The alarm data contain abundant fault information related to almost all components of the wind turbine. Reasonable analysis and utilization of alarm data can assist wind farm maintenance personnel in quickly identifying the types of turbine faults, reducing operation and maintenance costs. This paper proposes a clustering analysis method that groups similar alarm sequences with the same fault type. Firstly, the alarm data are preprocessed, where alarm sequences are segmented, and redundant alarms are removed. Then, a domain knowledge-fused Word2vec (DK-Wrod2vec) method is introduced to transform non-numeric alarm codes into numeric vector representations. Finally, new distance metrics are incorporated into the K-means clustering algorithm to improve clustering performance. The performance of the proposed clustering method is assessed by applying it to labeled alarm sequences. The results demonstrate that the clustering performance is the best when using DK-Word2vec and the word rotator’s distance compared with other methods. Additionally, with the optimal parameter combination, the fault types of unlabeled alarm sequences are also analyzed.
{"title":"Clustering Analysis of Wind Turbine Alarm Sequences Based on Domain Knowledge-Fused Word2vec","authors":"Lu Wei, Liliang Wang, Feng Liu, Zheng Qian","doi":"10.3390/app131810114","DOIUrl":"https://doi.org/10.3390/app131810114","url":null,"abstract":"The alarm data contain abundant fault information related to almost all components of the wind turbine. Reasonable analysis and utilization of alarm data can assist wind farm maintenance personnel in quickly identifying the types of turbine faults, reducing operation and maintenance costs. This paper proposes a clustering analysis method that groups similar alarm sequences with the same fault type. Firstly, the alarm data are preprocessed, where alarm sequences are segmented, and redundant alarms are removed. Then, a domain knowledge-fused Word2vec (DK-Wrod2vec) method is introduced to transform non-numeric alarm codes into numeric vector representations. Finally, new distance metrics are incorporated into the K-means clustering algorithm to improve clustering performance. The performance of the proposed clustering method is assessed by applying it to labeled alarm sequences. The results demonstrate that the clustering performance is the best when using DK-Word2vec and the word rotator’s distance compared with other methods. Additionally, with the optimal parameter combination, the fault types of unlabeled alarm sequences are also analyzed.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42069937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nabila Adoui, N. Souilah, H. Bendif, S. Sut, S. Dall'acqua, G. Flamini, Filippo Maggi, Gregorio Peron
Pallenis spinosa (L.) Cass. is a widespread plant in the Mediterranean region. Traditionally, it is used as a medicinal species to treat several ailments, from inflammation to skin injuries. Although the phytochemical content of this plant has already been investigated, there is currently limited data on Algerian P. spinosa. In this work, we focused on volatile compounds and non-volatile secondary metabolites extracted using HS-SPME and methanol from the aerial parts of P. spinosa collected from Northeast Algeria. Volatile constituents were analyzed by GC-MS, while non-volatile compounds were analyzed by NMR and HPLC-MSn. In total, 48 volatile compounds were identified, including sesquiterpene hydrocarbons (65.8%), monoterpene hydrocarbons (16.9%), and oxygenated monoterpenes and sesquiterpenes (8.3% and 6.5%, respectively). β-Chamigrene (16.2%), α-selinene (12.8%), β-pinene (10.6%), and β-caryophyllene (9.2%) were assessed as the main constituents. Concerning non-volatile metabolites, 23 polyphenols were identified (7.26 mg/g DW), and phenolic acids were predominant (5.83 mg/g DW). Tricaffeoylhexaric acid (1.76 mg/g DW), tetracaffeoylhexaric acid (1.41 mg/g DW), 3,5-dicaffeoylquinic acid (1.04 mg/g DW), caffeoyl dihexoside (0.35 mg/g DW), and chlorogenic acid (0.29 mg/g DW) were the most abundant ones. Several known flavonoids, such as tricin and patuletin glycosides, kaempferol, and apigenin, were also identified, and myricetin hexoside was detected in P. spinosa for the first time. Overall, our work is the first to report an exhaustive characterization of volatile and non-volatile secondary metabolites from Algerian P. spinosa. The results represent a step forward in revealing the chemistry of this widespread plant species. Furthermore, they may contribute to rationalizing its traditional medicinal applications and preserve the biodiversity of Algerian flora.
{"title":"Characterization of Polyphenols and Volatile Compounds from Understudied Algerian Pallenis spinosa by HS-SPME-GC-MS, NMR and HPLC-MSn Approaches","authors":"Nabila Adoui, N. Souilah, H. Bendif, S. Sut, S. Dall'acqua, G. Flamini, Filippo Maggi, Gregorio Peron","doi":"10.3390/app131810113","DOIUrl":"https://doi.org/10.3390/app131810113","url":null,"abstract":"Pallenis spinosa (L.) Cass. is a widespread plant in the Mediterranean region. Traditionally, it is used as a medicinal species to treat several ailments, from inflammation to skin injuries. Although the phytochemical content of this plant has already been investigated, there is currently limited data on Algerian P. spinosa. In this work, we focused on volatile compounds and non-volatile secondary metabolites extracted using HS-SPME and methanol from the aerial parts of P. spinosa collected from Northeast Algeria. Volatile constituents were analyzed by GC-MS, while non-volatile compounds were analyzed by NMR and HPLC-MSn. In total, 48 volatile compounds were identified, including sesquiterpene hydrocarbons (65.8%), monoterpene hydrocarbons (16.9%), and oxygenated monoterpenes and sesquiterpenes (8.3% and 6.5%, respectively). β-Chamigrene (16.2%), α-selinene (12.8%), β-pinene (10.6%), and β-caryophyllene (9.2%) were assessed as the main constituents. Concerning non-volatile metabolites, 23 polyphenols were identified (7.26 mg/g DW), and phenolic acids were predominant (5.83 mg/g DW). Tricaffeoylhexaric acid (1.76 mg/g DW), tetracaffeoylhexaric acid (1.41 mg/g DW), 3,5-dicaffeoylquinic acid (1.04 mg/g DW), caffeoyl dihexoside (0.35 mg/g DW), and chlorogenic acid (0.29 mg/g DW) were the most abundant ones. Several known flavonoids, such as tricin and patuletin glycosides, kaempferol, and apigenin, were also identified, and myricetin hexoside was detected in P. spinosa for the first time. Overall, our work is the first to report an exhaustive characterization of volatile and non-volatile secondary metabolites from Algerian P. spinosa. The results represent a step forward in revealing the chemistry of this widespread plant species. Furthermore, they may contribute to rationalizing its traditional medicinal applications and preserve the biodiversity of Algerian flora.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45769116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Real-time detection of satellite remote sensing images is one of the key technologies in the field of remote sensing, which requires not only high-efficiency algorithms, but also low-power and high-performance hardware deployment platforms. At present, the image processing hardware acceleration platform mainly uses an image processing unit (GPU), but the GPU has the problem of large power consumption, and it is difficult to apply to micro-nano satellites and other devices with limited volume, weight, computing power, and power consumption. At the same time, the deep learning algorithm model has the problem of too many parameters, and it is difficult to directly deploy it on embedded devices. In order to solve the above problems, we propose a YOLOv4-MobileNetv3 field programmable gate array (FPGA) deployment scheme based on channel layer pruning. Experiments show that the acceleration strategy proposed by us can reduce the number of model parameters by 91.11%, and on the aerial remote sensing dataset DIOR, the average accuracy of the design scheme in this paper reaches 82.61%, the FPS reaches 48.14, and the average power consumption is 7.2 W, which is 317.88% FPS higher than the CPU and reduces the power consumption by 81.91%. Compared to the GPU, it reduces power consumption by 91.85% and improves FPS by 8.50%. Compared with CPUs and GPUs, our proposed lightweight algorithm model is more energy-efficient and more real-time, and is suitable for application in spaceborne remote sensing image processing systems.
{"title":"Hardware Acceleration of Satellite Remote Sensing Image Object Detection Based on Channel Pruning","authors":"Yong Zhao, Yong Lv, Chao Li","doi":"10.3390/app131810111","DOIUrl":"https://doi.org/10.3390/app131810111","url":null,"abstract":"Real-time detection of satellite remote sensing images is one of the key technologies in the field of remote sensing, which requires not only high-efficiency algorithms, but also low-power and high-performance hardware deployment platforms. At present, the image processing hardware acceleration platform mainly uses an image processing unit (GPU), but the GPU has the problem of large power consumption, and it is difficult to apply to micro-nano satellites and other devices with limited volume, weight, computing power, and power consumption. At the same time, the deep learning algorithm model has the problem of too many parameters, and it is difficult to directly deploy it on embedded devices. In order to solve the above problems, we propose a YOLOv4-MobileNetv3 field programmable gate array (FPGA) deployment scheme based on channel layer pruning. Experiments show that the acceleration strategy proposed by us can reduce the number of model parameters by 91.11%, and on the aerial remote sensing dataset DIOR, the average accuracy of the design scheme in this paper reaches 82.61%, the FPS reaches 48.14, and the average power consumption is 7.2 W, which is 317.88% FPS higher than the CPU and reduces the power consumption by 81.91%. Compared to the GPU, it reduces power consumption by 91.85% and improves FPS by 8.50%. Compared with CPUs and GPUs, our proposed lightweight algorithm model is more energy-efficient and more real-time, and is suitable for application in spaceborne remote sensing image processing systems.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44207455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bruno Robisson, Van-Lap Ngo, L. Marchadier, Mohammed-Farouk Bouaziz, Alexandre Mignonac
Photovoltaic (PV) powered Electric Vehicle Charging Stations (PVCS) have received extensive attention recently due to the complementary relationship of PV energy and electric vehicles. This paper proposes a methodology aimed at assisting a Charging Point Operator (CPO) in determining the size of the main components of such PVCS. The modular structure of the method gives flexibility for possible use on a new sizing problem by modifying key parameters such as the EV charging demand (i.e., arrival/departure times and energy needed to fill the battery), the EV charging strategy or the business model, independently from each other. It is of particular interest for a CPO that sizes many PVCS operated in the same environment (for example, a car park at a workplace). In that case, the CPO first has to apply the method on a representative charging station. Next, he can re-use parts of the obtained results to drastically speed up (from weeks to hours) the sizing of the other charging stations. The proposed method has been applied to the EVCS of an industrial research complex in southern France. The input dataset used to apply the method consists of more than 32,000 charging transactions spanning over 6 years with 350 EV users and 80 charging points. Three charging strategies with different levels of complexity are investigated, including Mean Power, Plug and Charge, and Solar Smart Charging. The considered business model is based on the maximization of the self-production rate. The numerical findings reveal that employing a straightforward charging strategy, such as Mean Power, leads to a substantial reduction of nearly half in the required size of the PV plant compared to the basic Plug and Charge mode. In addition, our analysis demonstrates that Solar Smart Charging has the potential to decrease the PV plant size by nearly three times.
{"title":"PV Sizing for EV Workplace Charging Stations—An Empirical Study in France","authors":"Bruno Robisson, Van-Lap Ngo, L. Marchadier, Mohammed-Farouk Bouaziz, Alexandre Mignonac","doi":"10.3390/app131810128","DOIUrl":"https://doi.org/10.3390/app131810128","url":null,"abstract":"Photovoltaic (PV) powered Electric Vehicle Charging Stations (PVCS) have received extensive attention recently due to the complementary relationship of PV energy and electric vehicles. This paper proposes a methodology aimed at assisting a Charging Point Operator (CPO) in determining the size of the main components of such PVCS. The modular structure of the method gives flexibility for possible use on a new sizing problem by modifying key parameters such as the EV charging demand (i.e., arrival/departure times and energy needed to fill the battery), the EV charging strategy or the business model, independently from each other. It is of particular interest for a CPO that sizes many PVCS operated in the same environment (for example, a car park at a workplace). In that case, the CPO first has to apply the method on a representative charging station. Next, he can re-use parts of the obtained results to drastically speed up (from weeks to hours) the sizing of the other charging stations. The proposed method has been applied to the EVCS of an industrial research complex in southern France. The input dataset used to apply the method consists of more than 32,000 charging transactions spanning over 6 years with 350 EV users and 80 charging points. Three charging strategies with different levels of complexity are investigated, including Mean Power, Plug and Charge, and Solar Smart Charging. The considered business model is based on the maximization of the self-production rate. The numerical findings reveal that employing a straightforward charging strategy, such as Mean Power, leads to a substantial reduction of nearly half in the required size of the PV plant compared to the basic Plug and Charge mode. In addition, our analysis demonstrates that Solar Smart Charging has the potential to decrease the PV plant size by nearly three times.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48907334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaodong Liu, Wenyin Gong, Yuxin Li, Yanchi Li, Xiang Li
In the era of deep learning, representational text-matching algorithms based on BERT and its variant models have become mainstream and are limited by the sentence vectors generated by the BERT model, and the SimCSE algorithm proposed in 2021 has improved the sentence vector quality to a certain extent. In this paper, to address the problem that the SimCSE algorithm has—that the greater the difference in sentence length, the smaller the probability that the sentence pairs are similar—an EdaCSE algorithm is proposed to perturb the sentence length using a simple data enhancement method without affecting the semantics of the sentences. The perturbation is applied to the sentence length by adding meaningless English punctuation marks to the original sentence so that the model no longer tends to recognise sentences of similar length as similar sentences. Based on the BERT series of models, experiments were conducted on five different datasets, and the experiments proved that the EdaCSE method improves an average of 1.67, 0.84, and 1.08 on the five datasets.
{"title":"A Study of Contrastive Learning Algorithms for Sentence Representation Based on Simple Data Augmentation","authors":"Xiaodong Liu, Wenyin Gong, Yuxin Li, Yanchi Li, Xiang Li","doi":"10.3390/app131810120","DOIUrl":"https://doi.org/10.3390/app131810120","url":null,"abstract":"In the era of deep learning, representational text-matching algorithms based on BERT and its variant models have become mainstream and are limited by the sentence vectors generated by the BERT model, and the SimCSE algorithm proposed in 2021 has improved the sentence vector quality to a certain extent. In this paper, to address the problem that the SimCSE algorithm has—that the greater the difference in sentence length, the smaller the probability that the sentence pairs are similar—an EdaCSE algorithm is proposed to perturb the sentence length using a simple data enhancement method without affecting the semantics of the sentences. The perturbation is applied to the sentence length by adding meaningless English punctuation marks to the original sentence so that the model no longer tends to recognise sentences of similar length as similar sentences. Based on the BERT series of models, experiments were conducted on five different datasets, and the experiments proved that the EdaCSE method improves an average of 1.67, 0.84, and 1.08 on the five datasets.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45744722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Zifan, Junyue Lin, Zihan Peng, Yiqing Bo, R. Mittal
(1) Background: Dysphagia affects around 16% of the US population. Diagnostic tests like X-ray barium swallow and endoscopy are used initially to diagnose the cause of dysphagia, followed by high-resolution esophageal manometry (HRM). If the above tests are normal, the patient is classified as functional dysphagia (FD), suggesting esophageal sensory dysfunction. HRM records only the contraction phase of peristalsis, not the distension phase. We investigated the utilization of esophageal distension–contraction patterns for the automatic classification of FD, using artificial intelligent shallow learners. (2) Methods: Studies were performed in 30 healthy subjects and 30 patients with FD. Custom-built software (Dplots 1.0) was used to extract relevant esophageal distension–contraction features. Next, we used multiple shallow learners, namely support vector machines, random forest, K-nearest neighbors, and logistic regression, to determine which had the best performance in terms of accuracy, precision, and recall. (3) Results: In the proximal segment, LR produced the best results, with accuracy of 91.7% and precision of 92.86%, using only distension features. In the distal segment, random forest produced accuracy of 90.5% and precision of 91.1% using both pressure and distension features. (4) Conclusions: Findings emphasize the crucial role of abnormality in the distension phase of peristalsis in FD patients.
{"title":"Unraveling Functional Dysphagia: A Game-Changing Automated Machine-Learning Diagnostic Approach","authors":"A. Zifan, Junyue Lin, Zihan Peng, Yiqing Bo, R. Mittal","doi":"10.3390/app131810116","DOIUrl":"https://doi.org/10.3390/app131810116","url":null,"abstract":"(1) Background: Dysphagia affects around 16% of the US population. Diagnostic tests like X-ray barium swallow and endoscopy are used initially to diagnose the cause of dysphagia, followed by high-resolution esophageal manometry (HRM). If the above tests are normal, the patient is classified as functional dysphagia (FD), suggesting esophageal sensory dysfunction. HRM records only the contraction phase of peristalsis, not the distension phase. We investigated the utilization of esophageal distension–contraction patterns for the automatic classification of FD, using artificial intelligent shallow learners. (2) Methods: Studies were performed in 30 healthy subjects and 30 patients with FD. Custom-built software (Dplots 1.0) was used to extract relevant esophageal distension–contraction features. Next, we used multiple shallow learners, namely support vector machines, random forest, K-nearest neighbors, and logistic regression, to determine which had the best performance in terms of accuracy, precision, and recall. (3) Results: In the proximal segment, LR produced the best results, with accuracy of 91.7% and precision of 92.86%, using only distension features. In the distal segment, random forest produced accuracy of 90.5% and precision of 91.1% using both pressure and distension features. (4) Conclusions: Findings emphasize the crucial role of abnormality in the distension phase of peristalsis in FD patients.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42587858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sangchul Han, Woojin Paik, Myeong-Cheol Ko, Minkyu Park
As multiprocessor (or multicore) real-time systems become popular, there has been much research on multiprocessor real-time scheduling algorithms. This work evaluates EDZL (Earliest Deadline until Zero Laxity), a scheduling algorithm for real-time multiprocessor systems. First, we compare the performance of EDZL schedulability tests. We measure and compare the ratio of task sets admitted by each test. We also investigate the dominance between EDZL schedulability tests and discover that the union of the demand-based test and the utilization-based test is an effective combination. Second, we compare the schedulability of EDZL and EDF(k). We prove that the union of the EDZL schedulability tests dominates the EDF(k) schedulability test, i.e., the union of the EDZL schedulability tests can admit all task sets admitted by the EDF(k) schedulability test. We also compare the schedulability of EDZL and EDF(k) through scheduling simulation by measuring the ratio of successfully scheduled task sets. EDZL can successfully schedule 7.0% more task sets than EDF(k).
{"title":"A Comparative Study on the Schedulability of the EDZL Scheduling Algorithm on Multiprocessors","authors":"Sangchul Han, Woojin Paik, Myeong-Cheol Ko, Minkyu Park","doi":"10.3390/app131810131","DOIUrl":"https://doi.org/10.3390/app131810131","url":null,"abstract":"As multiprocessor (or multicore) real-time systems become popular, there has been much research on multiprocessor real-time scheduling algorithms. This work evaluates EDZL (Earliest Deadline until Zero Laxity), a scheduling algorithm for real-time multiprocessor systems. First, we compare the performance of EDZL schedulability tests. We measure and compare the ratio of task sets admitted by each test. We also investigate the dominance between EDZL schedulability tests and discover that the union of the demand-based test and the utilization-based test is an effective combination. Second, we compare the schedulability of EDZL and EDF(k). We prove that the union of the EDZL schedulability tests dominates the EDF(k) schedulability test, i.e., the union of the EDZL schedulability tests can admit all task sets admitted by the EDF(k) schedulability test. We also compare the schedulability of EDZL and EDF(k) through scheduling simulation by measuring the ratio of successfully scheduled task sets. EDZL can successfully schedule 7.0% more task sets than EDF(k).","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47230528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kui Wen, Xianjun Huang, Rici Tang, Yuanlong Liang, Peiguo Liu
The generation of a strong electromagnetic weapon requires the electromagnetic protection performance of the photoelectric system, including the high shielding and ultra-wideband protection characteristics against strong electromagnetic attacks and superhigh infrared transmittance. This article aims to excite surface plasmons by etching a subwavelength circular structure array run through a metal film. At the same time, the local field enhancement effect based on surface plasmons is used to tune specific wavelengths of light, achieving the goal of enhancing the optical transmission effect. Ulteriorly, the amplitude and position of the infrared response peak are controlled by optimizing the structural geometric parameters to achieve filtering effects in different wavebands. Furthermore, through the inversion calculation of the transmission spectrum of the circle array structure in the visible light band, the different colors of its surface under different parameters can correspond one-to-one to its performance, so as to intuitively identify different filter types and their performance. Meanwhile, the remaining metal film after etching off the circle array structure region constitutes an ultra-wideband shielding layer as a continuous conductor, achieving a shielding efficiency of more than 45 dB in the radar band (1–18 GHz). It is worth noting that the cascaded theory combines ultra-thin metal films with thick substrates to solve the problem of software running for long periods of time and under high loads during the simulation of light propagation. This scheme greatly reduces the error between simulation and practical application.
{"title":"Study on the Filter Integrated with High Transmission and Ultra-Wideband Electromagnetic Shielding Function in the View of Surface Plasmon","authors":"Kui Wen, Xianjun Huang, Rici Tang, Yuanlong Liang, Peiguo Liu","doi":"10.3390/app131810124","DOIUrl":"https://doi.org/10.3390/app131810124","url":null,"abstract":"The generation of a strong electromagnetic weapon requires the electromagnetic protection performance of the photoelectric system, including the high shielding and ultra-wideband protection characteristics against strong electromagnetic attacks and superhigh infrared transmittance. This article aims to excite surface plasmons by etching a subwavelength circular structure array run through a metal film. At the same time, the local field enhancement effect based on surface plasmons is used to tune specific wavelengths of light, achieving the goal of enhancing the optical transmission effect. Ulteriorly, the amplitude and position of the infrared response peak are controlled by optimizing the structural geometric parameters to achieve filtering effects in different wavebands. Furthermore, through the inversion calculation of the transmission spectrum of the circle array structure in the visible light band, the different colors of its surface under different parameters can correspond one-to-one to its performance, so as to intuitively identify different filter types and their performance. Meanwhile, the remaining metal film after etching off the circle array structure region constitutes an ultra-wideband shielding layer as a continuous conductor, achieving a shielding efficiency of more than 45 dB in the radar band (1–18 GHz). It is worth noting that the cascaded theory combines ultra-thin metal films with thick substrates to solve the problem of software running for long periods of time and under high loads during the simulation of light propagation. This scheme greatly reduces the error between simulation and practical application.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46778027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wong Kiong Hung, A. Mahyuddin, S. Sockalingam, Zaleha Shafiei, Mariati Abdul Rahman, Nurul Inaas Mahamad Apandi, Z. D. F. Abdul Ghani, Ahmad Shuhud Irfani Zakaria
Concerns have been raised about the usage of sodium hypochlorite (NaOCl) in endodontics following its toxic effects. Effective ecoproduce (EEP), an organic solution produced through the fermentation of fruit peels, exhibits antibacterial and antibiofilm action, suggesting its potential as an endodontic irrigant. However, studies on its cytotoxicity are limited. This in vitro study aimed to evaluate the cytotoxic effects of EEP at different concentrations and fermentation periods against the MC3T3-E1 cell. EEP derived from orange and pineapple peel waste and fermented for 3 and 6 months was prepared from 100% to 0.78% concentration. Briefly, 2.5% NaOCl was used as the comparison group. Cell viability was analysed using Alamar Blue and Live and Dead Cell assay. A transmission electron microscope (TEM) was used to evaluate ultrastructural changes to the cells. Data analysis was performed using a two-way mixed Analysis of Variance (ANOVA). EEP exhibited concentration-dependent cytotoxicity regardless of the fermentation period (p > 0.05). A concentration below 6.25% was non-cytotoxic and comparable to the negative control (p > 0.05). Live and Dead Cell assay and TEM analysis complement the findings. The mean cell viability of EEP at all concentrations for both fermentation periods was significantly higher than that of 2.5% NaOCl (p < 0.05). Conclusively, 6.25% EEP fermented for 3 and 6 months are non-cytotoxic and can serve as an alternative endodontic irrigants.
{"title":"Cytotoxic Evaluation of Effective Ecoproduce (EEP) as a Potential Root Canal Irrigant: A Preliminary In Vitro Study","authors":"Wong Kiong Hung, A. Mahyuddin, S. Sockalingam, Zaleha Shafiei, Mariati Abdul Rahman, Nurul Inaas Mahamad Apandi, Z. D. F. Abdul Ghani, Ahmad Shuhud Irfani Zakaria","doi":"10.3390/app131810125","DOIUrl":"https://doi.org/10.3390/app131810125","url":null,"abstract":"Concerns have been raised about the usage of sodium hypochlorite (NaOCl) in endodontics following its toxic effects. Effective ecoproduce (EEP), an organic solution produced through the fermentation of fruit peels, exhibits antibacterial and antibiofilm action, suggesting its potential as an endodontic irrigant. However, studies on its cytotoxicity are limited. This in vitro study aimed to evaluate the cytotoxic effects of EEP at different concentrations and fermentation periods against the MC3T3-E1 cell. EEP derived from orange and pineapple peel waste and fermented for 3 and 6 months was prepared from 100% to 0.78% concentration. Briefly, 2.5% NaOCl was used as the comparison group. Cell viability was analysed using Alamar Blue and Live and Dead Cell assay. A transmission electron microscope (TEM) was used to evaluate ultrastructural changes to the cells. Data analysis was performed using a two-way mixed Analysis of Variance (ANOVA). EEP exhibited concentration-dependent cytotoxicity regardless of the fermentation period (p > 0.05). A concentration below 6.25% was non-cytotoxic and comparable to the negative control (p > 0.05). Live and Dead Cell assay and TEM analysis complement the findings. The mean cell viability of EEP at all concentrations for both fermentation periods was significantly higher than that of 2.5% NaOCl (p < 0.05). Conclusively, 6.25% EEP fermented for 3 and 6 months are non-cytotoxic and can serve as an alternative endodontic irrigants.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45571159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fei Zhao, Xi Wang, Beibei Liu, Wenzhuo Sun, Zheng Liu
In order to build a more comprehensive emergency disposal and transportation network system for medical waste, it is necessary to consider various uncertain factors and data characteristics. Therefore, in the context of intelligent transportation, this article considers the uncertainty of the quantity and regional population density of infectious medical waste generation as well as the emergency disposal of infectious medical waste under multi-cycle and multi-objective conditions, and it constructs a multi-cycle emergency disposal logistics network optimization model for infectious medical waste under uncertain conditions. Through deterministic transformation of the model and data mining of the medical waste disposal logistics network in Wuhan, China, the multi-objective model under uncertain conditions was also solved and sensitivity analyzed using the MOPSO-NSGA2 intelligent algorithm, verifying the effectiveness and superiority of the algorithm.
{"title":"Research on Optimization of Medical Waste Emergency Disposal Transportation Network for Public Health Emergencies in the Context of Intelligent Transportation","authors":"Fei Zhao, Xi Wang, Beibei Liu, Wenzhuo Sun, Zheng Liu","doi":"10.3390/app131810122","DOIUrl":"https://doi.org/10.3390/app131810122","url":null,"abstract":"In order to build a more comprehensive emergency disposal and transportation network system for medical waste, it is necessary to consider various uncertain factors and data characteristics. Therefore, in the context of intelligent transportation, this article considers the uncertainty of the quantity and regional population density of infectious medical waste generation as well as the emergency disposal of infectious medical waste under multi-cycle and multi-objective conditions, and it constructs a multi-cycle emergency disposal logistics network optimization model for infectious medical waste under uncertain conditions. Through deterministic transformation of the model and data mining of the medical waste disposal logistics network in Wuhan, China, the multi-objective model under uncertain conditions was also solved and sensitivity analyzed using the MOPSO-NSGA2 intelligent algorithm, verifying the effectiveness and superiority of the algorithm.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42892998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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