Modelling techniques allow certain processes to be characterized and optimized without the need for experimentation. One of the crucial steps in vinegar production is the biotransformation of ethanol into acetic acid by acetic bacteria. This step has been extensively studied by using two predictive models: first-principles models and black-box models. The fact that first-principles models are less accurate than black-box models under extreme bacterial growth conditions suggests that the kinetic equations used by the former, and hence their goodness of fit, can be further improved. By contrast, black-box models predict acetic acid production accurately enough under virtually any operating conditions. In this work, we trained black-box models based on Artificial Neural Networks (ANNs) of the multilayer perceptron (MLP) type and containing a single hidden layer to model acetification. The small number of data typically available for a bioprocess makes it rather difficult to identify the m... [more]

The drive at the center of gravity (DCG) principle has been adopted in computer numerical control (CNC) machines and industrial robots that require heavy-duty and quick feeds. Using this principle requires accurate corrections of positioning errors. Conventional error compensation methods may cause vibrations and unstable control performances due to the delay between compensation and motor motion. This paper proposes a new method to reduce the positioning errors of the dual-driving gantry-type machine tool (DDGTMT), namely, a typical DCG-principle-based machine tool. An error prediction method is proposed to characterize errors online. An algorithm is proposed to quickly and accurately compensate the errors of the DDGTMT. Experiment results verify that the non-delay error compensation method proposed in this paper can effectively improve the accuracy of the DDGTMT.

The global burden of cancer is on the rise, and as a result, the number of therapeutics administered for chemotherapy is increasing. The occupational exposure, recalcitrant nature and ecotoxicological toxicity of these therapeutics, referred to as antineoplastic (ANP) drugs, have raised concerns about their safe remediation. This review provides an overview of the environmental source of ANPs agents, with emphasis on the currently used remediation approaches. Outpatient excreta, hospital effluents, and waste from pharmaceutical industries are the primary source of ANP waste. The current review describes various biotic and abiotic methods used in the remediation of ANP drugs in the environment. Abiotic methods often generate transformation products (TPs) of unknown toxicity. In this light, obtaining data on the environmental toxicity of ANPs and its TPs is crucial to determine their toxic effect on the ecosystem. We also discuss the biodegradation of ANP drugs using monoculture of funga... [more]

Alkyl lactates are green solvents that are successfully employed in several industries such as pharmaceutical, food and agricultural. They are considered prospective renewable substitutes for petroleum-derived solvents and the opportunity exists to obtain these valuable chemicals from the chemical recycling of waste poly(lactic acid). Alkyl lactates (ethyl lactate, propyl lactate and butyl lactate) were obtained from the catalysed alcoholysis reaction of poly(lactic acid) with the corresponding linear alcohol. Reactions were catalysed by a Zn complex synthesised from an ethylenediamine Schiff base. The reactions were studied in the 50−130 °C range depending on the alcohol, at autogenous pressure. Arrhenius temperature-dependent parameters (activation energies and pre-exponential factors) were estimated for the formation of the lactates. The activation energies (Ea1, Ea2 and Ea−2) for alcoholysis in ethanol were 62.58, 55.61 and 54.11 kJ/mol, respectively. Alcoholysis proceeded fastest... [more]

The rapid development of renewable energy, represented by wind and photovoltaic, provides a new solution for island power supplies. However, due to the intermittent and random nature of renewable energy, a microgrid needs energy-storage components to stabilize its power supply when coupled with them. The emergence of seawater-pumped storage stations provides a new method to offset the shortage of island power supply. In this study, an optimal scheduling of island microgrid is proposed, which uses seawater-pumped storage station as the energy storage equipment to cooperate with wind, photovoltaic and diesel generator. First, a mathematic formulation of seawater-pumped storage station with renewable energy is presented. Then, to reach the goal of economic dispatch, an optimal scheduling model of island microgrid is established with the consideration of both respective operation constraints and island load requirements. Finally, the effectiveness of the proposed model is verified by an is... [more]

The traditional ageing of wine spirits is done in wooden barrels, however, high costs have led to the search for alternative technologies, such as the use of stainless steel tanks with wooden staves and the application of micro-oxygenation. This work evaluates the changes in the major volatile compounds of wine spirits aged for 6, 12 and 18 months in wooden barrels and stainless steel tanks with micro-oxygenation. For both ageing technologies, two types of wood (Limousin oak and Portuguese chestnut wood) were used. The samples were analysed concerning their alcohol strength (electronic densimetry) and volatile composition, namely of methanol, acetaldehyde, ethyl acetate and other major volatile compounds ((GC-FID) and near-infrared spectroscopy (NIR)). The results show that the ageing technology was more influential than the wood species for the volatile composition of wine spirits, namely acetaldedehyde, methanol, 2-methylpropan-1-ol and 2+3-methylbutan-1-ol. However, the opposite beh... [more]

The novel cationic flocculant, poly(lactic acid) choline iodide ester methacrylate (poly(PLA4ChMA)), has been shown to provide improved flocculation of 5.0 wt.% mature fine tailings (MFT) diluted in deionized water compared to commercial anionic polymers, with continued dewatering of the sediment occurring as the polymer undergoes partial hydrolytic degradation. However, the elevated dosages (10,000 ppm) required would make the polymer costly to implement on an industrial scale. With this motivation, the impact of MFT loading and the use of process water is explored while comparing the settling performance of poly(PLA4ChMA) to available commercial alternatives such as anionic FLOPAM A3338. Improved consolidation of 5.0 wt.% MFT diluted with process water could be achieved at reduced dosages (500 ppm) with poly(PLA4ChMA). However, the final compaction levels after polymer degradation were similar to those achieved with the nondegradable commercial flocculants. Flocculation-filtration ex... [more]

Up-flow Anaerobic Sludge Blanket (UASB) reactors are popular tools in wastewater treatment systems due to the ability to work with high feed rates and wastes with high concentration of organic contaminants. While full-scale industrial applications of UASB reactors are developed and described in the available literature, laboratory-scale designs utilized for treatability testing are not well described. The majority of published studies do not describe the laboratory UASB construction details or do use reactors that already had developed a trophic network in microbial consortia under laboratory environment and therefore are more stable. The absence of defined guidelines for geometry design, selection of materials, construction, operation rules, and, especially, the start-up conditions, significantly hamper researchers who desire to conduct treatability testing using UASB reactors in laboratory scale. In this article, we compiled and analyzed the information available in the refereed lite... [more]

Post-thickener polymer addition to initiate rapid tailings dewatering has gained considerable interest for tailings storage facility (TSF) management. However, the highly viscous and non-Newtonian rheology of dense suspensions presents unique challenges for mixing with polymer solutions. Such mixing is highly inefficient, often resulting in polymer overdosing and wide variations in deposited tailings characteristics, with the potential to significantly compromise TSF performance. In this study, a new type of mixer based on the principles of chaotic advection was used for treating kaolin suspensions with high molecular weight (MW) anionic copolymer solutions. Chaotic advection imparts efficient mixing by gently stretching and folding flows in a controlled manner, as opposed to random, high-shear flows associated with turbulent mixing, and this lower shear stress allows for the controlled formation of larger aggregate structures with vastly improved dewatering characteristics. A pre-cond... [more]

The extraction of glycyrrhizin from licorice root and stolon with ethanol/water solutions leaves a lignocellulosic residue, which could be potentially applied in biocomposites. This process proved difficult in principle, given the considerable hardness of this material as received, which impedes its use in polymer resins in large amounts. After ball milling, up to 10% of this fibrous residue, which shows very variable aspect ratio, was introduced into an epoxy matrix, to investigate its possible future application in sustainable polymers. Of the three composites investigated, containing 1, 5 and 10 wt% of licorice waste, respectively, by performing flexural testing, it was found that the introduction of an intermediate amount of filler proved the most suitable for possible development. Thermal characterization by thermogravimetry (TGA) did not indicate large variation of degradation properties due to the introduction of the filler. Despite the preliminary characteristics of this study,... [more]

Nowadays, the steel industry is seeking to reduce its carbon footprint without affecting productivity or profitability. This challenge needs to be supported by continuous improvements in equipment, methods, sensors and models. The present work exposes how the combined development of processes and models (CDPM) has been applied to the improvement of hot metal temperature determination. The synergies that arise when both sides of this research are simultaneously approached are evidenced. A workflow that takes into account the CDPM approach is proposed. First, a thermal model of the process is developed, making it possible to identify that hot metal temperature is a key lever for carbon footprint reduction. Then, three main alternatives for hot metal temperature determination are compared: infrared thermometry, time-series forecasting and machine learning prediction. Despite considering only few process variables, machine learning techniques succeed in extracting relevant information from... [more]

Air−light hydrocarbon mixing gas is a new type of city gas which is composed of light hydrocarbon with the main component of n-pentane and air mixed in a certain proportion. To explore the dominant reactions for CO production of air−light hydrocarbon mixing gas with different mixing degrees at the critical equivalence ratios, a computational study was conducted on the combustion characteristics, including the ignition delay time, laminar flame speed, extinction residence time, and emission of air−light hydrocarbon mixing gas at atmospheric pressure and room temperature in the present study. The calculated results indicate that the ignition delay time of air−light hydrocarbon mixing gas at temperatures of 1000−1118 K is greater than that of n-pentane, while the opposite at temperatures of 1118−1600 K. From the study of the laminar flame speed and ignition delay time, it was found that the essence of air−light hydrocarbon mixing gas is that its attribute parameter is determined by the ra... [more]

Deep lean is a novel approach that is concerned with the profound analysis for waste’s behavior at hidden layers in manufacturing processes to enhance processes’ reliability level at the upstream. Ideal Standard Co. for bathtubs suffered from defects and cost losses in the spraying section, due to differences in the painting cover thickness due to bubbles, caused by eddies, which move toward the bathtubs through hoses. These bubbles and their movement are considered as a form of lean’s waste. The spraying liquid inside the tanks and hoses must move with uniform velocity, viscosity, pressure, feed rate and suitable Reynolds circulation values to eliminate the eddy causes. These factors are tackled through the adoption Internet of Things (IoT) technologies that are aided by neural networks (NN) when an abnormal flow rate is detected using sensor data in real-time that can reduce the defects. The NN aimed at forecasting eddies’ movement lines that carry bubbles and works on being blasted... [more]

This article focuses on fuel quality in biomass power plants and describes an online prediction method based on image analysis and regression modeling. The main goal is to determine the mixture fraction from blends of two wood chip species with different qualities and properties. Starting from images of both fuels and different mixtures, we used two different approaches to deduce feature vectors. The first one relied on integral brightness values while the latter used spatial texture information. The features were used as input data for linear and non-linear regression models in nine training classes. This permitted the subsequent prediction of mixture ratios from prior unknown similar images. We extensively discuss the influence of model and image selection, parametrization, the application of boosting algorithms and training strategies. We obtained models featuring predictive accuracies of R2 > 0.9 for the brightness-based model and R2 > 0.8 for the texture based one during the valid... [more]

Condensate-liquid accumulation in the vicinity of a well is known to curtail gas production up to 80%. Numerous approaches are employed to mitigate condensate banking and improve gas productivity. In this work, a field-scale simulation is presented for condensate damage removal in tight reservoirs using a thermochemical treatment strategy where heat and pressure are generated in situ. The impact of thermochemical injection on the gas recovery is also elucidated. A compositional simulator was utilized to assess the effectiveness of the suggested treatment on reducing the condensate damage and, thereby, improve the gas recovery. Compared to the base case, represented by an industry-standard gas injection strategy, simulation studies suggest a significantly improved hydrocarbon recovery performance upon thermochemical treatment of the near-wellbore zone. For the scenarios investigated, the application of thermochemicals allowed for an extension of the production plateau from 104 days, as... [more]

New synthetic biobased mechanically adaptive composites, responding to water and having self-healing property, were developed. These composites were prepared by introducing plant-based cellulose nanofibrils (CNFs) at 10, 20, and 25% (v/v) concentration into a biobased rubbery poly (myrcene-co-furfuryl methacrylate) (PMF) matrix by solution mixing and subsequent compression molding technique. The reinforcement of CNFs led to an increase in the tensile storage modulus (E’) of the dry composites. Upon exposure to water, water sensitivity and a drastic fall in storage moduli (E’) were observed for the 25% (v/v) CNF composite. A modulus reduction from 1.27 (dry state) to 0.15 MPa (wet state) was observed for this composite. The water-sensitive nature of the composites was also confirmed from the force modulation study in atomic force microscopy (AFM), revealing the average modulus as 82.7 and 32.3 MPa for dry and swollen composites, respectively. Interestingly, the composites also showed th... [more]

Mitochondrial proteins of Plasmodium falciparum (MPPF) are an important target for anti-malarial drugs, but their identification through manual experimentation is costly, and in turn, their related drugs production by pharmaceutical institutions involves a prolonged time duration. Therefore, it is highly desirable for pharmaceutical companies to develop computationally automated and reliable approach to identify proteins precisely, resulting in appropriate drug production in a timely manner. In this direction, several computationally intelligent techniques are developed to extract local features from biological sequences using machine learning methods followed by various classifiers to discriminate the nature of proteins. Unfortunately, these techniques demonstrate poor performance while capturing contextual features from sequence patterns, yielding non-representative classifiers. In this paper, we proposed a sequence-based framework to extract deep and representative features that are... [more]

The goal of this work was to investigate the effect of the biochar additive (2.5; 5; 10 wt.%) on the properties of carbon fiber-reinforced bio-epoxy composites. The morphology of the composites was monitored by scanning electron microscopy (SEM), and the thermomechanical properties by dynamic mechanical thermal analysis (DMTA). Additionally, mechanical properties such as impact strength, flexural strength andtensile strength, as well as the thermal stability and degradation kinetics of these composites were evaluated. It was found that the introduction of biochar into the epoxy matrix improved the mechanical and thermal properties of carbon fiber-reinforced composites.

Over the last decade, food waste has been one of the major issues globally as it brings a negative impact on the environment and health. Rotting discharges methane, causing greenhouse effect and adverse health effects due to pathogenic microorganisms or toxic leachates that reach agricultural land and water system. As a solution, composting is implemented to manage and reduce food waste in line with global sustainable development goals (SDGs). This review compiles input on the types of organic composting, its characteristics, physico-chemical properties involved, role of microbes and tools available in determining the microbial community structure. Composting types: vermi-composting, windrow composting, aerated static pile composting and in-vessel composting are discussed. The diversity of microorganisms in each of the three stages in composting is highlighted and the techniques used to determine the microbial community structure during composting such as biochemical identification, po... [more]

This paper presents a multi-scale-homogenization based on a two-step methodology (micro-meso and meso-macro homogenization) to predict the elastic constants of 3D fiber-reinforced composites (FRC). At each level, the elastic constants were predicted through both analytical and numerical methods to ascertain the accuracy of predicted elastic constants. The predicted elastic constants were compared with experimental data. Both methods predicted the in-plane elastic constants “ E x ” and “ E y ” with good accuracy; however, the analytical method under predicts the shear modulus “ G x y ”. The elastic constants predicted through a multiscale homogenization approach can be used to predict the behavior of 3D-FRC under different loading conditions at the macro-level.

In this study, livestock wastewater treatment plants in South Korea were monitored to determine the characteristics of influent and effluent wastewater, containing four types of veterinary antibiotics (sulfamethazine, sulfathiazole, chlortetracycline, oxytetracycline), and the removal efficiencies of different treatment processes. Chlortetracycline had the highest average influent concentration (483.7 μg/L), followed by sulfamethazine (251.2 μg/L), sulfathiazole (230.8 μg/L) and oxytetracycline (25.7 μg/L), at five livestock wastewater treatment plants. Sulfathiazole had the highest average effluent concentration (28.2 μg/L), followed by sulfamethazine (20.8 μg/L) and chlortetracycline (11.5 μg/L), while no oxytetracycline was detected. For veterinary antibiotics in the wastewater, a removal efficiency of at least 90% was observed with five types of treatment processes, including a bio-ceramic sequencing batch reactor, liquid-phase flotation, membrane bioreactor, bioreactor plus ultraf... [more]

Phenol degradation by Pseudomonas putida BCRC 14365 was investigated at 30 °C and a pH of 5.0−9.0 in the batch tests. Experimental results for both free and immobilized cells demonstrated that a maximum phenol degradation rate occurred at an initial pH of 7. The peak value of phenol degradation rates by the free and immobilized cells were 2.84 and 2.64 mg/L-h, respectively. Considering the culture at 20 °C, there was a lag period of approximately 44 h prior to the start of the phenol degradation for both free and immobilized cells. At the temperatures ranging from 25 to 40 °C, the immobilized cells had a higher rate of phenol degradation compared to the free cells. Moreover, the removal efficiencies of phenol degradation at the final stage were 59.3−92% and 87.5−92%, for the free and immobilized cells, respectively. The optimal temperature was 30 °C for free and immobilized cells. In the batch experiments with various initial phenol concentrations of 68.3−563.4 mg/L, the lag phase was... [more]

RNA viruses, such as influenza and Severe Acute Respiratory Syndrome (SARS), invoke excessive immune responses; however, the kinetics that regulate inflammatory responses within infected cells remain unresolved. Here, we develop a mathematical model of the RNA virus sensing pathways, to determine the intracellular events that primarily regulate interferon, an important protein for the activation and management of inflammation. Within the ordinary differential equation (ODE) model, we incorporate viral replication, cell death, interferon stimulated genes’ antagonistic effects on viral replication, and virus sensor protein (TLR and RIG-I) kinetics. The model is parameterized to influenza infection data using Markov chain Monte Carlo and then validated against infection data from an NS1 knockout strain of influenza, demonstrating that RIG-I antagonism significantly alters cytokine signaling trajectory. Global sensitivity analysis suggests that paracrine signaling is responsible for the ma... [more]

The effect of ultrasound and enzyme pretreatment (with pectinase, amylase, and cellulase) on the physicochemical properties (yield, viscosity, total soluble solids, and total phenolics) of mango juice was evaluated through a set of six experiments. Ultrasonication treatment alone showed no influence on juice yield (54.6 ± 1.1%). However, the combined uses of ultrasonication with a pectinase or the enzyme mixture significantly increased the yield (94.1 ± 1.4% and 80.0 ± 2.1%, respectively) and decreased the enzyme pretreatment time (from 2 h to 1 h). Pectinase treatment assisted by ultrasonication was more effective with regard to juice yield, viscosity reduction, and the clarity of the juice than the enzyme mixture treatment with ultrasonication. Ultrasonication alone significantly increased the amount of total phenolics (65.5 ± 1.0 mg/100 mL) and showed a slight reduction of viscosity and improvement of clarity compared to the control.

Globally, increasing environmental issues are gaining attention to facilitate the adoption of green innovation for sustainable supply chain management (SSCM). Sustainable environmental practices have been well-considered in the literature; however, no study has focused on adopting green innovation practices for sustainable development. Thus, environmental management authorities are putting pressure on industries to implement green innovation criteria for SSCM operations. Moreover, it is important to select traditional suppliers to transform its practices to that of sustainable supply chains in order to achieve the industry’s sustainable supply chain goals. In response, this research identified and analyzed the green innovation criteria for SSCM and then selected a supplier that could implement green aspects in the SSCM. This study developed an integrated multi-criteria decision making (MCDM) model using the fuzzy analytical hierarchy process (FAHP) and the fuzzy technique for order of... [more]