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Appl. Sci., Volume 10, Issue 7 (April-1 2020) – 366 articles

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Open AccessArticle
Kinematic and Dynamic Modelling for a Class of Hybrid Robots Composed of m Local Closed-Loop Linkages Appended to an n-Link Serial Manipulator
Appl. Sci. 2020, 10(7), 2567; https://doi.org/10.3390/app10072567 (registering DOI) - 08 Apr 2020
Abstract
Recently, more and more hybrid robots have been designed to meet the increasing demand for a wide spectrum of applications. However, development of a general and systematic method for kinematic design and dynamic analysis for hybrid robots is rare. Most publications deal with [...] Read more.
Recently, more and more hybrid robots have been designed to meet the increasing demand for a wide spectrum of applications. However, development of a general and systematic method for kinematic design and dynamic analysis for hybrid robots is rare. Most publications deal with the kinematic and dynamic issues for individual hybrid robots rather than any generalization. Hence, in this paper, we present a novel method for kinematic and dynamic modelling for a class of hybrid robots. First, a generic scheme for the kinematic design of a general hybrid robot mechanism is proposed. In this manner, the kinematic equation and the constraint equations for the robot class are derived in a generalized case. Second, in order to simplify the dynamic modelling and analysis of the complex hybrid robots, a Lemma about the analytical relationship among the generalized velocities of a hybrid robot system is proven in a generalized case as well. Last, examples of the kinematic and dynamic modelling of a newly designed hybrid robot are presented to demonstrate and validate the proposed method. Full article
(This article belongs to the Section Mechanical Engineering)
Open AccessFeature PaperArticle
Electrical Monitoring as a Novel Route to Understanding the Aging Mechanisms of Carbon Nanotube-Doped Adhesive Film Joints
Appl. Sci. 2020, 10(7), 2566; https://doi.org/10.3390/app10072566 (registering DOI) - 08 Apr 2020
Abstract
Carbon fiber-reinforced plastic bonded joints with novel carbon nanotube (CNT) adhesive films were manufactured and tested under different aging conditions by varying the surfactant content added to enhance CNT dispersion. Single lap shear (SLS) tests were conducted in their initial state and after [...] Read more.
Carbon fiber-reinforced plastic bonded joints with novel carbon nanotube (CNT) adhesive films were manufactured and tested under different aging conditions by varying the surfactant content added to enhance CNT dispersion. Single lap shear (SLS) tests were conducted in their initial state and after 1 and 2 months immersed in distilled water at 60 °C. In addition, their electrical response was measured in terms of the electrical resistance change through thickness. The lap shear strength showed an initial decrease due to plasticization of weak hydrogen bonds, and then a partial recovery due to secondary crosslinking. This plasticization effect was confirmed by differential scanning calorimetry analysis with a decrease in the glass transition temperature. The electrical response varied with aging conditions, showing a higher plasticity region in the 1-month SLS joints, and a sharper increase in the case of the non-aged and 2-month-aged samples; these changes were more prevalent with increasing surfactant content. By adjusting the measured electrical data to simple theoretical calculations, it was possible to establish the first estimation of damage accumulation, which was higher in the case of non-aged and 2-month-aged samples, due to the presence of more prevalent brittle mechanisms for the CNT-doped joints. Full article
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Open AccessArticle
Soil Hg Contamination Impact on Earthworms’ Gut Microbiome
Appl. Sci. 2020, 10(7), 2565; https://doi.org/10.3390/app10072565 (registering DOI) - 08 Apr 2020
Abstract
Mercury (Hg) is one of the most toxic heavy metals and is known for its persistence in the environment and potential to accumulate along the food chain. In many terrestrial polluted sites, earthworms are in direct contact with Hg contamination by ingesting large [...] Read more.
Mercury (Hg) is one of the most toxic heavy metals and is known for its persistence in the environment and potential to accumulate along the food chain. In many terrestrial polluted sites, earthworms are in direct contact with Hg contamination by ingesting large quantities of soil. However, little is known about the impact of Hg soil pollution on earthworms’ gut microbiome. In this study, two incubation experiments involving earthworms in soils from a long-term Hg-polluted site were conducted to assess: (1) the effect of soil Hg contamination on the diversity and structure of microbial communities in earthworm, cast and soil samples; and (2) how the gut microbiome of different digestive track parts of the earthworm responds to soil Hg contamination. The large accumulation of total Hg and methyl-Hg within the earthworm tissues clearly impacted the bacterial and fungal gut community structures, drastically decreasing the relative abundance of the dominating gut bacterial class Mollicutes. Hg-tolerant taxa were found to be taxonomically widespread but consistent along the different parts of the earthworm digestive tract. This study revealed that although Hg might not directly affect the health of macro-organisms in the food-web such as earthworms, their metabolism and legacy in the soil might be impacted through changes in their gut microbiome. Full article
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Open AccessArticle
Model and Algorithm of Two-Stage Distribution Location Routing with Hard Time Window for City Cold-Chain Logistics
Appl. Sci. 2020, 10(7), 2564; https://doi.org/10.3390/app10072564 (registering DOI) - 08 Apr 2020
Abstract
Taking cold-chain logistics as the research background and combining with the overall optimisation of logistics distribution networks, we develop two-stage distribution location-routing model with the minimum total cost as the objective function and varying vehicle capacity in different delivery stages. A hybrid genetic [...] Read more.
Taking cold-chain logistics as the research background and combining with the overall optimisation of logistics distribution networks, we develop two-stage distribution location-routing model with the minimum total cost as the objective function and varying vehicle capacity in different delivery stages. A hybrid genetic algorithm is designed based on coupling and collaboration of the two-stage routing and transfer stations. The validity and feasibility of the model and algorithm are verified by conducting a randomly generated test. The optimal solutions for different objective functions of two-stage distribution location-routing are compared and analysed. Results turn out that for different distribution objectives, different distribution schemes should be employed. Finally, we compare the two-stage distribution location-routing to single-stage vehicle routing problems. It is found that a two-stage distribution location-routing system is feasible and effective for the cold-chain logistics network, and can decrease distribution costs for cold-chain logistics enterprises. Full article
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Open AccessArticle
Efficacy of Allicin against Plant Pathogenic Fungi and Unveiling the Underlying Mode of Action Employing Yeast Based Chemogenetic Profiling Approach
Appl. Sci. 2020, 10(7), 2563; https://doi.org/10.3390/app10072563 (registering DOI) - 08 Apr 2020
Abstract
Allicin (diallylthiosulfinate) is the principal organosulfur compound present in freshly damaged garlic tissue which exhibits a wide range of biological actions including antibacterial, antifungal, antiviral and anticancer properties. The antifungal activities of allicin were investigated against plant pathogenic fungi of agriculture importance. Furthermore, [...] Read more.
Allicin (diallylthiosulfinate) is the principal organosulfur compound present in freshly damaged garlic tissue which exhibits a wide range of biological actions including antibacterial, antifungal, antiviral and anticancer properties. The antifungal activities of allicin were investigated against plant pathogenic fungi of agriculture importance. Furthermore, a yeast genome haploinsufficiency screening was also employed to decipher the antifungal mode of action of allicin. Wildtype and 1152 yeast mutant strains (each deprived of one specific allele of an essential gene in a diploid strain) were screened against allicin. Allicin exhibited promising antifungal properties against all the tested plant pathogens. Haploinsufficiency screening revealed three hypersensitive yeast mutants with gene deletions coding for proteins involved in DNA replication, mitochondrial translation and chromatids cohesion. These processes play a vital role in the cell cycle, growth and viability of yeast cells. Taken together, the results of the present study unravel the excellent antifungal activities and mechanisms and modes of action of allicin. These findings also indicate the potential use of allicin as an alternative “green” fungicide (fumigant) in agriculture. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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Open AccessArticle
Adaptive Visual Servoing Control for Hoisting Positioning Under Disturbance Condition
Appl. Sci. 2020, 10(7), 2562; https://doi.org/10.3390/app10072562 (registering DOI) - 08 Apr 2020
Abstract
This paper proposes a visual servo scheme for hoisting positioning under disturbance conditions. In actual hoisting work, disturbances such as equipment and load vibration are inevitable, which brings challenges to the development of a visual servo for hoisting positioning. The main problems are [...] Read more.
This paper proposes a visual servo scheme for hoisting positioning under disturbance conditions. In actual hoisting work, disturbances such as equipment and load vibration are inevitable, which brings challenges to the development of a visual servo for hoisting positioning. The main problems are as follows: (1) the correlation between visual error and disturbance is not considered or well resolved; (2) the disturbance has a great influence on the control stability, but it is difficult to model. At present, there is no detailed research on the above problems. In this paper, the visual error is defined by the image error of the feedback signal based on dynamic equations containing disturbances. An adaptive sliding mode control algorithm is employed to decrease the influence of external disturbance, and the coefficient of the slide surface is established based on the adaptive gain. In view of the belief that it is difficult to model disturbance terms, a nonlinear disturbance observer is introduced to obtain equivalent disturbance. On this basis, an adaptive control algorithm with disturbance compensation is proposed to improve the robustness of the visual servo system. We use Lyapunov’s method to analyze the stability conditions of the system. Compared with the other state-of-the-art methods, the simulation results show that our method has superior performance in convergence, accuracy, and restraining disturbance. Finally, the proposed algorithm is applied to the hoisting platform for experimental research, which proves the effectiveness of the controller. Full article
(This article belongs to the Section Applied Physics)
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Open AccessFeature PaperArticle
Pine Resin Derivatives as Sustainable Additives to Improve the Mechanical and Thermal Properties of Injected Moulded Thermoplastic Starch
Appl. Sci. 2020, 10(7), 2561; https://doi.org/10.3390/app10072561 (registering DOI) - 08 Apr 2020
Abstract
Fully bio-based materials based on thermoplastic starch (TPS) were developed starting from corn starch plasticized with glycerol. The obtained TPS was further blended with five pine resin derivatives: gum rosin (GR), disproportionated gum rosin (dehydroabietic acid, RD), maleic anhydride modified gum rosin (CM), [...] Read more.
Fully bio-based materials based on thermoplastic starch (TPS) were developed starting from corn starch plasticized with glycerol. The obtained TPS was further blended with five pine resin derivatives: gum rosin (GR), disproportionated gum rosin (dehydroabietic acid, RD), maleic anhydride modified gum rosin (CM), pentaerythritol ester of gum rosin (LF), and glycerol ester of gum rosin (UG). The TPS–resin blend formulations were processed by melt extrusion and further by injection moulding to simulate the industrial conditions. The obtained materials were characterized in terms of mechanical, thermal and structural properties. The results showed that all gum rosin-based additives were able to improve the thermal stability of TPS, increasing the degradation onset temperature. The carbonyl groups of gum rosin derivatives were able to interact with the hydroxyl groups of starch and glycerol by means of hydrogen bond interactions producing a significant increase of the glass transition temperature with a consequent stiffening effect, which in turn improve the overall mechanical performance of the TPS-resin injected moulded blends. The developed TPS–resin blends are of interest for rigid packaging applications. Full article
(This article belongs to the Special Issue Sustainable Polymer Technologies for a Circular Economy)
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Open AccessArticle
Augmented Reality as a Didactic Resource for Teaching Mathematics
Appl. Sci. 2020, 10(7), 2560; https://doi.org/10.3390/app10072560 (registering DOI) - 08 Apr 2020
Abstract
This paper is an example of how to use new technologies to produce didactic innovative resources that ease the teaching and learning process of mathematics. This paper is focused on augmented reality technology with the aim of achieving the creation of didactic resources [...] Read more.
This paper is an example of how to use new technologies to produce didactic innovative resources that ease the teaching and learning process of mathematics. This paper is focused on augmented reality technology with the aim of achieving the creation of didactic resources related to the polyhedra taught in a course of compulsory secondary education in Spain. First, we introduce the basis of this technology and present the theoretical framework in which we make an exhaustive analysis that justifies its usage with educative purposes. Secondly, we explain how to build the polyhedra in augmented reality using the Unity game engine and the Vuforia software development kit (SDK), which enables the use of augmented reality. Using both tools, we create an augmented reality application and some augmented reality notes with the purpose of helping in the process of visualization and comprehension of the three-dimensional geometry related to polyhedra. Finally, we design an innovative, didactic proposal for teaching the polyhedra in the third course of compulsory Secondary Education in Spain, using the resources created with the augmented reality technology. Full article
(This article belongs to the Special Issue Augmented Reality: Current Trends, Challenges and Prospects)
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Open AccessArticle
Laboratory Characterization of a Compacted–Unsaturated Silty Sand with Special Attention to Dynamic Behavior
Appl. Sci. 2020, 10(7), 2559; https://doi.org/10.3390/app10072559 (registering DOI) - 08 Apr 2020
Abstract
The dynamic properties of compacted non-cohesive soils are desired not only because of the risk of natural sources of dynamic excitations such as earthquakes, but mostly because of the anthropogenic impact of machines that are working on such soils. These soils are often [...] Read more.
The dynamic properties of compacted non-cohesive soils are desired not only because of the risk of natural sources of dynamic excitations such as earthquakes, but mostly because of the anthropogenic impact of machines that are working on such soils. These soils are often unsaturated, which positively affects the soil’s mechanical properties. The information about the values of these parameters is highly desirable for engineers. In this article, we performed a series of tests, including oedometric tests, resonant column tests, bender element tests, and unsaturated triaxial tests, to evaluate those characteristic parameters. The results showed that sandy silt soil has a typical reaction to dynamic loading in terms of shear modulus degradation and the damping ratio curves’ characteristics, which can be modeled by using empirical equations. We found that the compaction procedure caused an over-consolidation state dependent on the moisture content during compaction effort. The article analyzed the soil properties that impact the maximum shear modulus G0 value. Those properties were suction s, confining pressure σ3, and compaction degree represented by the void ratio function f(e). Full article
(This article belongs to the Section Acoustics and Vibrations)
Open AccessArticle
Adaptive Human–Machine Evaluation Framework Using Stochastic Gradient Descent-Based Reinforcement Learning for Dynamic Competing Network
Appl. Sci. 2020, 10(7), 2558; https://doi.org/10.3390/app10072558 (registering DOI) - 08 Apr 2020
Abstract
Complex problems require considerable work, extensive computation, and the development of effective solution methods. Recently, physical hardware- and software-based technologies have been utilized to support problem solving with computers. However, problem solving often involves human expertise and guidance. In these cases, accurate human [...] Read more.
Complex problems require considerable work, extensive computation, and the development of effective solution methods. Recently, physical hardware- and software-based technologies have been utilized to support problem solving with computers. However, problem solving often involves human expertise and guidance. In these cases, accurate human evaluations and diagnoses must be communicated to the system, which should be done using a series of real numbers. In previous studies, only binary numbers have been used for this purpose. Hence, to achieve this objective, this paper proposes a new method of learning complex network topologies that coexist and compete in the same environment and interfere with the learning objectives of the others. Considering the special problem of reinforcement learning in an environment in which multiple network topologies coexist, we propose a policy that properly computes and updates the rewards derived from quantitative human evaluation and computes together with the rewards of the system. The rewards derived from the quantitative human evaluation are designed to be updated quickly and easily in an adaptive manner. Our new framework was applied to a basketball game for validation and demonstrated greater effectiveness than the existing methods. Full article
(This article belongs to the Section Applied Industrial Technologies)
Open AccessArticle
Conceptual Design of BCI for Mobile Robot Control
Appl. Sci. 2020, 10(7), 2557; https://doi.org/10.3390/app10072557 (registering DOI) - 08 Apr 2020
Abstract
This paper presents an application of Hierarchical Systems (HS) technology in conceptual and detailed design of Brain Computer Interface (BCI) system to control a mobile robot. The BCI is a biomechatronic system that includes biological (brain), computer (control PC), electronic (sensors), visual informatics [...] Read more.
This paper presents an application of Hierarchical Systems (HS) technology in conceptual and detailed design of Brain Computer Interface (BCI) system to control a mobile robot. The BCI is a biomechatronic system that includes biological (brain), computer (control PC), electronic (sensors), visual informatics (LCD—liquid crystal display, GUI—graphic user interface) and executive electro-mechanical (MR—mobile robot) subsystems. Therefore, the conceptual model of the designed BCI system should present connected formal models of the above subsystems presented in the general systemic basis. The structure of the BCI system, its dynamic realization as a unit in its environment and MR environment are presented formally as well. In addition, the conceptual model should also take into account the BCI inter-level relations performed by MR coordinator implemented in the form of the design and control system. Therefore, HS model (and its standard block aed—ancient Greek word) is selected and described as the formal basis of the conceptual model of BCI system in the first part of the given paper. BCI system detailed design is under consideration in the second part of the paper. BCI control system and MR design results, as well as MR control process are also described in the final part of the paper. Full article
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Open AccessArticle
Efficient Deep Learning for Gradient-Enhanced Stress Dependent Damage Model
Appl. Sci. 2020, 10(7), 2556; https://doi.org/10.3390/app10072556 (registering DOI) - 08 Apr 2020
Abstract
This manuscript introduces a computational approach to micro-damage problems using deep learning for the prediction of loading deflection curves. The location of applied forces, dimensions of the specimen and material parameters are used as inputs of the process. The micro-damage is modelled with [...] Read more.
This manuscript introduces a computational approach to micro-damage problems using deep learning for the prediction of loading deflection curves. The location of applied forces, dimensions of the specimen and material parameters are used as inputs of the process. The micro-damage is modelled with a gradient-enhanced damage model which ensures the well-posedness of the boundary value and yields mesh-independent results in computational methods such as FEM. We employ the Adam optimizer and Rectified linear unit activation function for training processes and research into the deep neural network architecture. The performance of our approach is demonstrated through some numerical examples including the three-point bending specimen, shear bending on L-shaped specimen and different failure mechanisms. Full article
(This article belongs to the Special Issue Computational Methods for Fracture Ⅱ)
Open AccessArticle
Better Not To Use Vulnerability’s Reference for Exploitability Prediction
Appl. Sci. 2020, 10(7), 2555; https://doi.org/10.3390/app10072555 (registering DOI) - 08 Apr 2020
Abstract
About half of all exploit codes will become available within about two weeks of the release date of its vulnerability. However, 80% of the released vulnerabilities are never exploited. Since putting the same effort to eliminate all vulnerabilities can be somewhat wasteful, software [...] Read more.
About half of all exploit codes will become available within about two weeks of the release date of its vulnerability. However, 80% of the released vulnerabilities are never exploited. Since putting the same effort to eliminate all vulnerabilities can be somewhat wasteful, software companies usually use different methods to assess which vulnerability is more serious and needs an immediate patch. Recently, there have been some attempts to use machine learning techniques to predict a vulnerability’s exploitability. In doing so, a vulnerability’s related URL, called its reference, is commonly used as a machine learning algorithm’s feature. However, we found that some references contained proof-of-concept codes. In this paper, we analyzed all references in the National Vulnerability Database and found that 46,202 of them contained such codes. We compared prediction performances between feature matrix with and without reference information. Experimental results showed that test sets that used references containing proof-of-concept codes had better prediction performance than ones that used references without such codes. Even though the difference is not huge, it is clear that references having answer information contributed to the prediction performance, which is not desirable. Thus, it is better not to use reference information to predict vulnerability exploitation. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Open AccessFeature PaperArticle
Vitamin D Regulation of a SOD1-to-SOD2 Antioxidative Switch to Prevent Bone Cancer
Appl. Sci. 2020, 10(7), 2554; https://doi.org/10.3390/app10072554 (registering DOI) - 08 Apr 2020
Abstract
Superoxide, a form of reactive oxygen species (ROS), is catabolized by superoxide dismutase (SOD) and contributes to carcinogenesis via the oxidative damage it inflicts on cells. The aim of this research was to analyze the potential vitamin D-mediated regulation of the antioxidative “SOD1-to-SOD2 [...] Read more.
Superoxide, a form of reactive oxygen species (ROS), is catabolized by superoxide dismutase (SOD) and contributes to carcinogenesis via the oxidative damage it inflicts on cells. The aim of this research was to analyze the potential vitamin D-mediated regulation of the antioxidative “SOD1-to-SOD2 switch” within the human MG-63 osteosarcoma model. For this study, real-time PCR analysis was performed using MG-63 cells exposed to metabolically active 1,25(OH)2D3. First, a sustained statistically significant >2-fold suppression of proliferating cell nuclear antigen (PCNA) transcripts was observed after 10 nM but not at 100 nM of 1,25(OH)2D3 treatment, suggesting a cytostatic effect. In order to assess regulators of mitochondrial oxidative phosphorylation, gene expression of COX2 and COX4l1 of the mitochondrial complex IV and antioxidative enzymes (SOD1, SOD2 and Catalase (CAT)) were monitored. For COX2 and COX4l1, no changes in gene expression were observed. However, a concomitant decrease in CAT and SOD1 mRNA, and increase in SOD2 mRNA after 24 h of 10 nM 1,25(OH)2D3 treatment were observed. A ~8-fold increase in SOD2 mRNA was apparent after 48 ours. The significant increase in SOD2 activity in the presence of vitamin D indicates an antioxidant potential and sensitization of vitamin D during osteosarcoma transformation and mitochondrial detoxification over time. Full article
(This article belongs to the Special Issue Vitamin D in Human Health and Disease)
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Open AccessFeature PaperArticle
Phytodepuration of Pyroligneous Liquor: A Case Study
Appl. Sci. 2020, 10(7), 2553; https://doi.org/10.3390/app10072553 (registering DOI) - 08 Apr 2020
Abstract
Wastewaters generated by the pyrolytic process require treatments to reduce the risks of contamination in rivers, lakes, and coastal waters. Utilizing constructed wetlands is one of the possible approaches according to a Circular Economy System. Plant Growth-Promoting Bacteria (PGPB) and Arbuscular Mycorrhizal Fungi [...] Read more.
Wastewaters generated by the pyrolytic process require treatments to reduce the risks of contamination in rivers, lakes, and coastal waters. Utilizing constructed wetlands is one of the possible approaches according to a Circular Economy System. Plant Growth-Promoting Bacteria (PGPB) and Arbuscular Mycorrhizal Fungi (AMF) can improve plant growth and enhance the bioremediation of wastewater. Two experiments were set up: in the first, a pilot mesocosm was designed to evaluate the effects of a consortium of AM fungi and a PGPB strain on Phragmites australis. After 60 days, the highest plant growth was obtained after inoculation with the combination of microorganisms. In the second experiment, a constructed wetland was built to remediate wastewaters from gasification plant. The plants were efficient in scavenging biological oxygen demand (BOD5), chemical oxygen demand (COD), total fat and oils, hydrocarbons, phenols, aldehydes, surfactants, fluorides, sulfites, sulfates, nitrate, and phosphorus. These data suggest that inoculation of P. australis with AMF and PGPB strains significantly improve the depuration process of wastewaters from gasification plants via constructed wetlands. Full article
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Open AccessArticle
Development of an ESCO Risk Assessment Model as a Decision-Making Tool for the Energy Savings Certificates Market Regulator: A Case Study
Appl. Sci. 2020, 10(7), 2552; https://doi.org/10.3390/app10072552 (registering DOI) - 08 Apr 2020
Abstract
This article is focused on developing an Energy Service Company (ESCO) risk assessment model for use by energy savings certificates (ESC) market regulators. This model enables market regulators to determine the appropriate point in time for ESCOs to sell their certificates with the [...] Read more.
This article is focused on developing an Energy Service Company (ESCO) risk assessment model for use by energy savings certificates (ESC) market regulators. This model enables market regulators to determine the appropriate point in time for ESCOs to sell their certificates with the aim of minimizing risk as well as maximizing economic gain yet remain motivated for reducing the cost of energy efficiency technologies. To this end, the interactions between an ESCO and other parties (such as suppliers) in the market in addition to the principles of the energy efficiency performance contract are taken into consideration. Then, appropriate probability distributions have been fitted to the stochastic variables to be applied in the Net Present Value (NPV) function, based on sampled company data. A case study considers a one MW Organic Rankine Cycle (ORC) implementation in Iran’s petrochemical industry. The finding of this study shows if the ESCO is allowed to sell the certificates during the first seven years as well reduce 30% of the investment cost, the expected Net Present Value over Investment Cost (NPV/I) savings will cover more than one cycle. Full article
(This article belongs to the Section Energy)
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Open AccessArticle
Automatic Expanding Mandrel with Air Sensing Device: Design and Analysis
Appl. Sci. 2020, 10(7), 2551; https://doi.org/10.3390/app10072551 (registering DOI) - 08 Apr 2020
Abstract
In precision machining, expanding mandrels are used for jobs with close tolerances. An expanding mandrel consists of a tapered arbor or shaft, with a thin-slotted clamping sleeve or collet made of hardened steel. The internal tapered and external cylindrical surfaces are ground to [...] Read more.
In precision machining, expanding mandrels are used for jobs with close tolerances. An expanding mandrel consists of a tapered arbor or shaft, with a thin-slotted clamping sleeve or collet made of hardened steel. The internal tapered and external cylindrical surfaces are ground to a high degree of accuracy, and the mandrel expands to fit the internal bore of the workpiece. Expanding mandrels are, essentially, wedge mechanisms. This paper proposes an automatic expanding mandrel with a novel force transmission system for high stiffness within a novel air sensing system, which allows detection of the correct part position before starting machining. A computational model for determining the dynamic clamping force of the proposed mechanism is developed and implemented using MATLAB. This model considers the influence of the stiffness behaviors of the collet, force transmission structure and workpiece. Additionally, this paper presents the finite element method analyses which were conducted to check the proposed computational model. The amount of clamping force transmitted by a collet chuck holder depends strongly on: clearances, wedge angle, stiffness of the collet chuck holder and workpiece stiffness. Full article
(This article belongs to the Section Mechanical Engineering)
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Open AccessArticle
Simulation of Radiation and Crop Activity in a Greenhouse Covered with Semitransparent Organic Photovoltaics
Appl. Sci. 2020, 10(7), 2550; https://doi.org/10.3390/app10072550 (registering DOI) - 08 Apr 2020
Abstract
A solution to the problem of reduction of available photosynthetically active radiation (PAR) due to the cover with conventional opaque photovoltaics (PV) of greenhouses is the use of semitransparent PV. The question is how dense the semitransparent PV should be and how dense [...] Read more.
A solution to the problem of reduction of available photosynthetically active radiation (PAR) due to the cover with conventional opaque photovoltaics (PV) of greenhouses is the use of semitransparent PV. The question is how dense the semitransparent PV should be and how dense the coverage should be in order not to burden plant growth. The present paper assesses the effect of the use of semitransparent organic photovoltaics (OPV) on the greenhouse roof cover on the available PAR inside the greenhouse. The method used is to simulate the transmission of radiation through the cover and into the greenhouse with computational fluid dynamics (CFD) using the discrete ordinates (DO) model. Three combinations of OPV/cover that give a normal (perpendicular) transmittance to PAR of 30%, 45%, and 60%, defining the required PV covering, were examined. Then the radiation transmission during eight indicative solar days was simulated. The results are given in terms of available PAR radiation inside the greenhouse and of crop photosynthesis rate, comparing them with the results of a polyethylene cover without OPVs and external conditions. The reduction observed to the mean daily PAR radiation integral for the cases with normal PAR transmittance of 30%, 45%, and 60% in relation to the bare polyethylene (PE) was 77%, 66%, and 52%, respectively while the respective simulated reduction to the daily average photosynthesis rate was 33%, 21%, and 12%, respectively. Finally, the yearly power production from the OPV per greenhouse length meter for the cases with normal PAR transmittance of 30%, 45%, and 60% was 323, 242, and 158 kWh m−1 y−1, respectively. The results of this work could be further used for the optimization of greenhouse design for maximizing the PAR at the crop level. Full article
(This article belongs to the Special Issue Greenhouse Integrated Photovoltaic System Ⅱ)
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Open AccessArticle
Tailoring the FeO/SiO2 Ratio in Electric Arc Furnace Slags to Minimize the Leaching of Vanadium and Chromium
Appl. Sci. 2020, 10(7), 2549; https://doi.org/10.3390/app10072549 (registering DOI) - 08 Apr 2020
Abstract
Based on recently published research on leaching control mechanisms in electric arc furnace (EAF) slags, it is assumed that a FeO/SiO2 ratio of around one leads to low leached V and Cr concentrations. This ratio influences the mineral phase composition of the [...] Read more.
Based on recently published research on leaching control mechanisms in electric arc furnace (EAF) slags, it is assumed that a FeO/SiO2 ratio of around one leads to low leached V and Cr concentrations. This ratio influences the mineral phase composition of the slag toward higher amounts of spinel and a lower solubility of calcium silicate phases by suppressing the formation of magnesiowuestite and highly soluble calcium silicate phases. To evaluate this hypothesis, laboratory and scaled up tests in an EAF pilot plant were performed on slag samples characterized by elevated V and Cr leaching and a high FeO/SiO2 ratio. Prior to the melting experiments, the optimum FeO/SiO2 ratio was calculated via FactSageTM. In the melting experiments, the ratio was adjusted by adding quartz sand, which also decreased the basicity (CaO/SiO2) of the slag. As a reference, remelting experiments without quartz sand addition were conducted and additionally, the influence of the cooling rate of the slag was examined. The remelted (without quartz sand) and the remelted modified slags (with quartz sand) were analyzed chemically and mineralogically and the leaching behavior was investigated. The modification of the slags yielded a minimized release of V and Cr, supporting the hypothesis that the FeO/SiO2 ratio influences the mineralogy and the leaching behavior. Full article
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Open AccessArticle
Transient Study of Flow and Cavitation Inside a Bileaflet Mechanical Heart Valve
Appl. Sci. 2020, 10(7), 2548; https://doi.org/10.3390/app10072548 (registering DOI) - 08 Apr 2020
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Abstract
A mechanical heart valve (MHV) is an effective device to cure heart disease, which has the advantage of long life and high reliability. Due to the hemodynamic characteristics of blood, mechanical heart valves can lead to potential complications such as hemolysis, which have [...] Read more.
A mechanical heart valve (MHV) is an effective device to cure heart disease, which has the advantage of long life and high reliability. Due to the hemodynamic characteristics of blood, mechanical heart valves can lead to potential complications such as hemolysis, which have damage to the blood elements and thrombosis. In this paper, flowing features of the blood in the valve are analyzed and the cavitation mechanism in bileaflet mechanical heart valve (BMHV) is studied. Results show that the water hammer effect and the high-speed leakage flow effect are the primary causes of the cavitation in the valve. Compared with the high-speed leakage flow effect, the water hammer has a greater effect on the cavitation strength. The valve goes through four kinds of working condition within one heart beating period, including, fully opening stage, closing stage and fully closing stage. These four stages, respectively, make up 8.5%, 16.1%, 4.7% and 70.7% of the total period. The cavitation occurs on the fully closing stage. When the valve is in closing stage, the high pressure downstream of the valve lasts for about 20 ms and the high-speed leakage flow lasts for about 200 ms. This study systematically analyzes the causes of cavitation emerged in the process of periodic motion, which proposes the method for characterizing the intensity of the cavitation, and can be referred to for the cavitation suppression of the BHMV and similar valves. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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Open AccessArticle
Automatic Cephalometric Landmark Detection on X-ray Images Using a Deep-Learning Method
Appl. Sci. 2020, 10(7), 2547; https://doi.org/10.3390/app10072547 (registering DOI) - 07 Apr 2020
Viewed by 157
Abstract
Accurate automatic quantitative cephalometry are essential for orthodontics. However, manual labeling of cephalometric landmarks is tedious and subjective, which also must be performed by professional doctors. In recent years, deep learning has gained attention for its success in computer vision field. It has [...] Read more.
Accurate automatic quantitative cephalometry are essential for orthodontics. However, manual labeling of cephalometric landmarks is tedious and subjective, which also must be performed by professional doctors. In recent years, deep learning has gained attention for its success in computer vision field. It has achieved large progress in resolving problems like image classification or image segmentation. In this paper, we propose a two-step method which can automatically detect cephalometric landmarks on skeletal X-ray images. First, we roughly extract a region of interest (ROI) patch for each landmark by registering the testing image to training images, which have annotated landmarks. Then, we utilize pre-trained networks with a backbone of ResNet50, which is a state-of-the-art convolutional neural network, to detect each landmark in each ROI patch. The network directly outputs the coordinates of the landmarks. We evaluate our method on two datasets: ISBI 2015 Grand Challenge in Dental X-ray Image Analysis and our own dataset provided by Shandong University. The experiments demonstrate that the proposed method can achieve satisfying results on both SDR (Successful Detection Rate) and SCR (Successful Classification Rate). However, the computational time issue remains to be improved in the future. Full article
(This article belongs to the Special Issue Machine Learning for Biomedical Application)
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Open AccessArticle
A Case Study about Biomass Torrefaction on an Industrial Scale: Solutions to Problems Related to Self-Heating, Difficulties in Pelletizing, and Excessive Wear of Production Equipment
Appl. Sci. 2020, 10(7), 2546; https://doi.org/10.3390/app10072546 (registering DOI) - 07 Apr 2020
Viewed by 136
Abstract
The search for different forms of biomass that can be used as an alternative to those more traditional ones has faced numerous difficulties, namely those related to disadvantages that the majority of residual forms present. However, these residual forms of biomass also have [...] Read more.
The search for different forms of biomass that can be used as an alternative to those more traditional ones has faced numerous difficulties, namely those related to disadvantages that the majority of residual forms present. However, these residual forms of biomass also have advantages, namely the fact that, by being outside the usual biomass supply chains for energy, they are usually much cheaper, and therefore contribute to a significant reduction in production costs. To improve the less-favorable properties of these biomasses, thermochemical conversion technologies, namely torrefaction, are presented as a way to improve the combustibility of these materials. However, it is a technology that has not yet demonstrated its full potential, mainly due to difficulties in the process of scale-up and process control. In this article it is intended to present the experience obtained over 5 years in the operation of a biomass torrefaction plant with an industrial pilot scale, where all the difficulties encountered and how they were corrected are presented, until it became a fully operational plant. This article, in which a real case study is analyzed, presents in a descriptive way all the work done during the time from when the plant started up and during the commissioning period until the state of continuous operation had been reached. Full article
(This article belongs to the Special Issue Biomass Energy and Biomass as a Clean Renewable Fuel)
Open AccessArticle
Multi-modal Anterior Eye Imager Combining Ultra-High Resolution OCT and Microvascular Imaging for Structural and Functional Evaluation of the Human Eye
Appl. Sci. 2020, 10(7), 2545; https://doi.org/10.3390/app10072545 (registering DOI) - 07 Apr 2020
Viewed by 105
Abstract
To establish complementary information for the diagnosis and evaluation of ocular surface diseases, we developed a multi-modal, non-invasive optical imaging platform by combining ultra-high resolution optical coherence tomography (UHR-OCT) with a microvascular imaging system based on slit-lamp biomicroscopy. Our customized UHR-OCT module achieves [...] Read more.
To establish complementary information for the diagnosis and evaluation of ocular surface diseases, we developed a multi-modal, non-invasive optical imaging platform by combining ultra-high resolution optical coherence tomography (UHR-OCT) with a microvascular imaging system based on slit-lamp biomicroscopy. Our customized UHR-OCT module achieves an axial resolution of ≈2.9 μm in corneal tissue with a broadband light source and an A-line acquisition rate of 24 kHz with a line array CCD camera. The microvascular imaging module has a lateral resolution of 3.5 μm under maximum magnification of ≈187.5× with an imaging rate of 60 frames/s, which is sufficient to image the conjunctival vessel network and record the movement trajectory of clusters of red blood cells. By combining the imaging optical paths of different modules, our customized multi-modal anterior eye imaging platform is capable of performing real-time cross-sectional UHR-OCT imaging of the anterior eye, conjunctival vessel network imaging, high-resolution conjunctival blood flow videography, fluorescein staining and traditional slit-lamp imaging on a single device. With self-developed software, a conjunctival vessel network image and blood flow videography were further analyzed to acquire quantitative morphological and hemodynamics parameters, including vessel fractal dimensions, blood flow velocity and vessel diameters. The ability of our multi-modal anterior eye imager to provide both structural and functional information for ophthalmic clinical applications was demonstrated on a healthy human subject and a keratitis patient. Full article
(This article belongs to the Special Issue Optical Biomedical Imaging)
Open AccessFeature PaperArticle
DC Microgrid System Modeling and Simulation Based on a Specific Algorithm for Grid-Connected and Islanded Modes with Real-Time Demand-Side Management Optimization
Appl. Sci. 2020, 10(7), 2544; https://doi.org/10.3390/app10072544 (registering DOI) - 07 Apr 2020
Viewed by 95
Abstract
This paper presents an algorithm considering both power control and power management for a full direct current (DC) microgrid, which combines grid-connected and islanded operational modes, with real-time demand-side management optimization. The full microgrid is a hybrid dynamic system model consisting of two [...] Read more.
This paper presents an algorithm considering both power control and power management for a full direct current (DC) microgrid, which combines grid-connected and islanded operational modes, with real-time demand-side management optimization. The full microgrid is a hybrid dynamic system model consisting of two interacting parts: continuous-time dynamics and discrete-event dynamics. Such a full microgrid consists of photovoltaic sources, a DC load, battery storage systems, supercapacitor storage, a diesel generator, and a public grid connection, all connected on a DC common bus. This full microgrid is more reliable than a microgrid with only renewable sources or with only traditional energy sources, considering the power constraints imposed by the public grid as well as the sluggish dynamic of the diesel generator, self-discharging characteristic of the supercapacitor, and load shedding optimization. Meanwhile, this algorithm can automatically switch between grid-connected and islanded operational modes to optimize the power of the load shedding, take advantage of renewable energy, and keep the power balance in the full DC microgrid. The results under MATLAB/Simulink verify that the real-time control algorithm can maintain the power balance in real-time for the whole day and satisfy the power management strategy. Full article
(This article belongs to the Section Energy)
Open AccessArticle
Research on Lane Detection Based on Global Search of Dynamic Region of Interest (DROI)
Appl. Sci. 2020, 10(7), 2543; https://doi.org/10.3390/app10072543 (registering DOI) - 07 Apr 2020
Viewed by 106
Abstract
A novel lane detection approach, based on the dynamic region of interest (DROI) selection in the horizontal and vertical safety vision, is proposed to improve the accuracy of lane detection in this paper. The curvature of each point on the edge of the [...] Read more.
A novel lane detection approach, based on the dynamic region of interest (DROI) selection in the horizontal and vertical safety vision, is proposed to improve the accuracy of lane detection in this paper. The curvature of each point on the edge of the road and the maximum safe distance, which are solved by the lane line equation and vehicle speed data of the previous frame, are used to accurately select the DROI at the current moment. Next, the global search of DROI is applied to identify the lane line feature points. Subsequently, the discontinuous points are processed by interpolation. To fulfill fast and accurate matching of lane feature points and mathematical equations, the lane line is fitted in the polar coordinate equation. The proposed approach was verified by the Caltech database, under the premise of ensuring real-time performance. The accuracy rate was 99.21% which is superior to other mainstream methods described in the literature. Furthermore, to test the robustness of the proposed method, it was tested in 5683 frames of complicated real road pictures, and the positive detection rate was 99.07%. Full article
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Open AccessArticle
Many-Body Effects in FeN4 Center Embedded in Graphene
Appl. Sci. 2020, 10(7), 2542; https://doi.org/10.3390/app10072542 (registering DOI) - 07 Apr 2020
Viewed by 106
Abstract
We introduce a computational approach to study porphyrin-like transition metal complexes, bridging density functional theory and exact many-body techniques, such as the density matrix renormalization group (DMRG). We first derive a multi-orbital Anderson impurity Hamiltonian starting from first principles considerations that qualitatively reproduce [...] Read more.
We introduce a computational approach to study porphyrin-like transition metal complexes, bridging density functional theory and exact many-body techniques, such as the density matrix renormalization group (DMRG). We first derive a multi-orbital Anderson impurity Hamiltonian starting from first principles considerations that qualitatively reproduce generalized gradient approximation (GGA)+Uresults when ignoring inter-orbital Coulomb repulsion U and Hund exchange J. An exact canonical transformation is used to reduce the dimensionality of the problem and make it amenable to DMRG calculations, including all many-body terms (both intra- and inter-orbital), which are treated in a numerically exact way. We apply this technique to FeN 4 centers in graphene and show that the inclusion of these terms has dramatic effects: as the iron orbitals become single occupied due to the Coulomb repulsion, the inter-orbital interaction further reduces the occupation, yielding a non-monotonic behavior of the magnetic moment as a function of the interactions, with maximum polarization only in a small window at intermediate values of the parameters. Furthermore, U changes the relative position of the peaks in the density of states, particularly on the iron d z 2 orbital, which is expected to affect the binding of ligands greatly. Full article
Open AccessArticle
Research on Semi-Active Vibration Control of Pipeline Based on Magneto-Rheological Damper
Appl. Sci. 2020, 10(7), 2541; https://doi.org/10.3390/app10072541 (registering DOI) - 07 Apr 2020
Viewed by 107
Abstract
This paper proposes a scheme to control the low-frequency vibration of pipelines by using magneto-rheological (MR) vibration reduction technology. The state equation and the transfer function of the pipeline system are established, and its stability and the sinusoidal excitation response are analyzed. The [...] Read more.
This paper proposes a scheme to control the low-frequency vibration of pipelines by using magneto-rheological (MR) vibration reduction technology. The state equation and the transfer function of the pipeline system are established, and its stability and the sinusoidal excitation response are analyzed. The prototype of MR damper is developed. The dynamic characteristics of MR damper are tested and the double-sigmoid model of MR damper is established. The two-state control, Proportion Integration Differentiation (PID) control and sliding-mode-variable-structure (SMVS) control methods of pipeline vibration using MR damper are analyzed comparatively, and the vibration control laws are deduced. The simulation analyses are carried out to predict the control effect of different pipeline vibration control algorithms. The verification tests through a semi-active measurement and control platform are carried out, and the feasibility and applicability of different pipeline vibration control strategies are analyzed. The test results show that the three kinds of pipeline vibration control methods based on MR damper can effectively control the pipeline vibration. Especially, SMVS control has the best vibration control effect, the pipeline amplitude drop and the acceleration drop can reach 22.31 dB and 16.34 dB respectively, while the amplitude attenuation rate and the acceleration attenuation rate can reach 92.34% and 84.77%, respectively. Full article
(This article belongs to the Section Acoustics and Vibrations)
Open AccessArticle
Leveraging User Comments for Recommendation in E-Commerce
Appl. Sci. 2020, 10(7), 2540; https://doi.org/10.3390/app10072540 (registering DOI) - 07 Apr 2020
Viewed by 102
Abstract
Collaborative filtering recommender systems traditionally recommend products to users solely based on the given user-item rating matrix. Two main issues, data sparsity and scalability, have long been concerns. In our previous work, an approach was proposed to address the scalability issue by clustering [...] Read more.
Collaborative filtering recommender systems traditionally recommend products to users solely based on the given user-item rating matrix. Two main issues, data sparsity and scalability, have long been concerns. In our previous work, an approach was proposed to address the scalability issue by clustering the products using the content of the user-item rating matrix. However, it still suffers from these concerns. In this paper, we improve the approach by employing user comments to address the issues of data sparsity and scalability. Word2Vec is applied to produce item vectors, one item vector for each product, from the comments made by users on their previously bought goods. Through the user-item rating matrix, the user vectors of all the customers are produced. By clustering, products and users are partitioned into item groups and user groups, respectively. Based on these groups, recommendations to a user can be made. Experimental results show that both the inaccuracy caused by a sparse user-item rating matrix and the inefficiency due to an enormous amount of data can be much alleviated. Full article
(This article belongs to the Special Issue New Frontiers in Computational Intelligence)
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Open AccessArticle
Locality-Sensitive Hashing for Information Retrieval System on Multiple GPGPU Devices
Appl. Sci. 2020, 10(7), 2539; https://doi.org/10.3390/app10072539 (registering DOI) - 07 Apr 2020
Viewed by 104
Abstract
It is challenging to build a real-time information retrieval system, especially for systems with high-dimensional big data. To structure big data, many hashing algorithms that map similar data items to the same bucket to advance the search have been proposed. Locality-Sensitive Hashing (LSH) [...] Read more.
It is challenging to build a real-time information retrieval system, especially for systems with high-dimensional big data. To structure big data, many hashing algorithms that map similar data items to the same bucket to advance the search have been proposed. Locality-Sensitive Hashing (LSH) is a common approach for reducing the number of dimensions of a data set, by using a family of hash functions and a hash table. The LSH hash table is an additional component that supports the indexing of hash values (keys) for the corresponding data/items. We previously proposed the Dynamic Locality-Sensitive Hashing (DLSH) algorithm with a dynamically structured hash table, optimized for storage in the main memory and General-Purpose computation on Graphics Processing Units (GPGPU) memory. This supports the handling of constantly updated data sets, such as songs, images, or text databases. The DLSH algorithm works effectively with data sets that are updated with high frequency and is compatible with parallel processing. However, the use of a single GPGPU device for processing big data is inadequate, due to the small memory capacity of GPGPU devices. When using multiple GPGPU devices for searching, we need an effective search algorithm to balance the jobs. In this paper, we propose an extension of DLSH for big data sets using multiple GPGPUs, in order to increase the capacity and performance of the information retrieval system. Different search strategies on multiple DLSH clusters are also proposed to adapt our parallelized system. With significant results in terms of performance and accuracy, we show that DLSH can be applied to real-life dynamic database systems. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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Open AccessArticle
Serial Disulfide Polymers as Cathode Materials in Lithium-Sulfur Battery: Materials Optimization and Electrochemical Characterization
Appl. Sci. 2020, 10(7), 2538; https://doi.org/10.3390/app10072538 (registering DOI) - 07 Apr 2020
Viewed by 100
Abstract
Herein, a series of novel disulfide polymers were synthesized by using the raw materials of diallyl-o-phthalate, tung oil, peanut oil, and styrene. Four kinds of products: Poly (sulfur-diallyl-o-phthalate) copolymer, poly (sulfur-tung oil) copolymer, poly (sulfur-peanut oil) copolymer, and poly (sulfur-styrene-peanut oil) terpolymer were [...] Read more.
Herein, a series of novel disulfide polymers were synthesized by using the raw materials of diallyl-o-phthalate, tung oil, peanut oil, and styrene. Four kinds of products: Poly (sulfur-diallyl-o-phthalate) copolymer, poly (sulfur-tung oil) copolymer, poly (sulfur-peanut oil) copolymer, and poly (sulfur-styrene-peanut oil) terpolymer were characterized, and their solubility was studied and compared. Among the four kinds of disulfide polymers, poly (sulfur-styrene-peanut oil) terpolymer had the best solubility in an organic solvent, and it was chosen to be the active cathode material in Li-S battery. Subsequently, two different conductive additives—conductive carbon black and graphene were separately blended with this terpolymer to prepare two battery systems. The electrochemical performances of the two batteries were compared and analyzed. The result showed that the initial specific capacity of poly (sulfur-styrene-peanut oil) terpolymer (blended with conductive carbon black) battery was 935.88 mAh/g, with the capacity retention rate about 43.5%. Comparingly, the initial specific capacity of poly (sulfur-styrene-peanut oil) terpolymer (blended with graphene) battery was 1008.35 mAh/g, with the capacity retention rate around 60.59%. Therefore, the battery system of poly (sulfur-styrene-peanut oil) terpolymer with graphene showed a more stable cycle performance and better rate performance. This optimized system had a simple and environmental-friendly synthesis procedure, which showed a great application value in constructing cathode materials for the Li-S battery. Full article
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