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Processes, Volume 9, Issue 8 (August 2021) – 222 articles

Cover Story (view full-size image): Water transport in food materials during freeze-drying is of high interest for maintaining high quality at lower costs. The vapor transport through the pores is, besides the chemical composition of the food material, based on physical properties like the internal pore structure. In frozen materials, especially the size and the arrangement of the ice crystals determines the open pore structure and a good interconnection of the pores during drying. In this study, the dependency of the internal structure of granular instant beverage powder on process parameters in a scraped surface heat exchanger is analyzed. The impact of this pore structure on freeze-drying kinetics is investigated to reduce the drying time. View this paper
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Article
Performance of Alternative Methane Reforms Based on Experimental Kinetic Evaluation and Simulation in a Fixed Bed Reactor
Processes 2021, 9(8), 1479; https://doi.org/10.3390/pr9081479 - 23 Aug 2021
Cited by 1 | Viewed by 637
Abstract
A comparative evaluation of alternative methane reforming processes as an option to steam reforming was performed by carrying out simulations of operations in a fixed bed reactor with a Ni (4.8 wt.%/γ-Al2O3) catalyst at 1023 K under 1.0 bar. [...] Read more.
A comparative evaluation of alternative methane reforming processes as an option to steam reforming was performed by carrying out simulations of operations in a fixed bed reactor with a Ni (4.8 wt.%/γ-Al2O3) catalyst at 1023 K under 1.0 bar. Methane reforms, including processing with carbon dioxide (DRM, CH4/CO2), autothermal reform (ATRM, CH4/H2O/O2), and combined reform (CRM, CH4/CO2/H2O/O2) had their operations predicted based on experimental data developed to represent their kinetic behavior, formalized with mechanisms and parametric quantifications. The performance of fixed bed reactor operations for methane conversions occurred with different reaction rates in the three alternative processes, and comparatively the orders of magnitude were 102, 10−1, and 10−4 in CRM, ATRM, and DRM, respectively. According to each process, the methane conversions were oriented towards the predominant productions of hydrogen or carbon monoxide, indicating the kinetic selectivities of H2, 86.1% and CO, 59.2% in CRM and DRM, respectively. Considering the possibility of catalyst deactivation by carbon deposition, its predicted yields are low due to the slow stages of its production and due to its simultaneous consumption through interactions with O2, CO2, and H2O, reflecting favorably in additional productions of H2 and CO. Full article
(This article belongs to the Special Issue Methane Reforming Processes)
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Article
Numerical Simulation of Passive Cooling Beam and Its Optimization to Increase the Cooling Power
Processes 2021, 9(8), 1478; https://doi.org/10.3390/pr9081478 - 23 Aug 2021
Viewed by 571
Abstract
This article is focused on the research of passive cooling beams and increasing their cooling capacity. A passive cooling beam with four tubes was chosen as a model. A mathematical model was built using the corresponding criterion equations to capture the behavior of [...] Read more.
This article is focused on the research of passive cooling beams and increasing their cooling capacity. A passive cooling beam with four tubes was chosen as a model. A mathematical model was built using the corresponding criterion equations to capture the behavior of a passive cooling beam. This mathematical model can be used to optimize geometrical parameters (the distance between the ribs, rib height and thickness, and diameter and number of tubes), by changing these geometric parameters we can increase the cooling performance. The work includes a mathematical model for calculating the boundary layer, which has a significant influence on the cooling performance. The results obtained from the created mathematical model show that the model works correctly and can be used to optimize the cooling performance of passive cooling beams. To better understand the behavior of a passive cooling beam in a confined space, the entire device was numerically simulated, as was the flow in the intercostal space. Full article
(This article belongs to the Special Issue Experimental and Numerical Methods in Fluid Mechanics and Energy)
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Article
Numerical Study of Non-Linear Dynamic Behavior of an Asymmetric Rotor for Wave Energy Converter in Regular Waves
Processes 2021, 9(8), 1477; https://doi.org/10.3390/pr9081477 - 23 Aug 2021
Cited by 3 | Viewed by 512
Abstract
This study conducted a numerical investigation on the non-linear motion problems between a Salter duck-type rotor and large waves using CFD simulations. Regular waves of five different wave heights were generated. First, the linear motion of the rotor from the CFD simulation was [...] Read more.
This study conducted a numerical investigation on the non-linear motion problems between a Salter duck-type rotor and large waves using CFD simulations. Regular waves of five different wave heights were generated. First, the linear motion of the rotor from the CFD simulation was verified by comparing it with the existing experimental and frequency domain analysis results. Then, a series of CFD simulations were performed to investigate the non-linear motions of the rotor. In the case of a lower wave height, the CFD simulation results were in good agreement with the experimental and frequency domain analysis results. However, as the wave height increased, the resonance periods were different in each other. In addition, the magnitudes of normalized pitch motions by the wave heights decreased as the wave heights increased. To investigate the aforementioned phenomena, the pitch motion equation was examined using separate CFD simulations. The results showed that changing the restoring moments induced changes in the maximum pitch motions and magnitudes of the normalized pitch motions. In the case of a higher wave height, non-linear phenomena and the changing restoring moments induced non-linear motion. Full article
(This article belongs to the Special Issue Wave Energy Technologies in Korea)
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Article
Model Discrimination for Hydrogen Peroxide Consumption towards γ-Alumina in Homogeneous Liquid and Heterogeneous Liquid-Liquid Systems
Processes 2021, 9(8), 1476; https://doi.org/10.3390/pr9081476 - 23 Aug 2021
Viewed by 645
Abstract
The use of hydrogen peroxide as an oxidizing agent becomes increasingly important in chemistry. The example of vegetable oil epoxidation is an excellent illustration of the potential of such an agent. This reaction is traditionally performed by Prileschajew oxidation, i.e., by the in [...] Read more.
The use of hydrogen peroxide as an oxidizing agent becomes increasingly important in chemistry. The example of vegetable oil epoxidation is an excellent illustration of the potential of such an agent. This reaction is traditionally performed by Prileschajew oxidation, i.e., by the in situ production of percarboxylic acids. Drawbacks of this approach are side reactions of ring-opening and thermal runaway reactions due to percarboxylic acid instability. One way to overcome this issue is the direct epoxidation by hydrogen peroxide by using γ-alumina. However, the reaction mechanism is not elucidated: does hydrogen peroxide decompose with alumina or oxidize the hydroxyl groups at the surface? The kinetics of hydrogen peroxide consumption with alumina in homogeneous liquid and heterogeneous liquid-liquid systems was investigated to reply to this question. Bayesian inference was used to determine the most probable models. The results obtained led us to conclude that the oxidation mechanism is the most credible for the heterogeneous liquid-liquid system. Full article
(This article belongs to the Special Issue Redesign Processes in the Age of the Fourth Industrial Revolution)
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Article
Adaptive PID Control and Its Application Based on a Double-Layer BP Neural Network
Processes 2021, 9(8), 1475; https://doi.org/10.3390/pr9081475 - 23 Aug 2021
Cited by 1 | Viewed by 642
Abstract
In this paper, focusing on the inconvenience of variable value PID based on manual parameter adjustment for the hydraulic drive unit (HDU) of a legged robot, a method employing double-layer back propagation (BP) neural networks for learning the law of PID control parameters [...] Read more.
In this paper, focusing on the inconvenience of variable value PID based on manual parameter adjustment for the hydraulic drive unit (HDU) of a legged robot, a method employing double-layer back propagation (BP) neural networks for learning the law of PID control parameters is proposed. The first layer is used to learn the relationship between different control parameters and the control performance of the system under various working conditions. The second layer is used to study the relationship between the parameters of the working conditions and the optimizing control parameters under various working conditions. The effectiveness of the proposed control method was verified by simulation and experiment. The results showed that the proposed method can provide a theoretical and experimental basis for the selection of control parameters, and can be extended to similar controllers, therefore possessing engineering application value. Full article
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Article
Numerical Study on the Influence of Well Layout on Electricity Generation Performance of Enhanced Geothermal Systems
Processes 2021, 9(8), 1474; https://doi.org/10.3390/pr9081474 - 23 Aug 2021
Viewed by 553
Abstract
The energy efficiency of the enhanced geothermal system (EGS) measures the economic value of the heat production and electricity generation, and it is a key indicator of system production performance. Presently there is no systematic study on the influence of well layout on [...] Read more.
The energy efficiency of the enhanced geothermal system (EGS) measures the economic value of the heat production and electricity generation, and it is a key indicator of system production performance. Presently there is no systematic study on the influence of well layout on the system energy efficiency. In this work we numerically analyzed the main factors affecting the energy efficiency of EGS using the TOUGH2-EOS1 codes at Gonghe Basin geothermal field, Qinghai province. The results show that for the reservoirs of the same size, the electric power of the three horizontal well system is higher than that of the five vertical well system, and the electric power of the five vertical well system is higher than that of the three vertical well system. The energy efficiency of the three horizontal well system is higher than that of the five vertical well system and the three vertical well system. The reservoir impedance of the three horizontal well system is lower than that of the three vertical well system, and the reservoir impedance of the three vertical well system is lower than that of the five vertical system. The sensitivity analysis shows that well spacing has an obvious impact on the electricity production performance; decreasing well spacing will reduce the electric power, reduce the energy efficiency and only have very slight influence on the reservoir impedance. Fracture spacing has an obvious impact on the electricity production performance; increasing fracture spacing will reduce the electric power and reduce the energy efficiency. Fracture permeability has an obvious impact on the electricity production performance; increasing fracture permeability will improve the energy efficiency and reduce the reservoir impedance. Full article
(This article belongs to the Special Issue Energy Conversion and Storage Processes)
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Article
The Expression of UGT46A1 Gene and Its Effect on Silkworm Feeding
Processes 2021, 9(8), 1473; https://doi.org/10.3390/pr9081473 - 23 Aug 2021
Viewed by 573
Abstract
The silkworm, Bombyx mori, uses a complex olfactory system to determine whether the food is edible. As an odor degrading enzyme, UDP-glycosyltransferase (UGT) participates in the degradation of odor molecules in the olfactory system of the silkworm. By sequencing the whole genome [...] Read more.
The silkworm, Bombyx mori, uses a complex olfactory system to determine whether the food is edible. As an odor degrading enzyme, UDP-glycosyltransferase (UGT) participates in the degradation of odor molecules in the olfactory system of the silkworm. By sequencing the whole genome of the silkworm NB and using comparative genomics methods, we found that UGT46A1 is unique in species that eat mulberry leaves. Bioinformatics shows that its function may be related to the feeding habits of the silkworm. In this study, it was found through quantitative real-time polymerase chain reaction (qRT-PCR) that UGT46A1 was highly expressed in the heads of silkworms, which was consistent with the conjecture that UGT46A1 was involved in silkworm olfactory recognition. RNA interference (RNAi) was used to knock down the expression of UGT46A1. By observing the silkworm’s tendency toward mulberry leaves and food selectivity, it was found that the silkworms that successfully knocked down the UGT46A1 gene altered their feeding habits and that their ability to find food was weakened, but they could eat more leaves of plants other than mulberry leaves. This evidence indicates that UGT46A1 may affect the silkworm’s feeding by influencing the olfactory system of the silkworm. Full article
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Article
Effect of an Increased Particulate COD Load on the Aerobic Granular Sludge Process: A Full Scale Study
Processes 2021, 9(8), 1472; https://doi.org/10.3390/pr9081472 - 23 Aug 2021
Cited by 3 | Viewed by 784
Abstract
High concentrations of particulate COD (pCOD) in the influent of aerobic granular sludge (AGS) systems are often associated to small granule diameter and a large fraction of flocculent sludge. At high particulate concentrations even granule stability and process performance might be compromised. However, [...] Read more.
High concentrations of particulate COD (pCOD) in the influent of aerobic granular sludge (AGS) systems are often associated to small granule diameter and a large fraction of flocculent sludge. At high particulate concentrations even granule stability and process performance might be compromised. However, pilot- or full-scale studies focusing on the effect of real wastewater particulates on AGS are scarce. This study describes a 3-month period of increased particulate loading at a municipal AGS wastewater treatment plant. The pCOD concentration of the influent increased from 0.5 g COD/L to 1.3 g COD/L, by adding an untreated slaughterhouse wastewater source to the influent. Sludge concentration, waste sludge production and COD and nutrient removal performance were monitored. Furthermore, to investigate how the sludge acclimatises to a higher influent particulate content, lipase and protease hydrolytic activities were studied, as well as the microbial community composition of the sludge. The composition of the granule bed and nutrient removal efficiency did not change considerably by the increased pCOD. Interestingly, the biomass-specific hydrolytic activities of the sludge did not increase during the test period either. However, already during normal operation the aerobic granules and flocs exhibited a hydrolytic potential that exceeded the influent concentrations of proteins and lipids. Microbial community analysis also revealed a high proportion of putative hydrolysing and fermenting organisms in the sludge, both during normal operation and during the test period. The results of this study highlight the robustness of the full-scale AGS process, which can bear a substantial increase in the influent pCOD concentration during an extended period. Full article
(This article belongs to the Special Issue Environmental Protection by Aerobic Granular Sludge Process)
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Communication
Assessment of the Effective Impact of Bisphenols on Mitochondrial Activity, Viability and Steroidogenesis in a Dose-Dependency in Human Adrenocortical Carcinoma Cells
Processes 2021, 9(8), 1471; https://doi.org/10.3390/pr9081471 - 23 Aug 2021
Cited by 2 | Viewed by 611
Abstract
In recent years, bisphenol analogues such as bisphenol B (BPB), bisphenol F (BPF), and bisphenol S (BPS) have come to replace bisphenol A (BPA) in food packaging and food containers, since BPA has been shown to leach into food and water, causing numerous [...] Read more.
In recent years, bisphenol analogues such as bisphenol B (BPB), bisphenol F (BPF), and bisphenol S (BPS) have come to replace bisphenol A (BPA) in food packaging and food containers, since BPA has been shown to leach into food and water, causing numerous negative health effects. Although much information on the endocrine activity of BPA is available, a proper human hazard assessment of analogues that are believed to have a less harmful toxicity profile is lacking. The aim of our in vitro study was to assess the potential effect of bisphenol B, F, and S on the biosynthesis of steroid hormones in human H295R adrenocortical carcinoma cells, using the enzyme-linked immunosorbent assay. In addition, we evaluated mitochondrial activity using the MTT test and viability using triple assay. Adrenocortical carcinoma cells were cultivated for 24 h in the presence of bisphenol B, F, or S (0.1, 0.5, 1, 10, 25, 50, 75, 100 μM). We demonstrated that BPB, BPF, and BPS could affect progesterone and testosterone secretion, as well as affect cell mitochondrial, lysosomal, and metabolic activity, as well as plasma membrane integrity, but considerably more detailed and systematic research is required for a better understanding of risks associated with the effects of bisphenols on steroidogenesis. Full article
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Article
Beauveria bassiana Ribotoxin (BbRib) Induces Silkworm Cell Apoptosis via Activating Ros Stress Response
Processes 2021, 9(8), 1470; https://doi.org/10.3390/pr9081470 - 23 Aug 2021
Cited by 1 | Viewed by 598
Abstract
The BbRib gene participates in the infection process of Beauveria bassiana (B. bassiana). It also helps pathogenic fungi to escape and defeat the insect host immune defense system by regulating the innate immune response. However, model insects are rarely used to [...] Read more.
The BbRib gene participates in the infection process of Beauveria bassiana (B. bassiana). It also helps pathogenic fungi to escape and defeat the insect host immune defense system by regulating the innate immune response. However, model insects are rarely used to study the mechanism of fungal ribosomal toxin protein. In this study, BbRib protein was produced by prokaryotic expression and injected into silkworm (Bombyx mori) larvae. The physiological and biochemical indexes of silkworm were monitored, and the pathological effects of BbRib protein on immune tissues of silkworm were examined by Hematoxylin and Eosin (HE) staining. BbRib protein can significantly affect the growth and development of the silkworm, causing poisoning, destroying the midgut and fat body and producing physiological changes. The ROS stress response in the adipose tissue and cells of the silkworm was activated to induce apoptosis. These results indicated that the BbRib gene not only participates in the infection process of B. bassiana, it also helps the pathogenic fungi escape the immune system by regulating the innate immune system of the silkworm, allowing it to break through the silkworm’s immune defense. This study reveals the potential molecular mechanism of BbRib protein to insect toxicity, and provides a theoretical basis and material basis for the development and use of novel insecticidal toxins. Full article
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Article
Controlling Atmospheric Corrosion of Weathering Steel Using Anodic Polarization Protection Technique
Processes 2021, 9(8), 1469; https://doi.org/10.3390/pr9081469 - 23 Aug 2021
Cited by 3 | Viewed by 619
Abstract
The atmospheric corrosion of weathering steels varies as a function of geographic zone, season, and other environmental variables related to that region which the experiments have been done. Meanwhile, rusting is a continuous process, and it is the main corrosion product of atmospheric [...] Read more.
The atmospheric corrosion of weathering steels varies as a function of geographic zone, season, and other environmental variables related to that region which the experiments have been done. Meanwhile, rusting is a continuous process, and it is the main corrosion product of atmospheric corrosion. The current study investigates the effects of rust on weathering steel in the localized region of Digha, a sea resort of West Bengal, India. The investigations have been performed by purposely accelerating the rusting of weathering steel in a laboratory within one week in order to simulate approximately 18 months of actual rusting that can be achieved at field exposure. Anodic polarization of weathering steel comparable to potentiostatic passivation is obtained by shorting weathering steel with nobler metals, such as copper or graphite. The effect of rust formation on corrosion resistance after being immersed in 0.01 M KCl solutions for polished and unpolished samples has been investigated using electrochemical techniques, such as potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). The rusted surfaces’ morphology and composition were characterized using field emission scanning electron microscope (FE-SEM) and energy dispersive X-ray analysis (EDX). Based on the obtained results, it is concluded that the progressive rusting of weathering steel leads to a decrease in corrosion rate. Full article
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Article
Investigating the Impact of Economic Uncertainty on Optimal Sizing of Grid-Independent Hybrid Renewable Energy Systems
Processes 2021, 9(8), 1468; https://doi.org/10.3390/pr9081468 - 23 Aug 2021
Cited by 18 | Viewed by 1130
Abstract
One of the many barriers to decarbonization and decentralization of the energy sector in developing countries is the economic uncertainty. As such, this study scrutinizes economics of three grid-independent hybrid renewable-based systems proposed to co-generate electricity and heat for a small-scale load. Accordingly, [...] Read more.
One of the many barriers to decarbonization and decentralization of the energy sector in developing countries is the economic uncertainty. As such, this study scrutinizes economics of three grid-independent hybrid renewable-based systems proposed to co-generate electricity and heat for a small-scale load. Accordingly, the under-study systems are simulated and optimized with the aid of HOMER Pro software. Here, a 20-year average value of discount and inflation rates is deemed a benchmark case. The techno-economic-environmental and reliability results suggest a standalone solar/wind/electrolyzer/hydrogen-based fuel cell integrated with a hydrogen-based boiler system is the best alternative. Moreover, to ascertain the impact of economic uncertainty on optimal unit sizing of the nominated model, the fluctuations of the nominal discount rate and inflation, respectively, constitute within the range of 15–20% and 10–26%. The findings of economic uncertainty analysis imply that total net present cost (TNPC) fluctuates around the benchmark value symmetrically between $478,704 and $814,905. Levelized energy cost varies from an amount 69% less than the benchmark value up to two-fold of that. Furthermore, photovoltaic (PV) optimal size starts from a value 23% less than the benchmark case and rises up to 55% more. The corresponding figures for wind turbine (WT) are, respectively, 21% and 29%. Eventually, several practical policies are introduced to cope with economic uncertainty. Full article
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Review
Is Gutta-Percha Still the “Gold Standard” among Filling Materials in Endodontic Treatment?
Processes 2021, 9(8), 1467; https://doi.org/10.3390/pr9081467 - 23 Aug 2021
Cited by 5 | Viewed by 1237
Abstract
The paper is an extensive monographic review of the literature, and also uses the results of the authors’ own experimental research illustrating the noticed developmental tendencies of the filling material based on gutta-percha. The whole body of literature proves the correctness of the [...] Read more.
The paper is an extensive monographic review of the literature, and also uses the results of the authors’ own experimental research illustrating the noticed developmental tendencies of the filling material based on gutta-percha. The whole body of literature proves the correctness of the research thesis that this material is the best currently that can be used in endodontics. Caries is one of the most common global infectious diseases. Since the dawn of humankind, the consequence of the disease has been the loss of dentition over time through dental extractions. Both tooth caries and tooth loss cause numerous complications and systemic diseases, which have a serious impact on insurance systems and on the well-being, quality, and length of human life. Endodontic treatment, which has been developing since 1836, is an alternative to tooth extraction. Based on an extensive literature review, the methodology of qualifying patients for endodontic treatment was analyzed. The importance of selecting filling material and techniques for the development and obturation of the root canal during endodontic treatment was described. Particular attention was paid to the materials science aspects and the sequence of phase transformations and precipitation processes, as well as the need to ensure the stoichiometric chemical composition of Ni–Ti alloys, and the vacuum metallurgical processes and material processing technologies for the effects of shape memory and superelasticity, which determine the suitability of tools made of this alloy for endodontic purposes. The phenomena accompanying the sterilization of such tools, limiting the relatively small number of times of their use, play an important role. The methods of root canal preparation and obturation methods through cold side condensation and thermoplastic methods, including the most modern of them, the thermo-hydraulic condensation (THC) technique, were analyzed. An important element of the research hypothesis was to prove the assumption that to optimize the technology of development and obturation of root canals, tests of filling effectiveness are identified by the density and size of the gaps between the root canal wall, and the filling methods used and devices appropriate for material research, using mainly microscopy such as light stereoscopic (LSM) and scanning electron (SEM). The most beneficial preparations were obtained by making a longitudinal breakthrough of 48 natural human teeth, extracted for medical reasons, different from caries, with compliance with all ethical principles in this field. The teeth were prepared using various methods and filled with multiple obturation techniques, using a virtual selection of experimental variants. The breakthroughs were made in liquid nitrogen after a one-sided incision with a narrow gap created by a diamond disc using a materialographic cutter. The best effectiveness of the root canal filling was ensured by the technology of preparing the root canals with K3 rotary nitinol tools and filling the teeth with the THC thermoplastic method using the System B and Obtura III devices with studs and pellets of filling material based on gutta-percha after covering the root canal walls with a thin layer of AH Plus sealant. In this way, the research thesis was confirmed. Full article
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Review
A Review on Recent Progress in Machine Learning and Deep Learning Methods for Cancer Classification on Gene Expression Data
Processes 2021, 9(8), 1466; https://doi.org/10.3390/pr9081466 - 22 Aug 2021
Cited by 1 | Viewed by 1390
Abstract
Data-driven model with predictive ability are important to be used in medical and healthcare. However, the most challenging task in predictive modeling is to construct a prediction model, which can be addressed using machine learning (ML) methods. The methods are used to learn [...] Read more.
Data-driven model with predictive ability are important to be used in medical and healthcare. However, the most challenging task in predictive modeling is to construct a prediction model, which can be addressed using machine learning (ML) methods. The methods are used to learn and trained the model using a gene expression dataset without being programmed explicitly. Due to the vast amount of gene expression data, this task becomes complex and time consuming. This paper provides a recent review on recent progress in ML and deep learning (DL) for cancer classification, which has received increasing attention in bioinformatics and computational biology. The development of cancer classification methods based on ML and DL is mostly focused on this review. Although many methods have been applied to the cancer classification problem, recent progress shows that most of the successful techniques are those based on supervised and DL methods. In addition, the sources of the healthcare dataset are also described. The development of many machine learning methods for insight analysis in cancer classification has brought a lot of improvement in healthcare. Currently, it seems that there is highly demanded further development of efficient classification methods to address the expansion of healthcare applications. Full article
(This article belongs to the Special Issue Advanced Technologies in Biohydrogen and Bioprocesses)
Article
Experimental Investigation on the DPF High-Temperature Filtration Performance under Different Particle Loadings and Particle Deposition Distributions
Processes 2021, 9(8), 1465; https://doi.org/10.3390/pr9081465 - 22 Aug 2021
Cited by 3 | Viewed by 738
Abstract
Based on DPF filtration and regeneration bench, the solid particle emission and high-temperature filtration characteristics of different carbon black particle loadings and particle deposition distributions are studied. The aerosol generator (PAlAS RGB 1000) is used to introduce carbon black particles into the inlet [...] Read more.
Based on DPF filtration and regeneration bench, the solid particle emission and high-temperature filtration characteristics of different carbon black particle loadings and particle deposition distributions are studied. The aerosol generator (PAlAS RGB 1000) is used to introduce carbon black particles into the inlet of a DPF, and the NanoMet3 particle meter is used to measure the solid particle concentration at the inlet and outlet of a DPF to obtain the filtration characteristics. Previous studies found that without inlet carbon black particles, there was an obvious solid particle emission peak at the outlet of the deposited DPF during the heating, and the concentration increased by 1–2 orders of magnitude. In this paper, the high-temperature filtration characteristics under steady-state temperature conditions are studied. It is found that a DPF can reduce the range of inlet fluctuating particles, and with the increase of temperature, the proportion of large solid particles in the outlet particles increases, and the size distribution range decreases. Particle loading has positive and negative effects on the DPF filtration, and the DPF has the optimal particle loading, which makes the comprehensive filtration efficiency improve the highest. The deposition transition section can make the deposition particles in the DPF uniform, but the filtration efficiency is reduced. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System)
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Article
Risk Assessment and Material Suitability Evaluation on Static Equipment of Hydrofluoric Acid Alkylation Unit
Processes 2021, 9(8), 1464; https://doi.org/10.3390/pr9081464 - 21 Aug 2021
Viewed by 677
Abstract
In 2005, a 60 kt/a alkylation (ALK) unit began to resume production in the Second Oil Refinery Plant of Beijing Yanshan Petrochemical Company. There have been many leak cases from pipeline welds, valve body, flange, etc. After a half-year period of operation, production [...] Read more.
In 2005, a 60 kt/a alkylation (ALK) unit began to resume production in the Second Oil Refinery Plant of Beijing Yanshan Petrochemical Company. There have been many leak cases from pipeline welds, valve body, flange, etc. After a half-year period of operation, production process is stable. However, the operation of the hydrofluoric (HF) acid ALK unit has been suffered from corrosion problems. There are no clear answers and references to the following problems. What types of corrosion are currently in the main equipment for HF acid ALK unit? What does cause equipment corrosion? What are the main influencing factors for corrosion? What measures can be taken to reduce the corrosion of HF acid? In this paper, considering the acid-related conditions of the ALK unit, the damage mechanism and damage rate analysis were carried out to calculate the safety risk of the static equipment of the ALK unit. Based on the damage mechanism and failure history, the material suitability of the ALK unit was investigated. The anti-corrosion measures and recommended materials for important corrosion parts of the ALK unit were proposed. It is meaningful for reducing the number of shutdowns of ALK units and maintaining safe and stable operation of the unit. Full article
(This article belongs to the Special Issue Recent Advances in Chemical Process Safety)
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Article
A Techno-Economic Model for Wind Energy Costs Analysis for Low Wind Speed Areas
Processes 2021, 9(8), 1463; https://doi.org/10.3390/pr9081463 - 21 Aug 2021
Cited by 3 | Viewed by 883
Abstract
The global population is moving away from fossil fuel technologies due to their many disadvantages, such as air pollution, greenhouse gases emission, global warming, acid rain, health problems, and high costs. These disadvantages make fossil fuels unsustainable. As a result, renewable energy is [...] Read more.
The global population is moving away from fossil fuel technologies due to their many disadvantages, such as air pollution, greenhouse gases emission, global warming, acid rain, health problems, and high costs. These disadvantages make fossil fuels unsustainable. As a result, renewable energy is becoming more attractive due to its steadily decreasing costs. Harnessing renewable energy promises to meet the present energy demands of the African continent. The enormous renewable energy potential available across the African continent remains largely untapped, especially for wind energy. However, marginal and fair wind speeds and power densities characterize African wind energy resulting in low and unsustainable power in many areas. This research develops a techno-economic model for wind energy cost analysis for a novel, Ferris wheel-based wind turbine. The model is used to techno-economically analyze the siting of wind turbine sites in low wind speed areas on the African continent. The wind turbine’s technical performance is characterized by calculating the annual energy production and the capacity factor using the wind Weibull probability distribution of the cities and theoretical power curve of the wind turbine. Its economic performance is evaluated using annualized financial return on investment, simple payback period, and levelized cost of electricity. The techno-economic model is validated for 21 African cities and shows that the Ferris wheel-based design is very competitive with four current, commercial wind turbines, as well as with other sources of energy. Hence, the new wind turbine may help provide the economical, clean, renewable energy that Africa needs. Full article
(This article belongs to the Special Issue The Process and Modelling of Renewable Energy Sources)
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Article
Design and Performance Test of the Coffee Bean Classifier
Processes 2021, 9(8), 1462; https://doi.org/10.3390/pr9081462 - 21 Aug 2021
Cited by 1 | Viewed by 1013
Abstract
Currently, some coffee production centers still perform classification manually, which requires a very long time, a lot of labor, and expensive operational costs. Therefore, the purpose of this research was to design and test the performance of a coffee bean classifier that can [...] Read more.
Currently, some coffee production centers still perform classification manually, which requires a very long time, a lot of labor, and expensive operational costs. Therefore, the purpose of this research was to design and test the performance of a coffee bean classifier that can accelerate the process of classifying beans. The classifier used consisted of three main parts, namely the frame, the driving force, and sieves. The research parameters included classifier work capacity, power, specific energy, classification distribution and effectiveness, and efficiency. The results showed that the best operating conditions of the coffee bean classifier was a rotational speed of 91.07 rpm and a 16° sieve angle with a classifier working capacity of 38.27 kg/h: the distribution of the seeds retained in the first sieve was 56.77%, the second sieve was 28.12%, and the third sieve was 15.11%. The efficiency of using a classifier was found at a rotating speed of 91.07 rpm and a sieve angle of 16°. This classifier was simple in design, easy to operate, and can sort coffee beans into three classifications, namely small, medium, and large. Full article
(This article belongs to the Topic Modern Technologies and Manufacturing Systems)
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Article
Preparation of Slow-Release Insecticides from Biogas Slurry: Effectiveness of Ion Exchange Resin in the Adsorption and Release of Ammonia Nitrogen
Processes 2021, 9(8), 1461; https://doi.org/10.3390/pr9081461 - 21 Aug 2021
Cited by 2 | Viewed by 714
Abstract
The insecticidal ingredient in a biogas solution being fully utilized by cation exchange resin to produce slow-release insecticide is of great social value. In this work, the feasibility of ammonia nitrogen in a biogas slurry loaded on resin as a slow-release insecticide was [...] Read more.
The insecticidal ingredient in a biogas solution being fully utilized by cation exchange resin to produce slow-release insecticide is of great social value. In this work, the feasibility of ammonia nitrogen in a biogas slurry loaded on resin as a slow-release insecticide was evaluated by studying the effect of adsorption and the slow release of ammonia nitrogen by resin. The effects of the ammonia nitrogen concentration, resin dosage, adsorption time and pH value on the ammonia nitrogen adsorption by the resin were studied. The results showed that the ion exchange resin had a good adsorption effect on the ammonia nitrogen. With the increase of the resin dosage, time and ammonia nitrogen concentration, the adsorption capacity increased at first and then stabilized. The ammonia nitrogen adsorption capacity reached its maximum value (1.13 mg) when the pH value was 7. The adsorption process can be fitted well by the Langmuir isothermal adsorption equation and quasi-second-order kinetic model. Additionally, the release rate of the ammonia nitrogen increased with the increasing sodium chloride concentration. The adsorption capacity of ammonia nitrogen by the D113 (resin type) resin decreased by 15.8% compared with the ammonium chloride solution. The report shows that the ion exchange resin has a good adsorption effect on ammonia nitrogen, which is of guiding significance for expanding the raw materials for slow-release insecticides, improving the utilization rate of biogas slurry and cleaner production of slow-release insecticides from biogas slurry. Additionally, all variables showed statistical differences (p < 0.05). Full article
(This article belongs to the Special Issue New Processes: Working towards a Sustainable Society)
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Article
Experimental Study on Axial Temperature Profile of Jet Fire of Oil-Filled Equipment in Substation
Processes 2021, 9(8), 1460; https://doi.org/10.3390/pr9081460 - 21 Aug 2021
Cited by 2 | Viewed by 624
Abstract
With the widespread use of substations around the world, oil jet fire accidents from transformer oil-filled equipment in substations caused by faults have occurred from time to time. In this paper, a series of transformer oil jet fire experiments are carried out by [...] Read more.
With the widespread use of substations around the world, oil jet fire accidents from transformer oil-filled equipment in substations caused by faults have occurred from time to time. In this paper, a series of transformer oil jet fire experiments are carried out by changing the external heat source (30 cm and 40 cm) and the inner diameter of the container (5 cm, 8 cm and 10 cm) to study the axial centerline temperature distribution of the transformer oil jet fire plume of the transformer oil-filled equipment in the substation. The experiment uses K-type thermocouple, electronic balance and CCD to measure and assess the temperature distribution of the axial centerline of the fire plume of the transformer oil jet. The result demonstrates that the axial centerline temperature of the fire plume increases with the external heat release rate and the inner diameter of the container. In addition, a novel axial temperature distribution prediction model of the transformer oil jet fire plume is established. This model can effectively predict the oil jet fire plume temperature of transformer oil- filling equipment in substations, and provide help for substation fire control. Full article
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Article
Estimating the Remaining Useful Life of Proton Exchange Membrane Fuel Cells under Variable Loading Conditions Online
Processes 2021, 9(8), 1459; https://doi.org/10.3390/pr9081459 - 21 Aug 2021
Viewed by 756
Abstract
The major challenges for the commercialization of proton exchange membrane fuel cells (PEMFCs) are durability and cost. Prognostics and health management technology enable appropriate decisions and maintenance measures by estimating the current state of health and predicting the degradation trend, which can help [...] Read more.
The major challenges for the commercialization of proton exchange membrane fuel cells (PEMFCs) are durability and cost. Prognostics and health management technology enable appropriate decisions and maintenance measures by estimating the current state of health and predicting the degradation trend, which can help extend the life and reduce the maintenance costs of PEMFCs. This paper proposes an online model-based prognostics method to estimate the degradation trend and the remaining useful life of PEMFCs. A non-linear empirical degradation model is proposed based on an aging test, then three degradation state variables, including degradation degree, degradation speed and degradation acceleration, can be estimated online by the particle filter algorithm to predict the degradation trend and remaining useful life. Moreover, a new health indicator is proposed to replace the actual variable loading conditions with the simulated constant loading conditions. Test results using actual aging data show that the proposed method is suitable for online remaining useful life estimation under variable loading conditions. In addition, the proposed prognostics method, which considers the activation loss and the ohmic loss to be the main factors leading to the voltage degradation of PEMFCs, can predict the degradation trend and remaining useful life at variable degradation accelerations. Full article
(This article belongs to the Special Issue Modeling Approaches in Fuel Cells and Electrolyzers)
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Article
Influence of Hydrothermal Pretreatment Temperature on the Hydration Properties and Direct Carbonation Efficiency of Al-Rich Ladle Furnace Refining Slag
Processes 2021, 9(8), 1458; https://doi.org/10.3390/pr9081458 - 21 Aug 2021
Viewed by 561
Abstract
The influence of hydrothermal pretreatment temperature on the hydration products and carbonation efficiency of Al-rich LF slag was investigated. The results showed that the carbonation efficiency was strongly dependent on the morphology of hydration products and the hydration extent of the raw slag. [...] Read more.
The influence of hydrothermal pretreatment temperature on the hydration products and carbonation efficiency of Al-rich LF slag was investigated. The results showed that the carbonation efficiency was strongly dependent on the morphology of hydration products and the hydration extent of the raw slag. Hydrothermal pretreatment at 20 °C or 80 °C favored the formation of flake-shaped products with a higher specific surface area and therefore resulted in a higher CO2 uptake of 20 °C and 80 °C-pretreated slags (13.66 wt% and 10.82 wt%, respectively). However, hydrothermal pretreatment at 40 °C, 60 °C or 100 °C led to the rhombohedral-shaped calcite layer surrounding the unreacted core of the raw slag and the formation of fewer flake-shaped products, resulting in a lower CO2 uptake of 40 °C, 60 °C and 100 °C-pretreated slags (9.21 wt%, 9.83 wt%, and 6.84 wt%, respectively). Full article
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Article
Ultrasound-Assisted Cold Pasteurization in Liquid or SC-CO2
Processes 2021, 9(8), 1457; https://doi.org/10.3390/pr9081457 - 21 Aug 2021
Viewed by 566
Abstract
Various types of chemical and physical protocols are used, thermal treatment in particular, to increase the quality of bulk food products (for example, dates or some sort of nuts) and extend shelf life, and combinations of methods are frequently used to achieve the [...] Read more.
Various types of chemical and physical protocols are used, thermal treatment in particular, to increase the quality of bulk food products (for example, dates or some sort of nuts) and extend shelf life, and combinations of methods are frequently used to achieve the best results. However, the use of these processing methods is not always the best option to preserve the initial taste and appearance of food products. For instance, a product may lose its initial natural appearance and acquire different flavors due to chemical transformations that occur at certain temperatures or when the products are treated with chemicals. Non-thermal treatment methods are called “cold” pasteurization. This is a set of advanced techniques that are based on physical and chemical effects that do not result in the structural food-product transformations caused by heating. We have developed and tested a new technique for efficient food-product processing and cold pasteurization in an ultrasonic field under pressure in an atmosphere of supercritical or subcritical carbon dioxide. A laboratory-scale unit that was designed and built for this purpose has experimentally proven the feasibility of this process and demonstrated high efficiency in suppressing pathogenic flora. Full article
(This article belongs to the Special Issue Redesign Processes in the Age of the Fourth Industrial Revolution)
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Review
Machine Learning in Chemical Product Engineering: The State of the Art and a Guide for Newcomers
Processes 2021, 9(8), 1456; https://doi.org/10.3390/pr9081456 - 20 Aug 2021
Cited by 5 | Viewed by 2197
Abstract
Chemical Product Engineering (CPE) is marked by numerous challenges, such as the complexity of the properties–structure–ingredients–process relationship of the different products and the necessity to discover and develop constantly and quickly new molecules and materials with tailor-made properties. In recent years, artificial intelligence [...] Read more.
Chemical Product Engineering (CPE) is marked by numerous challenges, such as the complexity of the properties–structure–ingredients–process relationship of the different products and the necessity to discover and develop constantly and quickly new molecules and materials with tailor-made properties. In recent years, artificial intelligence (AI) and machine learning (ML) methods have gained increasing attention due to their performance in tackling particularly complex problems in various areas, such as computer vision and natural language processing. As such, they present a specific interest in addressing the complex challenges of CPE. This article provides an updated review of the state of the art regarding the implementation of ML techniques in different types of CPE problems with a particular focus on four specific domains, namely the design and discovery of new molecules and materials, the modeling of processes, the prediction of chemical reactions/retrosynthesis and the support for sensorial analysis. This review is further completed by general guidelines for the selection of an appropriate ML technique given the characteristics of each problem and by a critical discussion of several key issues associated with the development of ML modeling approaches. Accordingly, this paper may serve both the experienced researcher in the field as well as the newcomer. Full article
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Article
Biscuits Polyphenol Content Fortification through Herbs and Grape Seed Flour Addition
Processes 2021, 9(8), 1455; https://doi.org/10.3390/pr9081455 - 20 Aug 2021
Cited by 2 | Viewed by 731
Abstract
The study aimed to verify whether the addition of selected herbs and spices will affect the content of polyphenols in biscuits and their antioxidant capacity, as well as what impact it will have on their sensory properties and attractiveness to consumers. Ground cloves, [...] Read more.
The study aimed to verify whether the addition of selected herbs and spices will affect the content of polyphenols in biscuits and their antioxidant capacity, as well as what impact it will have on their sensory properties and attractiveness to consumers. Ground cloves, cinnamon, mint, and grape flour were added to the biscuits in concentrations of 1.0, 3.0, 5.0, and 10.0%. The total content of polyphenols in spices and biscuit samples was determined using the Folin–Ciocalteau solution and, subsequently, the antioxidant capacity was measured by FRAP (ferric ion reducing antioxidant power) and DPPH (2,2-diphenyl-1-picrylhydrazyl inhibition). Polyphenols were transferred through spices and herbs into the biscuits in all samples and thus their antioxidant capacity was increased. The antioxidant capacity of the control sample measured by the DPPH method was 15.41%, and by the FRAP method 1.02 μmol Trolox/g. There was an increase in antioxidant capacity in all samples with the addition of spices and herbs. The highest increase was recorded in the sample with cloves, namely with the addition of 10% of cloves there was an increase measured by the DPPH method to 92.6% and by the FRAP method to 208.42 μmol Trolox/g. This also corresponds to the measured TPC (Total Polyphenol Content) in the pure clove, which was 219.09 mg GAE/g, and in the samples where the content gradually grew up to 4.51 mg GAE/g in the sample with the addition of 10%, while the polyphenol content of the control sample was 0.2 mg GAE/g. For other parameters, changes were also observed, depending on the addition of spices/herbs. There was a reduction in both texture parameters, hardness and fracturability, depending on the addition of spices/herbs, which was confirmed by both instrumental measurements and sensory analysis. Colour measurements clearly separated the control from the fortified samples, thus confirming the colour changes. The addition of grape flour shows the smallest difference from the control when the overall impression does not change with the addition. In terms of the combination of increased antioxidant capacity and overall consumer acceptability, the addition of cloves at a concentration of 3.0% appears to be the best option. Full article
(This article belongs to the Special Issue Phenolic Profiling and Antioxidant Capacity in Agrifood Products)
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Article
Deep-Sequence–Aware Candidate Generation for e-Learning System
Processes 2021, 9(8), 1454; https://doi.org/10.3390/pr9081454 - 20 Aug 2021
Viewed by 496
Abstract
Recently proposed recommendation systems based on embedding vector technology allow us to utilize a wide range of information such as user side and item side information to predict user preferences. Since there is a lack of ability to use the sequential information of [...] Read more.
Recently proposed recommendation systems based on embedding vector technology allow us to utilize a wide range of information such as user side and item side information to predict user preferences. Since there is a lack of ability to use the sequential information of user history, most recommendation system algorithms fail to predict the user’s preferences more accurately. Therefore, in this study, we developed a novel recommendation system that takes advantage of sequence and heterogeneous information in the candidate-generation process. The principle underlying the proposed recommendation model is that the new sequence based embedding layer in the model catches the sequence pattern of user history. The proposed deep-learning model may improve the prediction accuracy using user data, item data, and sequential information of the user’s profile. Experiments were conducted on datasets of the Korean e-learning platform, and the empirical results confirmed the capability of the proposed approach and its superiority over models that do not use the sequences of the heterogeneous information of users and items for the candidate-generation process. Full article
(This article belongs to the Special Issue Advance in Machine Learning)
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Article
Computational Investigation of the Combined Impact of Nonlinear Radiation and Magnetic Field on Three-Dimensional Rotational Nanofluid Flow across a Stretchy Surface
Processes 2021, 9(8), 1453; https://doi.org/10.3390/pr9081453 - 20 Aug 2021
Cited by 13 | Viewed by 656
Abstract
This comparative study inspects the MHD three-dimensional revolving flow and temperature transmission of a radiative stretching surface. The flow of nanofluid is modeled using the Tiwari and Das model. Water is the base fluid, and the nanoparticles are composed of two different types [...] Read more.
This comparative study inspects the MHD three-dimensional revolving flow and temperature transmission of a radiative stretching surface. The flow of nanofluid is modeled using the Tiwari and Das model. Water is the base fluid, and the nanoparticles are composed of two different types of nanoparticle, i.e., gold and silver (Au and Ag). The non-radiative heat flow notion is examined in a temperature field that results in a nonlinear energy equation. Conformist transformations are used to generate a self-similar arrangement of the leading differential system. The resulting system has an intriguing temperature ratio constraint, which shows whether the flow has a little or significant temperature differential. By using a powerful mathematical technique, numerical results are obtained. The solutions are influenced by both stretching and rotation. The difference in velocity constituents with the elements’ volume fraction is non-monotonic. Results for the rotating nanofluid flow and heat transfer properties for both types of nanoparticles are highlighted with graphs. The impact of physical concentrations, such as heat flux rates and skin friction constants, are examined at the linear extending surface and clarified graphically. Ag-water nanofluid has a high-temperature transfer constant compared to Au-water nanofluid. The velocity profile was also discovered to have a parabolic distribution shape. Full article
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Article
Defect Detection on a Wind Turbine Blade Based on Digital Image Processing
Processes 2021, 9(8), 1452; https://doi.org/10.3390/pr9081452 - 20 Aug 2021
Cited by 2 | Viewed by 716
Abstract
Wind power generation is a widely used power generation technology. Among these, the wind turbine blade is an important part of a wind turbine. If the wind turbine blade is damaged, it will cause serious consequences. The traditional methods of defect detection for [...] Read more.
Wind power generation is a widely used power generation technology. Among these, the wind turbine blade is an important part of a wind turbine. If the wind turbine blade is damaged, it will cause serious consequences. The traditional methods of defect detection for wind turbine blades are mainly manual detection and acoustic nondestructive detection, which are unsafe and time-consuming, and have low accuracy. In order to detect the defects on wind turbine blades more safely, conveniently, and accurately, this paper studied a defect detection method for wind turbine blades based on digital image processing. Because the log-Gabor filter used needed to extract features through multiple filter templates, the number of output images was large. Firstly, this paper used the Lévy flight strategy to improve the PSO algorithm to create the LPSO algorithm. The improved LPSO algorithm could successfully solve the PSO algorithm’s problem of falling into the local optimal solution. Then, the LPSO algorithm and log-Gabor filter were used to generate an adaptive filter, which could directly output the optimal results in multiple feature extraction images. Finally, a classifier based on HOG + SVM was used to identify and classify the defect types. The method extracted and identified the scratch-type, crack-type, sand-hole-type, and spot-type defects, and the recognition rate was more than 92%. Full article
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Article
Antibiotic Resistance Gene Transformation and Ultrastructural Alterations of Lettuce (Lactuca sativa L.) Resulting from Sulfadiazine Accumulation in Culture Solution
Processes 2021, 9(8), 1451; https://doi.org/10.3390/pr9081451 - 20 Aug 2021
Viewed by 678
Abstract
The research herein explored the possible mechanism of toxicity of the antibiotic sulfadiazine (SD) and the related antibiotic resistance gene transformation in lettuce by systematically investigating its growth responses, ultrastructural changes, and antibiotic resistance gene transformation via solution culture experiments. The results showed [...] Read more.
The research herein explored the possible mechanism of toxicity of the antibiotic sulfadiazine (SD) and the related antibiotic resistance gene transformation in lettuce by systematically investigating its growth responses, ultrastructural changes, and antibiotic resistance gene transformation via solution culture experiments. The results showed that SD mainly accumulated in the roots of lettuce at concentrations ranging from 6.48 to 120.87 μg/kg, which were significantly higher than those in leaves (3.90 to 16.74 μg/kg). Lower concentrations of SD (0.5 and 2.0 mg/L) in the culture nutrient solution exerted little effect on lettuce growth, while at SD concentrations higher than 10 mg/L, the growth of lettuce was significantly inhibited, manifesting as shorter root length and lower dry matter yield of whole lettuce plants. Compared with that for the control group, the absolute abundance of bacteria in the root endophyte, rhizosphere, and phyllosphere communities under different concentrations of SD treatment decreased significantly. sul1 and sul2 mainly accumulated in the root endophyte community, at levels significantly higher than those in the leaf endophyte community. Studies of electrolyte leakage and ultrastructural characteristics of root and leaf cells indicated that lettuce grown in culture solutions with high SD concentrations suffered severe damage and disintegration of the cell walls of organs, especially chloroplasts, in leaves. Furthermore, the possible mechanism of SD toxicity in lettuce was confirmed to start with the roots, followed by a free flow of SD into the leaves to destroy the chloroplasts in the leaf cells, which ultimately reduced photosynthesis and decreased plant growth. Studies have shown that antibiotic residues have negative effects on the growth of lettuce and highlight a potential risk of the development and spread of antibiotic resistance in vegetable endophyte systems. Full article
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Article
Evaluation of One-Class Classifiers for Fault Detection: Mahalanobis Classifiers and the Mahalanobis–Taguchi System
Processes 2021, 9(8), 1450; https://doi.org/10.3390/pr9081450 - 20 Aug 2021
Cited by 1 | Viewed by 696
Abstract
Today, real-time fault detection and predictive maintenance based on sensor data are actively introduced in various areas such as manufacturing, aircraft, and power system monitoring. Many faults in motors or rotating machinery like industrial robots, aircraft engines, and wind turbines can be diagnosed [...] Read more.
Today, real-time fault detection and predictive maintenance based on sensor data are actively introduced in various areas such as manufacturing, aircraft, and power system monitoring. Many faults in motors or rotating machinery like industrial robots, aircraft engines, and wind turbines can be diagnosed by analyzing signal data such as vibration and noise. In this study, to detect failures based on vibration data, preprocessing was performed using signal processing techniques such as the Hamming window and the cepstrum transform. After that, 10 statistical condition indicators were extracted to train the machine learning models. Specifically, two types of Mahalanobis distance (MD)-based one-class classification methods, the MD classifier and the Mahalanobis–Taguchi system, were evaluated in detecting the faults of rotating machinery. Their performance for fault detection on rotating machinery was evaluated with different imbalanced ratios of data by comparing with binary classification models, which included classical versions and imbalanced classification versions of support vector machine and random forest algorithms. The experimental results showed the MD-based classifiers became more effective than binary classifiers in cases in which there were much fewer defect data than normal data, which is often common in the real-world industrial field. Full article
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