Processes

Journal Information
EISSN : 2227-9717
Current Publisher: MDPI AG (10.3390)
Total articles ≅ 4,191
Current Coverage
SCOPUS
SCIE
INSPEC
DOAJ
Archived in
SHERPA/ROMEO
Filter:

Latest articles in this journal

Published: 18 June 2021
Processes, Volume 9; doi:10.3390/pr9061068

Abstract:
In this study, paper-mill wastewater was treated using the Submerged Membrane Bioreactor (SMBR) process. In particular, the ozone oxidation treatment process is applied after SMBR to remove the fluorescent whitening agent, which is a trace pollutant and non-biodegradable. Fluorescent whitening agent concentration was indirectly measured by UV scanning and COD concentration. The concentration of COD before SMBR and ozone oxidation was 449.3 mg/L, and the concentration of treated water was 100.3 mg/ℓ. The COD removal efficiency of paper-mill wastewater through SMBR and the ozone oxidation process was about 77.68%. The optimized amount of ozone was required for the removal of the fluorescent whitening agent after SMBR was 95 mg·O3/ℓ calculated by UV scan results. Additionally, the optimized amount of required ozone to remove COD was calculated to 0.126 mg·COD/mg·O3.
Published: 18 June 2021
Processes, Volume 9; doi:10.3390/pr9061067

Abstract:
The quality of product and process is one of the most important factors in achieving constructively and then functionally safe products in any industry. Over the years, the concept of Industry 4.0 has emerged in all the quality processes, such as nondestructive testing (NDT). The most widely used quality control methods in the industries of mechanical engineering, aerospace, and civil engineering are nondestructive methods, which are based on inspection by detecting indications, without affecting the surface quality of the examined parts. Over time, the focus has been on research with the fourth generation in nondestructive testing, i.e., NDT 4.0 or Smart NDT, as a main topic to ensure the efficiency and effectiveness of the methods for a safe detection of all types of discontinuities. This area of research aims at the efficiency of methods, the elimination of human errors, digitalization, and optimization from a constructive point of view. In this paper, we presented a magnetic particles inspection method and the possible future directions for the development of standard equipment used in the context of this method in accordance with the applicable physical principles and constraints of the method for cylindrical parts. A possible development direction was presented in order to streamline the mass production of parts made of ferromagnetic materials. We described the methods of analysis and the tools used for the development of a magnetic particle inspection method used for cylindrical parts in all types of industry and NDT 4.0; the aim is to provide new NDT 4.0 directions in optimizing the series production for cylindrical parts from industry, as given in the conclusion of this article.
Published: 18 June 2021
Processes, Volume 9; doi:10.3390/pr9061066

Abstract:
The current research concerns the group acceptance sampling plan in the case where (i) the lifetime of the items follows the Marshall–Olkin Kumaraswamy exponential distribution (MOKw-E) and (ii) a large number of items, considered as a group, can be tested at the same time. When the consumer’s risk and the test terminsation period are defined, the key design parameters are extracted. The values of the operating characteristic function are determined for different quality levels. At the specified producer’s risk, the minimum ratios of the true average life to the specified average life are also calculated. The results of the present study will set the platform for future research on various nano quality level topics when the items follow different probability distributions under the Marshall–Olkin Kumaraswamy scheme. Real-world data are used to explain the technique.
Published: 18 June 2021
Processes, Volume 9; doi:10.3390/pr9061064

Abstract:
Olive oil dregs (OOD), which are an underutilized by-product from oil mills, were used for the extraction of antioxidant compounds. The residues from three oil mills located in Campania (Southern Italy) were extracted with acidified methanol, and hydroxytyrosol (HT) was the main phenolic compound detected. Total phenolic content (TPC) and HT amount were measured. EVO Campania oil mill provided the residue with the highest TPC and HT quantities: 6.801 ± 0.159 mg Gallic Acid Equivalents (GAE)/g OOD and 519.865 ± 9.082 μg/g OOD, respectively. Eco-friendly extractions at different temperatures and times were performed on EVO Campania OOD, obtaining 9.122 ± 0.104 mg GAE/g OOD and 541.330 ± 64.087 μg/g OOD for TPC and HT, respectively, at 121 °C for 60 min. Radical Scavenging Activity (RSA), Superoxide Scavenging Activity (SSA), and Ferric Reducing Antioxidant Power (FRAP) were measured in OOD aqueous extracts. Extract prepared at 37 °C for 60 min showed the greatest RSA and SSA values (44.12 ± 1.82 and 75.72 ± 1.78, respectively), whereas extract prepared at 121 °C for 60 min exhibited the highest FRAP value (129.10 ± 10.49 μg Ascorbic Acid Equivalents (AAE)/mg). OOD extracts were able to protect sunflower oil from oxidation for 4 weeks at 65 °C. The overall results suggest that this novel residue can be usefully valorized by providing HT-rich extracts to use as antioxidant agents.
Published: 18 June 2021
Processes, Volume 9; doi:10.3390/pr9061065

Abstract:
This study describes the influence of orchard cultural practices during the productive process of cherries on the environmental impact in terms of energy, air, soil and water through a “farm to market” Life Cycle Assessment (LCA). The results were used to identify the orchard cultural practices that contribute significantly to the environmental impact and to find solutions to reduce those impacts, serving as best practices guide to improving the environmental performance and as benchmarks for other national and international cherry and fruit growers. Primary data for production, harvest and post-harvest periods were gathered experimentally. The openLCA 1.10.2 software and the ecoinvent 3.5 database were used for modelling. Test case scenarios are modelled to identify the influence of cultural practices in low and high cherry production campaigns depending on climatic conditions and consequently diseases and plagues. Moreover, results are compared with other studies, not only covering cherries but also other fruits. The energy consumption per hectare in the production phase is similar in test scenarios. The energy consumption of orchard cultural practices related to tractor use, fertilizers and fungicides application are the main hotspots in terms of global warming, freshwater ecotoxicity and eutrophication, and terrestrial acidification. The use of electric vehicles, change the warehouse location or redefine transportation routes can reduce this impact, along with the optimization of the cherry’s quantity transported in each trip. In addition, the use of plant protection products, fertilizers and herbicides with less environmental impact will contribute to this objective. For that, the use of agriculture and precision systems to predict the need for fertilizers (nutrients), herbicides and fungicides, the use of decision support systems to define the dates of cultural practices, as well as innovative and emerging food and by-products processing methods are suggested. Thus, this study identifies and quantifies the environmental impacts associated with the production system of cherries and their main hotspots. It provides a best-practices guide for sustainable solutions in orchard management that contributes to the competitiveness and sustainability of fruit companies.
Published: 17 June 2021
Processes, Volume 9; doi:10.3390/pr9061055

Abstract:
Protonated g-C3N4 (pCN) formed by treating bulk g-C3N4 with an aqueous HCl solution was modified with D149 dye, i.e., 5-[[4[4-(2,2-diphenylethenyl) phenyl]-1,2,3,3a,4,8b-hexahydrocyclopent[b]indol-7-yl] methylene]-2-(3-ethyl-4-oxo-2-thioxo-5-thiazolidinylidene)-4-oxo-thiazolidin-2-ylidenerhodanine, for photocatalytic water splitting (using Pt as a co-catalyst). The D149/pCN-Pt composite showed a much higher rate (2138.2 µmol·h−1·g−1) of H2 production than pCN-Pt (657.0 µmol·h−1·g−1). Through relevant characterization, the significantly high activity of D149/pCN-Pt was linked to improved absorption of visible light, accelerated electron transfer, and more efficient separation of charge carriers. The presence of both D149 and Pt was found to be important for these factors. A mechanism was proposed.
Published: 17 June 2021
Processes, Volume 9; doi:10.3390/pr9061056

Abstract:
The widescale distribution of hydrogen through gas networks is promoted as a viable and cost-efficient option for optimising its application in heat, industry, and transport. It is a key step towards achieving decarbonisation targets in the UK. A key consideration before the injection of hydrogen into the UK gas networks is an assessment of the difference in hydrogen contaminants presence from different production methods. This information is essential for gas regulation and for further purification requirements. This study investigates the level of ISO 14687 Grade D contaminants in hydrogen from steam methane reforming, proton exchange membrane water electrolysis, and alkaline electrolysis. Sampling and analysis of hydrogen were carried out by the National Physical Laboratory following ISO 21087 guidance. The results of analysis indicated the presence of nitrogen in hydrogen from electrolysis, and water, carbon dioxide, and particles in all samples analysed. The contaminants were at levels below or at the threshold limits set by ISO 14687 Grade D. This indicates that the investigated production methods are not a source of contaminants for the eventual utilisation of hydrogen in different applications including fuel cell electric vehicles (FCEV’s). The gas network infrastructure will require a similar analysis to determine the likelihood of contamination to hydrogen gas.
Published: 17 June 2021
Processes, Volume 9; doi:10.3390/pr9061057

Abstract:
Drug repositioning is a strategy to identify new uses for existing, approved, or research drugs that are outside the scope of its original medical indication. Drug repurposing is based on the fact that one drug can act on multiple targets or that two diseases can have molecular similarities, among others. Currently, thanks to the rapid advancement of high-performance technologies, a massive amount of biological and biomedical data is being generated. This allows the use of computational methods and models based on biological networks to develop new possibilities for drug repurposing. Therefore, here, we provide an in-depth review of the main applications of drug repositioning that have been carried out using biological network models. The goal of this review is to show the usefulness of these computational methods to predict associations and to find candidate drugs for repositioning in new indications of certain diseases.
Published: 17 June 2021
Processes, Volume 9; doi:10.3390/pr9061058

Abstract:
The boiling performance of functionalized hybrid aluminum surfaces was experimentally investigated for water and self-rewetting mixtures of water and 1-butanol. Firstly, microstructured surfaces were produced via chemical etching in hydrochloric acid and the effect of the etching time on the surface morphology was evaluated. An etching time of 5 min was found to result in pitting corrosion and produced weakly hydrophilic microstructured surfaces with many microcavities. Observed cavity-mouth diameters between 3.6 and 32 μm are optimal for efficient nucleation and provided a superior boiling performance. Longer etching times of 10 and 15 min resulted in uniform corrosion and produced superhydrophilic surfaces with a micropeak structure, which lacked microcavities for efficient nucleation. In the second stage, hybrid surfaces combining lower surface energy and a modified surface microstructure were created by hydrophobization of etched aluminum surfaces using a silane agent. Hydrophobized surfaces were found to improve boiling heat transfer and their boiling curves exhibited a significantly lower superheat. Significant heat transfer enhancement was observed for hybrid microcavity surfaces with a low surface energy. These surfaces provided an early transition into nucleate boiling and promoted bubble nucleation. For a hydrophobized microcavity surface, heat transfer coefficients of up to 305 kW m−2 K−1 were recorded and an enhancement of 488% relative to the untreated reference surface was observed. The boiling of self-rewetting fluids on functionalized surfaces was also investigated, but a synergistic effect of developed surfaces and a self-rewetting working fluid was not observed. An improved critical heat flux was only obtained for the untreated surface, while a lower critical heat flux and lower heat transfer coefficients were measured on functionalized surfaces, whose properties were already tailored to promote nucleate boiling.
Published: 17 June 2021
Processes, Volume 9; doi:10.3390/pr9061059

Abstract:
Tea is a popular beverage worldwide and also has great medical value. A fundamental understanding of tea shoot growth and a precision picking model should be established to realize mechanized picking of tea shoots with a small product loss. Accordingly, the terminal bud length (Lbud), tea stem length (Lstem), terminal bud angle (αbud), tea stem angle (αstem), and growth time (t) were considered as the key growth parameters; the sum of the vertical lengths of the terminal bud and stem (ξ), the picking radius (r), and the vertical length of the stem (Zstem) were considered as the picking indexes of the tea shoots. The variations in growth parameters with time were investigated using a 3-D coordinate instrument, and the relationships between the growth parameters and the picking indexes were established using an artificial neural network (ANN). The results indicated that the tea growth cycles for periods P1, P2, P3, P4, P5, and P6 were 14, 7, 6, 4, 4, and 6 d, respectively. A growth cycle diagram of the tea growth was established. Moreover, a 5-2-12-3 ANN model was developed. The best prediction of ξ, r, and Zstem was found with 16 training epochs. The MSE value was 0.0923 × 10−4, and the R values for the training, test, and validation data were 0.99976, 0.99871, and 0.99857, respectively, indicating that the established ANN model demonstrates excellent performance in predicting the picking indexes of tea shoots.
Back to Top Top