020). Antibacterial Use of Macroalgae Compounds against Foodborne Pathogens. Antibiotics, 9(10), 712. https://doi.org/10.3390/antibiotics9100712

The research leading to these results was supported by MICINN supporting the Ramón y Cajal grant for M.A. Prieto (RYC-2017-22891) and L. Cassani (ED481B-2021/152), and the pre-doctoral grants of P. Garcia-Oliveira (ED481A-2019/295) and M. Carpena (ED481A 2021/313). The authors thank the program BENEFICIOS DO CONSUMO DAS ESPECIES TINTORERA-(CO-0019-2021) that supports the work of F. Chamorro. The Authors are grateful to Ibero-American Program on Science and Technology (CYTED—AQUA-CIBUS, P317RT0003), to the Bio Based Industries Joint Undertaking (JU) under grant agreement No 888003 UP4HEALTH Project (H2020-BBI-JTI-2019) of C. Lourenço-Lopes and to AlgaMar company (www.algamar.com) for the collaboration and algae material provision.The authors would like to thank the EU and FCT for funding through the programs UIDB/50006/2020; UIDP/50006/2020 and Authors are grateful to Ibero-American Program on Science and Technology (CYTED— GENOPSYSEN, P222RT0117). MFB thanks FCT for the FCT Investigator (2020.03107.CEECIND).

Grape is the third most produced fruit in the world, owing to its taste and its use as raw material for winemaking. Due to this fact, large volumes of waste biomass are generated as a result of grape juice and wine production, mainly grape seeds (GS) and peels. In recent decades, scientific research has highlighted the high content of polyphenols in GS, especially condensed tannins, and resveratrol. These compounds have been correlated to various potential benefits to human health, such as antioxidant, hypoglycemic, hypolipidemic or anti-inflammatory, among others. GS polyphenols may be incorporated into functional foods, especially as flour in wheat-based bakery products, appears to be an attractive option. Two strategies may be followed. By one hand, the incorporation of GS flour increases fiber, mineral and protein content of bakery products, as well as their hardness and phenolic content. However, it seems that consumers may accept up to 10% of GS flour since higher doses strongly diminish the organoleptic properties of the product. The other alternative involves the incorporation of polyphenol-rich GS extracts into the bakery formulations which would carry their beneficial bioactivities to final product. Nonetheless, this method is more laborious since it requires a prior chemical extraction of GS, and the control and addition of a safe, food-grade extract into the flour. Both strategies have been reported to increase phenolic content and antioxidant capacity of bakery products. The direct incorporation of GS flour is affordable for industries while the incorporation of polyphenol-rich extracts leads to the development of functional products with additional beneficial properties. This work discusses the benefits and potential hurdles of functional bakery products with incorporated GS flour and extracts based on up-to-date evidence.

In this study, an artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS) were used to predict the adsorption potential of the adsorbent for the removal of chromium (VI) from aqueous solution. Four operational variables were studied to assess their impact on the adsorption study in the ANFIS model, including initial Ni (II) concentration (mg/L), pH, contact duration (min), and adsorbent dose (mg/L). To build the ANN model, 70% of the data was used for training and 15% for testing and validation. The network was trained using feedforward propagation and the Levenberg-Marquardt algorithm. The regression coefficients (R²) for the ANFIS and ANN models were 0.99 and 0.98, respectively. The results show a good match between model-predicted and experimental data, indicating that the models are appropriate and compatible. The RMSE between predicted and observed removal percentage values for the ANFIS model was 0.008, whereas the RMSE for the ANN model was 0.06. The AARE between predicted and experimental removal percentage values for the ANFIS and ANN models was determined to be 0.009 and 0.045, respectively. The MSE between predicted and experimental removal percentages for the ANFIS and ANN models was found to be 0.002 and 0.035, respectively. the optimum conditions were pH 6, initial concentration of 275 mg/L, contact time of 60 min, and a dosage of 12.5 mg/L, the absorption was 91.00%.

Drugs are an important problem of pollution of the aquatic environment. Global drugs consumption, their use in human and veterinary medicine and agriculture are among the main sources of environmental pollution. Among the detected drugs, antibiotics are an important group, as they have high biological activity, and most of them dissolve well in water. The presence of antibiotics in the environment can adversely affect the organisms living in it - leading to reproductive, metabolic or histopathological disorders.

Drugs entering aquatic systems can remain unchanged or under the influence of various factors undergo degradation or transformation processes. One of these phenomena is the process of phototransformation as a result of which the resulting derivatives differ in physicochemical, pharmacological properties and toxicity from the parent compounds. The purpose of this preliminary study was to determine the potential ecotoxicity of the degradation products of cefepime, 4th generation cephalosporins. Toxicity was assessed using in silico methods, and then microbiotests were performed: Daphotoxikit and Thamnotoxikit. The used tests allow for a simple and quick assessment of how the tested mixtures of substances affect the survival of bioindicators. In addition, there is no need for continuous culture of test organisms. The tests do not require Ethics Committee approval and comply with the 3Rs principle (Reduction, Replacement, Refinement), which aims to reduce the use of laboratory animals. Data obtained during our preliminary studies indicate that mixtures of the parent compound and their photodegradation products are more toxic to the tested organisms than the parent compound.