Applied Sciences
2076-3417
Cơ quản chủ quản: MDPI , Multidisciplinary Digital Publishing Institute (MDPI)
Lĩnh vực:
Computer Science ApplicationsEngineering (miscellaneous)InstrumentationFluid Flow and Transfer ProcessesProcess Chemistry and TechnologyMaterials Science (miscellaneous)
Các bài báo tiêu biểu
Gold Nanoparticles for Drug Delivery and Cancer Therapy Nanomaterials are popularly used in drug delivery, disease diagnosis and therapy. Among a number of functionalized nanomaterials such as carbon nanotubes, peptide nanostructures, liposomes and polymers, gold nanoparticles (Au NPs) make excellent drug and anticancer agent carriers in biomedical and cancer therapy application. Recent advances of synthetic technique improved the surface coating of Au NPs with accurate control of particle size, shape and surface chemistry. These make the gold nanomaterials a much easier and safer cancer agent and drug to be applied to the patient’s tumor. Although many studies on Au NPs have been published, more results are in the pipeline due to the rapid development of nanotechnology. The purpose of this review is to assess how the novel nanomaterials fabricated by Au NPs can impact biomedical applications such as drug delivery and cancer therapy. Moreover, this review explores the viability, property and cytotoxicity of various Au NPs.
Tập 10 Số 11 - Trang 3824
Generative Oversampling Method for Imbalanced Data on Bearing Fault Detection and Diagnosis In this study, we developed a novel data-driven fault detection and diagnosis (FDD) method for bearing faults in induction motors where the fault condition data are imbalanced. First, we propose a bearing fault detector based on convolutional neural networks (CNN), in which the vibration signals from a test bench are used as inputs after an image transformation procedure. Experimental results demonstrate that the proposed classifier for FDD performs well (accuracy of 88% to 99%) even when the volume of normal and fault condition data is imbalanced (imbalance ratio varies from 20:1 to 200:1). Additionally, our generative model reduces the level of data imbalance by oversampling. The results improve the accuracy of FDD (by up to 99%) when a severe imbalance ratio (200:1) is assumed.
Tập 9 Số 4 - Trang 746
Screening of Antibacterial Activity, Antioxidant Activity, and Anticancer Activity of Euphorbia hirta Linn. Extracts
Tập 10 Số 23 - Trang 8408 - 2020
This study aimed to screen the anticancer and antioxidant potential and antimicrobial activity of methanol, petroleum ether, chloroform, ethyl acetate, butanol of Euphorbia hirta Linn. extracts (EH-Me, EH-PE, EH-Ch, EH-EA and EH-Bu, respectively). The results of 2,2-diphenyl-1-pycrylhydrazyl (DPPH) radical scavenging assay and lipid peroxidation inhibition assay showed that EH-EA was the strongest antioxidant (IC50 = 10.33 ± 0.01 µg/mL; IC50 = 1.48 ± 0.12 µg/mL, respectively) compared to all other extracts. In the antimicrobial activity of the extracts against eight strains of Gram-positive and Gram-negative bacteria using the agar disc diffusion method, we found the EH-EA to be the best antimicrobial agent. Anticancer activities of those extracts were examined by sulforhodamine B (SRB) in vitro cytotoxicity assay on two cancer cell lines, including lung cancer cells NCI-H460 and liver cancer cells Hep G2. EH-EA at concentration of 100 μg/mL has significant inhibitory activity the growth of lung cancer cells NCI-H460 and liver cancer cells Hep G2 compared to all other extracts. Our results suggest that E. hirta Linn. extracts possess significant biological activities, including antimicrobial, antioxidant, and moderate anticancer properties. Our results show that this plant could be a good source for natural antioxidants and a possible pharmaceutical supplement. Among five analyzed extracts, EH-EA extract has the strongest activities, and should be used to determine phytochemicals and mechanisms of these activities.
Displacement Characteristics of Shallow-Buried Large-Section Loess Tunnel with Different Types of Pre-Supports: A Case Study of New Badaling Tunnel Three-bench seven-step excavation method (TSEM) has been widely used in large-section loess tunnels for high-speed railway in China. As the most commonly applied pre-supports, pipe roofs and leading ductules are broadly used in the ground reinforcement of loess tunnels. Their application is to ensure face stability and prevent tunnel collapse during construction. This study focused on the impacts of the TSEM on the ground surface settlement (GSS), as well as the tunnel displacement characteristics for the high-speed railway tunnels with large cross-sections in loess ground. Furthermore, the reinforcement effects of the two kinds of pre-supports were compared in this study. In-situ tests for a total of 12 sections were conducted to reveal the GSSs and displacement characteristics for the shallow-buried large-section loess tunnels. The monitoring results showed that the excavation process plays a significant role on the GSSs and tunnel displacements. A maximum value was observed for the tunnel displacement rate at the excavation of the upper and middle benches, where the face instability or collapse were prone to occur. The GSS trough curves were deviated to the early excavation side, with no conformation to the Gauss distribution. After a series of comparisons, we concluded that the pre-reinforcement effect of the pipe roof is better than that of the leading ductule for the loess tunnels.
Tập 10 Số 1 - Trang 195
Self-Assembled Three-Dimensional Microporous rGO/PNT/Fe3O4 Hydrogel Sorbent for Magnetic Preconcentration of Multi-Residue Insecticides The purpose of this work was to develop a highly selective, sensitive, and reliable method for multi-residual analysis. A three-dimensional microporous reduced graphene oxide/polypyrrole nanotube/magnetite hydrogel (3D-rGOPFH) composite was synthesized and utilized as a magnetic solid-phase extraction (MSPE) sorbent to preconcentrate thirteen insecticides, including five organophosphorus (isocarbophos, quinalphos, phorate, chlorpyrifos, and phosalone), two carbamates (pirimor and carbaryl), two triazoles (myclobutanil and diniconazole), two pyrethroids (lambda-cyhalothrin and bifenthrin), and two organochlorines (2, 4′-DDT and mirex), from vegetables, followed by gas chromatography-tandem mass spectrometry. This method exhibited several major advantages, including simultaneous enrichment of different types of insecticides, no matrix effect, high sensitivity, and ease of operation. This is ascribed to the beneficial effects of 3D-rGOPFH, including the large specific surface (237 m2 g−1), multiple adsorption interactions (hydrogen bonding, electrostatic, π–π stacking and hydrophobic interaction force), appropriate pore size distribution (1–10 nm), and the good paramagnetic property. Under the optimal conditions, the analytical figures of merit were obtained as: linear dynamic range of 0.1–100 ng g−1 with determination coefficients of 0.9975–0.9998; limit of detections of 0.006–0.03 ng g−1; and the intra-day and inter-day relative standard deviations were 2.8–7.1% and 3.5–8.8%, respectively. Recoveries were within the range of 79.2 to 109.4% for tomato, cucumber, and pakchoi samples at the fortification levels of 5, 25, and 50 ng g−1. This effective and robust method can be applied for determining multi-classes of insecticide residues in vegetables.
Tập 10 Số 16 - Trang 5665
Model-Based Requirements Management in Gear Systems Design Based On Graph-Based Design Languages For several decades, a wide-spread consensus concerning the enormous importance of an in-depth clarification of the specifications of a product has been observed. A weak clarification of specifications is repeatedly listed as a main cause for the failure of product development projects. Requirements, which can be defined as the purpose, goals, constraints, and criteria associated with a product development project, play a central role in the clarification of specifications. The collection of activities which ensure that requirements are identified, documented, maintained, communicated, and traced throughout the life cycle of a system, product, or service can be referred to as “requirements engineering”. These activities can be supported by a collection and combination of strategies, methods, and tools which are appropriate for the clarification of specifications. Numerous publications describe the strategy and the components of requirements management. Furthermore, recent research investigates its industrial application. Simultaneously, promising developments of graph-based design languages for a holistic digital representation of the product life cycle are presented. Current developments realize graph-based languages by the diagrams of the Unified Modelling Language (UML), and allow the automatic generation and evaluation of multiple product variants. The research presented in this paper seeks to present a method in order to combine the advantages of a conscious requirements management process and graph-based design languages. Consequently, the main objective of this paper is the investigation of a model-based integration of requirements in a product development process by means of graph-based design languages. The research method is based on an in-depth analysis of an exemplary industrial product development, a gear system for so-called “Electrical Multiple Units” (EMU). Important requirements were abstracted from a gear system specification list and were analyzed in detail. As a second basis, the research method uses a conscious expansion of graph-based design languages towards their applicability for requirements management. This expansion allows the handling of requirements through a graph-based design language model. The first two results of the presented research consist of a model of the gear system and a detailed model of requirements, both modelled in a graph-based design language. Further results are generated by a combination of the two models into one holistic model.
Tập 7 Số 11 - Trang 1112
Gear Shift Coordinated Control Strategy Based on Motor Rotary Velocity Regulation for a Novel Hybrid Electric Vehicle This paper proposes a novel hybrid power system to improve the shift quality of a hybrid electric vehicle (HEV). After selecting a typical shift scheme, the study focused on the motor rotary velocity control algorithm and coordinated control strategy for the motor and clutch. The effects of various control algorithms on different target rotary velocities were analyzed, and a proportional-integral-derivative (PID)–bang-bang–fuzzy compound intelligent algorithm for a motor rotary velocity control system was investigated. In addition, to address the problems of the long synchronizing time required for the rotary velocity and large sliding friction work, which affect the shift quality during the process of engaging the clutch, a coordinated control strategy for the motor rotary velocity and clutch oil pressure was investigated. The research results showed that, compared with a gear shift coordinated control strategy based on a PID control algorithm, the strategy based on the PID–bang-bang–fuzzy compound intelligent control algorithm proposed here reduced the shift time and clutch slipping friction work by 35.7% and 19.2%, respectively.
Tập 11 Số 24 - Trang 12118
Development of a Hybrid Electric Vehicle Simulation Tool with a Rule-Based Topology The performance of hybrid electric vehicles (HEVs) greatly depends on the various sub-system components and their architecture, and designers need comprehensive reviews of HEVs before vehicle investigation and manufacturing. Simulations facilitate development of virtual prototypes that make it possible to rapidly see the effects of design modifications, avoiding the need to manufacture multiple expensive physical prototypes. To achieve the required levels of emissions and hardware costs, designers must use control strategies and tools such as computational modeling and optimization. However, most hybrid simulation tools do not share their principles and control logic algorithms in the open literature. With this motivation, the author developed a hybrid simulation tool with a rule-based topology. The major advantage of this tool is enhanced flexibility to choose different control and energy management strategies, enabling the user to explore a wide range of hybrid topologies. The tool provides the user with the ability to modify any sub-system according to one’s own requirements. In addition, the author introduces a simple logic control for a rule-base strategy as an example to show the flexibility of the tool in allowing the adaptation of any logic algorithm by the user. The results match the experimental data quite well. Details regarding modeling principle and control logic are provided for the user’s benefit.
Tập 11 Số 23 - Trang 11319
Impact of Environmental Conditions on the Degree of Efficiency and Operating Range of PV-Powered Electric Vehicles This paper investigates the impact of environmental conditions on the possible output power of photovoltaic (PV) installations on top of hybrid electric vehicles (HEVs) and battery-powered electric vehicles (BEVs). First, we discuss the characteristics and behavior of PV cells in order to provide an understanding of the energy source that we aim to integrate into vehicles. Second, we elaborate on how PV cells and panels can be simulated to estimate the potential extension of the electrical driving range (ERE) of BEVs and HEVs. In particular, we concentrate on the impact of the vehicle’s curved roof surface on the possible output of the PV installation. In this research, we present considerations for vehicles in both parking and driving conditions. More precisely, we demonstrate how the frequently changing environmental conditions that occur while driving represent significant challenges to the control of the operating voltage of PV cells. As the area for deploying PV cells on top of an electric vehicle is limited, attention needs to be paid to how to optimize and maximize the degree of efficiency of PV-powered electric vehicles.
Tập 12 Số 3 - Trang 1232
Project and Development of a Reinforcement Learning Based Control Algorithm for Hybrid Electric Vehicles Hybrid electric vehicles are, nowadays, considered as one of the most promising technologies for reducing on-road greenhouse gases and pollutant emissions. Such a goal can be accomplished by developing an intelligent energy management system which could lead the powertrain to exploit its maximum energetic performances under real-world driving conditions. According to the latest research in the field of control algorithms for hybrid electric vehicles, Reinforcement Learning has emerged between several Artificial Intelligence approaches as it has proved to retain the capability of producing near-optimal solutions to the control problem even in real-time conditions. Nevertheless, an accurate design of both agent and environment is needed for this class of algorithms. Within this paper, a detailed plan for the complete project and development of an energy management system based on Q-learning for hybrid powertrains is discussed. An integrated modular software framework for co-simulation has been developed and it is thoroughly described. Finally, results have been presented about a massive testing of the agent aimed at assessing for the change in its performance when different training parameters are considered.
Tập 12 Số 2 - Trang 812