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Bioactive coumarin crude mixture extraction from crude Calophyllum inophyllum oil by microwave-assisted extraction

AIP Conference Proceedings 2024年第1期2774卷

作者： Brilian Pamungkas Setiyo Gunawan Hakun W. Aparamarta Department of Chemical Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia

Mangroves have crucial roles in the coastal ecosystem and human life. It provides a place and shelter for marine biota to reproduce and live, prevent abrasion, prevent seawater intrusion and many more. Indonesia is the largest mangrove habitat globally, with a population of more than 20% of the world’s total mangrove population. Calophyllum is one of the mangrove’s genera. Genus Calophyllum consists of nearly 187 species, 179 distributed in the Indo-Malaysia Region, with C. inophyllum (nyamplung) being the most important species due to its economic values and usability of all of the plant parts. Due to its bioactive compound and high oil contents, it can be used as traditional medicine and biodiesel feedstock. One bioactive compound that has been identified is coumarin. It is a bioactive compound with many health benefits like antimicrobial, anti-inflammatory, and anticancer. A few studies have discussed the extraction of coumarin compounds by more advanced methods of environmental-friendly solvents. This research was conducted by extracting bioactive coumarin mixture with a more advanced extracti on method, microwave-assisted extraction (MAE) with environmental-friendly solvent, ethanol-water combined with n-hexane. This study aims to extract bioactive coumarin mixture by microwave assisted extraction (MAE) method with ethanol-water combined with n-hexane as solvents, to investigate the optimum conditions for extraction, and to study the yield, antioxidant activity, and total phenolic compound (TPC) extracted under optimum conditions. Determination of optimum conditions is carried out by one factor at a time (OFAT) method with variable concentrations of ethanol 30%, 70%, 90%, and 96%, microwave power 150W, 300W, and 450W, and time extraction of 3 min, 6 min, and 9 min. From the result of the conducted study, it is concluded that the optimum conditions to extract bioactive coumarin crude mixture from nyamplung oil are 90% of ethanol concentration, 150W of microwave

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Rare earth oxides and their supported noble metals in application of environmental catalysis

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Journal of Rare Earths 2020年第8期38卷 819-839,I0001页

作者： Zhiquan Hou Wenbo Pei Xing Zhang Kunfeng Zhang Yuxi Liu Jiguang Deng Lin Jing Hongxing Dai Beijing Key Laboratory for Green Catalysis and Separation Key Laboratory of Beijing on Regional Air Pollution ControlKey Laboratory of Advanced Functional MaterialsEducation Ministry of ChinaLaboratory of Catalysis Chemistry and NanoscienceDepartment of Chemistry and Chemical EngineeringCollege of Environmental and Energy EngineeringBeijing University of TechnologyBeijing 100124China

Volatile organic compounds(VOCs),methane,carbon monoxide,soot,automotive exhaust,and nitrogen oxides are harmful to the atmosphere and human *** is urgent to strictly control their *** catalysis is an effective pathway for the removal of these pollutants,and the critical issue is the development of novel and high-performance *** this review,we briefly summarize the preparation methods,physicochemical properties,catalytic activities,and related reaction mechanisms for the above pollutants removal of the rare earth oxides,mixed rare earth oxide,rare earth oxidesupported noble metal,and mixed rare earth oxide-supported noble metal catalysts that have been investigated by our group and other *** was found that catalytic performance was associated with the factors,such as specific surface area,pore structure,particle size and dispersion,adsorbed oxygen species concentration,reducibility,reactant activation ability or interaction between metal nanoparticles and ***,we also envision the development trend of such a topic in future work.

关键词： Volatile organic compound Atmospheric pollutant Rare earth oxide Mixed rare earth oxide Supported noble metal catalyst Porous mixed rare earth oxide

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A network-based bioinformatic analysis for identifying potential repurposable active molecules in different types of human cancers

A network-based bioinformatic analysis for identifying poten...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Martina Brunetti Paola Paci Giulia Fiscon Department of Computer Control and Management Engineering "A. Ruberti" Sapienza University of Rome Rome Italy Karolinska Institutet Stockholm Sweden Institute for Systems Analysis and Computer Science "A. Ruberti" National Research Council of Rome Rome Italy

Drug repurposing, also known as drug repositioning, is the process of identifying novel therapeutic indications for existing drugs, offering a cost-effective and time-efficient strategy to drug discovery. In this context, we developed a network-based algorithm, named SAveRUNNER (Searching off-lAbel dRUg aNd NEtwoRk), which predicts drug-disease associations by accounting for the interaction between the drug targets and disease-associated genes in the human interactome, implementing a novel network-based similarity measure that prioritizes associations between drugs and diseases locating in the same network neighborhoods. Following its successful applications to different disorders (such as viral infections and neurological diseases), in this study, we applied SAveRUNNER on a panel of 13 types of cancers using both disease-associated genes downloaded from widely-used databases and from gene expression data.

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Analysis of the downlink channel estimation methods in communication systems with SCMA 2

Analysis of the downlink channel estimation methods in commu...

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2nd International Conference on Electrical, Communication and Computer engineering, ICECCE 2020

作者： Pokamestov, Dmitriy Kryukov, Yakov Rogozhnikov, Evgeniy Mishchenko, Evgeniy Brovkin, Andrew Tomsk State University of Control Systems and Radioelectronic Department of Telecommunications and Basic Principles of Radio Engineering Tomsk Russia

ISBN: (纸本)9781728171166

Sparse Code Multiple Access (SCMA) is a nonorthogonal multiple access method that provides high bandwidth, noise immunity and a larger number of connections compared to traditional methods such as Orthogonal Frequency Division Multiple Access (OFDMA). One of the important problems that negatively affects the quality of communication is multipath propagation. To combat it, various equalization techniques are used, which provide for channel estimation by the receiver. In this paper, we consider three methods for estimating the downlink transmission channel for communication systems with SCMA. The first method is an assessment by reference (pilot) signals, which is classical and is widely used in modern telecommunication systems. The second method under consideration is the assessment of the regenerated information symbols. The third is a blind channel estimate. Algorithms are proposed for all three methods, and mathematical modeling is performed. The results of the dependences of the mean square error and bit error on the signal-to-noise ratio are obtained. © 2020 IEEE.

关键词： Channel estimation

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Multilingual web traffic forecasting for network management using artificial intelligence techniques

Results in Engineering

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Results in engineering 2025年 26卷

作者： Samaan, Sama Salam Korial, Ayad E. Sarra, Raniya R. Humaidi, Amjad J. Computer Engineering Department University of Technology- Iraq Baghdad10001 Iraq Control and Systems Engineering Department University of Technology- Iraq Baghdad10001 Iraq

Web traffic forecasting is critical for ensuring an effective allocation of network resources for websites to avoid potential congestion and maintain service quality. Analyzing traffic forecasts helps network operators plan for future capacity needs to accommodate unexpected traffic loads. Multilingual web platforms present unique challenges due to varying traffic patterns across several languages. In this paper, modular architecture is proposed for multilingual web traffic forecasting using deep learning models. The architecture consists of multiple processes, from collecting the traffic data of the targeted website to preparing the data to be in a suitable form to feed the deep learning models. This study explores time-series forecasting methods using three deep learning models: long short-term memory (LSTM), gated recurrent units (GRU), and convolutional neural networks (CNN). A comprehensive dataset was collected from the BBC World Service websites in three languages—English, Arabic, and Persian—spanning the period from January 2017 to July 2024. The performance of the employed deep learning models is evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), relative root mean square error (RRMSE), and R-squared (R²). Results show that the CNN model outperformed the GRU and LSTM models in accuracy and variance explanation across all three language datasets. The CNN model demonstrated superior performance, achieving R² scores of 0.980, 0.989, and 0.994;MAE values of 47,195, 5090, and 6714;RRMSE values of 1.43 %, 1.90 %, and 1.86 %;and RMSE values of 61,372, 6342, and 9376 for the English, Arabic, and Persian websites, respectively. These results highlight the potential of deep learning models in capturing complicated patterns of multilingual web platforms, making them suitable for real-world network management. © 2025

关键词： Convolutional neural networks

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Classification of EEG signals based on CNN-Transformer model

Classification of EEG signals based on CNN-Transformer model

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IEEE International Conference on Mechatronics and Automation

作者： Jianwei Liu Enzeng Dong Jigang Tong Sen Yang Shengzhi Du Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology 391 Binshui West Road Tianjin China Department of Electrical Engineering Tshwane University of Technology Pretoria South Africa

Brain-computer interfaces (BCI) based on EEG have attracted extensive research and attention worldwide, while motor imagery (MI), mental arithmetic (MA), and P300 event-related potentials are a few of the more commonly used *** Transformer(ViT) is a new Transformer model that has superior global processing power compared to Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN).In this study, we propose a hybrid CNN-Transformer based model that uses CNN to convolve EEG signals in time and space, followed by ViT for global processing, and finally optimizes the model using 10-run $\times 10$-fold cross-validation and validates it on a publicly available dataset of 29 subjects. Final accuracies of 87.23% and 90.79% were achieved on the MI and MA tasks, respectively. Compared to other literature, the model achieved higher classification accuracies.

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Data-driven Polytopic Output Synchronization of Heterogeneous Multi-agent systems from Noisy Data

arXiv

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arXiv 2023年

作者： Li, Yifei Liu, Wenjie Sun, Jian Wang, Gang Xie, Lihua Chen, Jie The National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing100081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore The Department of Control Science and Engineering Tongji University Shanghai201804 China

This paper proposes a novel approach to addressing the output synchronization problem in unknown heterogeneous multi-agent systems (MASs) using noisy data. Unlike existing studies that focus on noiseless data, we introduce a distributed data-driven controller that enables all heterogeneous followers to synchronize with a leader’s trajectory. To handle the noise in the state-input-output data, we develop a data-based polytopic representation for the MAS. We tackle the issue of infeasibility in the set of output regulator equations caused by the noise by seeking approximate solutions via constrained fitting error minimization. This method utilizes measured data and a noise-matrix polytope to ensure near-optimal output synchronization. Stability conditions in the form of data-dependent semidefinite programs are derived, providing stabilizing controller gains for each follower. The proposed distributed data-driven control protocol achieves near-optimal output synchronization by ensuring the convergence of the tracking error to a bounded polytope, with the polytope size positively correlated with the noise bound. Numerical tests validate the practical merits of the proposed data-driven design and theory. © 2023, CC BY.

关键词： Multi agent systems

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Model Predictive Temperature and Humidity control of Greenhouse with Ventilation

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Procedia Computer Science 2021年 192卷 212-221页

作者： Kazuhisa Ito Tsubasa Tabei Department of Machinery and Control Systems College of Systems Engineering and Science Shibaura Institute of Technology 307 Fukasaku Minuma Saitama 3378570 JAPAN Mechanical Engineering Course Graduate School of Engineering and Science Shibaura Institute of Technology 307 Fukasaku Minuma Saitama 3378570 JAPAN

Facility gardening with complex environmental control systems has potential in improving productivity and producing high value-added agricultural products; however, its introduction is expensive. Thus, this study proposes a greenhouse temperature and humidity control system using relatively inexpensive heaters, humidifiers, and ventilation fans. Humidity control is expected to promote photosynthesis and prevent plant disease. The concept of model predictive control (MPC) was applied to a small greenhouse to minimise the sum of squared errors. Compared with the two conventional methods, the simulation results showed that MPC reduced the relative RMS error of the temperature and humidity deficit to 23.5% and 13.1%, respectively.

关键词： Model predictive control Greenhouse Temperature Humidity deficit Ventilation

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Consumers’ Perception and Knowledge of Food Additives in Senegal: A Pilot Study

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Open Journal of Applied Sciences 2024年第1期14卷 38-50页

作者： Alé Kane Hamidou Mbodji Papa Mamadou Dit Doudou Sylla Alioune Sow Abdoulaye Tamba Malick Mbengue Mady Cissé Laboratory of Biological Agronomic and Food Sciences and Complex Systems Modelling (LABAAM) University Gaston Berger (UGB) Saint-Louis Senegal UFR of Agronomic Sciences Aquaculture and Food Technology (UFR S2ATA) UGB Saint-Louis Senegal Department of Chemical Engineering and Applied Biology University Cheikh Anta Diop of Dakar Dakar Senegal

Food safety has become a major concern for consumers, as well as a priority for regulatory authorities. Faced with the growing industrial and domestic use of food additives, many questions are being asked and concerns are being felt by consumers around the world. Consumer perception defines the acceptability or rejection of food products, and has an impact on consumption patterns and behavior. To assess the level of knowledge and perception of food additives, a pilot study was carried out on a sample of 200 people in Dakar and Saint-Louis. A questionnaire was used to assess the acceptance or rejection, use and impact of food additives by consumers in Senegal. The results revealed several aspects. On the whole, the people surveyed expressed great mistrust and even rejection of these substances added to food products. This consumer perception is shared throughout the world, as indicated in numerous surveys. It also emerges from this study that, although most consumers are aware of the existence of these additives and their uses in the home, they feel that the use of these substances in industrial production is too excessive. What’s more, consumers associate food additives with numerous pathologies such as cancer, diabetes, hypertension, stroke and even sexual impotence. For some of these indexed pathologies, scientific studies have reached the same conclusions, although controversy still persists. On the other hand, for some of the other adverse effects mentioned, no cause-and-effect relationship has been scientifically demonstrated. In these latter cases, it seems that negative communication, misinformation and misconceptions have a major influence on consumer perception of food additives.

关键词： Consumer Survey Food Additives Knowledge Perception Senegal

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Investigation of the Nh3 Consumption and H2o/No Formation During the Oxidation of N-Heptane and Iso-Octane Blended with Ammonia

SSRN

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SSRN 2023年

作者： Zheng, Dao Peng, Zhimin He, Dong Zhang, Meng Li, Jidong Ding, Yanjun Du, Yanjun School of Control and Computer Engineering North China Electric Power University Beijing102206 China State Key Laboratory of Power Systems Department of Energy and Power Engineering Tsinghua University Beijing100084 China Advanced Propulsion Laboratory Department of Modern Mechanics University of Science and Technology of China Hefei230026 China University of Chinese Academy of Sciences School of Engineering Sciences Beijing100049 China Tsinghua University China

Adding highly active fuels with ammonia is a compromising way to increase the mixture's reactivity. However, there are very few studies blending ammonia with large hydrocarbons, such as n-heptane and isooctane. In this study, the NH3, NO, and H2O time-histories were simultaneously measured during the oxidation of ammonia/n-heptane and ammonia/isooctane mixtures (equivalence ratio Φ ~ 1.2) in a shock tube. For the ammonia/n-heptane mixture, a reduced kinetics model, the Wang 2023 model, shows the best predictions in terms of the mixture reactivity and the H2O production but underpredicts the NO plateau. For the ammonia/isooctane mixture, the CRECK_TPRF_Alcohols_NOx (CRECK) model is the only available kinetics model containing ammonia and isooctane mechanisms. The CRECK model captures the H2O plateau but underpredicts the ammonia/isooctane mixture reactivity and the NO plateau. Detailed analyses are conducted based on the Wang 2023 and CRECK models. Rate-of-production (ROP) analyses reveal that: the consumption or formation pathways of the three species in the two models are basically the same but the magnitudes of the ROPs are quite different, especially for the NO formation;the reaction of ethylene or propylene with NH2 radical in the Wang 2023 model also contributes significantly to the NH3 consumption but they are not considered in the CRECK model. Sensitivity analyses show that: H + O2 = O + OH is the most promoting reaction for both mixtures and models;however, several reactions show strong effects in one mixture while having little effect in another mixture, or even playing an opposite effect. After modifying or adding some key reactions, the Wang 2023 and CRECK models get significantly improved in predicting the species' time-history during the oxidation of the ammonia/n-heptane or ammonia/isooctane mixture. © 2023, The Authors. All rights reserved.

关键词： Shock tubes

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