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Improving Microgrid reliability and Efficiency Through Energy Storage Systems with a Pyramidal dilation Attention Convolutional Neural Network for renewable Energy Integration

Improving Microgrid Reliability and Efficiency Through Energ...

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Sustainable Expert Systems (ICSES), International Conference on

作者： Bondu Vijayakumar K.E. Purushothamarn Priyanka Khabiya Akriti Garg rajesha N S. Kaliappan Department of Electrical and Electronics Engineering Madanapalle Institute of Technology & Science Annamayya Andhra Pradesh India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamil Nadu India Department of Computer Science Engineering Mandsaur University Mandsaur Madhya Pradesh India Department of Electrical Engineering Mahatma Jyotiba Phule Rohilkhand University Bareilly Uttar Pradesh India Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Division of Research and Development Lovely Professional University Jalandhar Delhi Punjab India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Microgrid (MG) design and deployment are heavily reliant on reliability. Integrating renewable energy sources (rESs) into power grids poses considerable challenges for maintaining grid reliability due to their intermittent nature. This paper proposes a novel approach to enhance grid stability by incorporating Energy Storage Systems (ESS) coupled with Pyramidal dilation Attention Convolutional Neural Network (PdACNN). The goal of the proposed method is to improve efficiency and lower electricity costs. The proposed PdACNN optimizes the control of Energy Storage Systems by providing more trustworthy forecasts of energy demand as well as supply. By, then the proposed method is implemented in MATLAB and evaluated their performance with various existing methods. The PdACNN method surpasses existing techniques in both efficiency and cost-effectiveness. It achieves a high efficiency of 95.7 % and reduces total electricity costs to $650/kWh, outperforming the Artificial Neural Network (ANN), and recurrent NN (rNN) and Convolutional NN (CNN) methods.

关键词： renewable energy sources Costs Electricity Microgrids Power system stability Stability analysis reliability Convolutional neural networks Thermal stability Energy storage

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Cyanobacteria-based near-infrared light-excited self-supplying oxygen system for enhanced photodynamic therapy of hypoxic tumors

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Nano research 2021年第3期14卷 667-673页

作者： Yinghua Zhang Huifang Liu Xinyue dai Hang Li Xiaohan Zhou Shizhu Chen Jinchao Zhang Xing-Jie Liang Zhenhua Li College of Chemistry&Environmental Science Analytical Chemistry Key Laboratory of Hebei ProvinceChemical Biology Key Laboratory of Hebei ProvinceHebei UniversityBaoding071002China Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education Institute of Life Science and Green DevelopmentHebei UniversityBaoding071002China College of Pharmaceutical Science Key Laboratory of Pharmaceutical Quality Control of Hebei ProvinceHebei UniversityBaoding071002China Beijing Pharmaceutical Group Company Limited Beijing100101China The National Institutes of Pharmaceutical R&D Co. Ltd.China Resources Pharmaceutical Group LimitedBeijing102206China CAS Key Laboratory for Biological Effects of Nanomaterials and Nanosafety National Center for Nanoscience and TechnologyBeijing100190China

Tumor hypoxia has been considered to induce tumor cell resistance to radiotherapy and anticancer chemotherapy,as well as predisposing for increased tumor ***,strategies for the eradication of the hypoxic tumor are highly *** therapy(PdT)is a new technique that can be used to treat tumors using laser irradiation to photochemically activate a *** to traditional radiotherapy and chemotherapy,photodynamic therapy has many advantages,such as good selectivity,low toxicity,and less trauma and ***,PdT is oxygen-dependent,and the lack of oxygen in hypoxic tumors renders photodynamic therapy ***,the earliest photosynthetic oxygen-generating organisms,can utilize water as an electron donor to reduce CO_(2) into organic carbon compounds along with continuously releasing oxygen under *** by this,herein,cyanobacteria were used as a living carrier of photosensitizer conjugated upconversion nanoparticles(UCNP)to construct a self-supplying oxygen PdT *** in the PdT efficiency for hypoxic tumors can be achieved as a result of in situ oxygen production by cyanobacteria under near-infrared(NIr)light using UCNP as a light harvesting antenna.A successful demonstration of this concept would be of great significance and could open the door to a new generation of carrier systems in the field of hypoxia-targeted drug transport platforms.

关键词： self-supplying oxygen cyanobacteria hypoxic tumor photodynamic therapy upconversion nanoparticles

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Investigation on cutting fluid use in finish milling of polylactide (PLA) 3d-printed parts

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Procedia CIrP 2025年 133卷 656-661页

作者： Margaux Lorenzoni Laurent Spitaels Edouard rivière-Lorphèvre Jérémy Odent rachid M’Saoubi Liam Cloëz Michaël Fontaine François ducobu Machine Design and Production Engineering Lab – Research Institute for Materials Science and Engineering University of Mons Place du Parc 20 7000 Mons Belgium Laboratory of Polymeric and Composite Materials (LMPC) – Center of Innovation and Research in Materials and Polymers (CIRMAP) University of Mons Place du Parc 20 7000 Mons Belgium R&D Material and Technology Development Seco Tools AB Björnbacksvägen 2 SE-737 82 Fagersta Sweden Department of Mechanical Engineering Sciences - Division of Production and Materials Engineering Lund University Ole Römers väg 1 SE-221 00 Lund Sweden FEMTO-ST Institute – Applied Mechanics Dept. Université de Franche-Comté – SUPMICROTECH – CNRS Rue de l’épitaphe 24 F-25000 Besançon France

Fused Filament Fabrication (FFF) is an additive manufacturing process based on Material Extrusion (MEX) of polymeric filament. This manufacturing technology is commonly used for personalized production applications and prototyping, allowing to obtain customized parts with complex geometries at a low cost. However, this production technique has its limitations regarding dimensional accuracy and surface roughness of the final parts. To overcome these limitations, finish milling is considered to be a promising technique as it is widely used for metallic parts. Yet, the specific thermal properties of polymers such as low thermal conductivity and low melting temperature are adding a challenge in the determination of optimal cutting conditions. In this context, the use of cutting fluid could be the key to keep the material from melting during milling. Therefore, this paper proposes to compare the impact of using a compressed air flow to dry conditions on the cutting forces and the surface quality obtained on 3d-printed polylactide (PLA) parts. The qualification test of the tool-material couple standard (NF E 66-520-6) will be used as a guideline to determine the relevance of cutting fluid use for cutting conditions varying around an operating point. Moreover, simulated cutting forces using a mechanistic model will be compared to experimental data to evaluate the applicability of the model.

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Metabolite Profiling of Herbal Medicines using an Artificial Intelligence Approach-A Concise review

Metabolite Profiling of Herbal Medicines using an Artificial...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Ajay S Shet Somasundaram r Sravan Kumar G S. Kaliappan S.r. ramprasad Maloth Srinivas Department of CSE Canara Engineering College Mangalore Karnataka India Management Studies Department Kongu Engineering College Erode TN India Dept. of CSE (Cyber Security) CVR College of Engineering Hyderabad Telangana India Division of Research and Development Lovely Professional University Jalandhar Punjab India Dept. of CSE School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai TN India Dept. of CSE (AIML) St. Martin's Engineering College Secunderabad Telangana India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

Artificial intelligence (AI) is being developed extremely swiftly in medicine. A structured review should be conducted to comprehend the current status of AI models since they have been introduced in Traditional medicine to Investigate and classify the present applications of AI in TM. Following the technique suggested by the Joanna Briggs Institute, a thorough scoping review was conducted. To find papers on AI and CAM, three databases were searched: PubMed, Embase, and Cochrane Library. Studies published only in English since 2000 are taken into account. Those without mention of traditional medicine or AI methods were also disqualified, as were studies that were not peer-reviewed. All pertinent studies were located using a comprehensive search technique. This review demonstrated the potential use of AI models in TM; nevertheless, to develop AI in TM in the era of digital health, future research should concentrate on validating and verifying the models by carrying out a sizable clinical investigation.

关键词： reviews databases Machine learning Predictive models Prediction algorithms Knowledge discovery data models Libraries data mining Artificial intelligence

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Catalytic hydrogenation of disinfection by-product bromate by cobalt and nickle prussian blue analogues with borohydride

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Korean Journal of Chemical Engineering 2023年第12期40卷 2876-2885页

作者： Mao, Po-Hsin Park, Young-Kwon Lin, Yi-Feng Thanh, Bui Xuan Tuan, duong dinh Ebrahimi, Afshin Lisak, Grzegorz Tangcharoen, Thanit Lin, Kun-Yi Andrew Department of Environmental Engineering & Innovation and Development Center of Sustainable Agriculture National Chung Hsing University 250 Kuo-Kuang Road Taichung Taiwan School of Environmental Engineering University of Seoul Seoul02504 Korea Republic of Department of Chemical Engineering and R&D Center for Membrane Technology Chung Yuan Christian University 200 Chung Pei Rd. Chungli Taoyuan Taiwan Faculty of Environment and Natural Resources Ho Chi Minh City University of Technology VNU-HCM 268 Ly Thuong Kiet District 10 Ho Chi Minh City700000 Viet Nam International School Thai Nguyen University Thai Nguyen city250000 Viet Nam Environment Research Center and Department of Environmental Health Engineering Isfahan University of Medical Sciences Isfahan Iran Residues and Resource Reclamation Centre Nanyang Environment and Water Research Institute Nanyang Technological University Singapore637141 Singapore School of Civil and Environmental Engineering Nanyang Technological University Singapore639798 Singapore Department of Basic Science and Physical Education Faculty of Science at Sriracha Kasetsart University Sriracha Campus Chonburi Thailand

As disinfection is employed extensively, disinfection by-product bromate has become an emerging environmental issue due to its carcinogenic toxicity. For developing an effective alternative approach for reducing bromate, cobalt and nickel-based Prussian Blue (PB) analogues are proposed here for incorporating a convenient reducing agent, NaBH4 (i.e., a H2-rich reagent) for reducing bromate to bromide as cobalt and nickel are recognized as effective metals for catalyzing hydrolysis of NaBH4, and PB exhibits versatile catalytic activity. While CoPB and NiPB are comprised of the same crystalline structure, CoPB exhibits slightly higher specific surface area, more reductive surface, and more superior electron transfer than NiPB, enabling CoPB to accelerate bromate reduction. CoPB also exhibits a higher affinity towards NaBH4 than NiPB based on density functional theory calculations. Moreover, CoPB also exhibits a relatively low activation energy (i.e., 59.5 kJ/mol) of bromate reduction than NiPB (i.e., 63.2 kJ/mol). Furthermore, bromate reduction by CoPB and NiPB could be also considerably enhanced under acidic conditions, and CoPB and NiPB could still effectively remove bromate even in the presence of nitrate, sulfate and phosphate. CoPB and NiPB are also validated to be recyclable for reducing bromate, indicating that CoPB and NiPB are promising heterogeneous catalysts for reducing bromate. © 2023, The Korean Institute of Chemical Engineers.

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Physicochemical and Biological Changes on Naturally Aged Microplastic Surfaces in real Environments Over 10 Months

SSRN

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SSrN 2023年

作者： Yu, Xue Wang, Bing Han, Chenglong Liu, Ling Han, Xiaoxin Zheng, Boyang Zhang, Bo Sun, Jiawei Zhang, Zhiyin Ma, Weiqi Zhai, Lifang Lu, Xueqiang Tianjin Key Laboratory of Environmental Technology for Complex Trans-Media Pollution Tianjin International Joint Research Center for Environmental Biogeochemical Technology College of Environmental Science and Engineering Nankai University Tianjin300350 China Tianjin Marine Environmental Monitoring Central Station of SOA Tianjin Marine Environmental Monitoring and Forecasting Center Tianjin300457 China Changchun Bureau of Ecology and Environment Changchun130022 China Nanchang City Development and Reform Commission Jiangxi330038 China R&D Department FS Ltd. Katikati3129 New Zealand

Microplastics (MPs) undergo aging over time, which can influence their behavior in the environment. While laboratory-simulated studies have investigated MP aging, research on natural aging in various real environments remains limited. This study aims to investigate the physical, chemical and biological changes that occur in five types of MPs after more than 10 months of natural aging in three different real environments: seawater, air and soil. results are compared with previous laboratory experiments. The surface roughness of all types of aged MPs was found to be higher in seawater than in air and soil, which differed from previous simulated studies that showed the highest roughness in air. All aged MPs exhibited the occurance of hydroxyl and carbonyl groups due to the oxidation processes. Interestingly, the MPs aged in soil showed the lowest level of these functional groups, while in seawater or air, some MPs demonstrated the highest, without a discernible pattern. This contrasts with previous studies indicating the highest level of oxygen-containing functional groups in aged MPs in air. Bacterial analysis identified fourteen bacterial phyla on the surface of aged MPs in all three real environments, with varying abundance in specific environments. Notably, the composition of bacterial communities in the microplastisphere was determined by the surrounding environments, independent of MP types. Natural aging is more complex than laboratory simulations, and the degree of MP aging increases with the complexity of environmental factors. These findings enhance our understanding of the natural aging of MPs in different real environments. © 2023, The Authors. All rights reserved.

关键词： Microplastic

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rollable Multi-Touch Organic Capacitive Pressure Sensor for Multi-directional User Interactions

Rollable Multi-Touch Organic Capacitive Pressure Sensor for ...

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SId Symposium, Seminar, and Exhibition 2019, display Week 2019

作者： Ebisui, Akira Kaneko, Hiroki Tsukamoto, Kei Harada, Tomoko Goto, Tetsuro Sakakura, Yoshiaki Miyawaki, Manami Hasegawa, Hayato Kobayashi, Ken Sato, Satoshi Kamei, Takahiro Nomoto, Kazumasa Application Technology Development Div.1 R&D Center Sony Corporation New Business Development Dept Sony Storage Media Solutions Corporation

We have developed a rollable multi-touch pressure sensor that works with a radius down to 5 mm, a high dynamic range of 1– 300 kPa, and a spatial resolution down to 3 mm. This was achieved using a novel sensor with a... 详细信息

ISBN: (纸本)9781510896161

关键词： Pressure sensors

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Characterization of aroma profiles and volatile organic compounds in silver carp surimi gel by GC-IMS, SPME-GC-MS, and sensory evaluation: Affected by okara insoluble dietary fiber with varied particle sizes

Food Chemistry Advances

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Food Chemistry Advances 2023年 2卷

作者： Qiu, Jing Cai, Libin Xiong, Shanbai You, Juan Yin, Tao An, Yueqi College of Food Science and Technology/National R&D Branch Center for Conventional Freshwater Fish Processing (Wuhan) Huazhong Agricultural University Hubei Province Wuhan 430070 China Engineering Research Center of Green development for Conventional Aquatic Biological Industry in the Yangtze River Economic Belt Ministry of Education Hubei Province Wuhan 430070 China College of Fisheries Huazhong Agricultural University Hubei Province Wuhan 430070 China

This study aimed to investigate the effects of okara insoluble dietary fiber (IdF) with different particle sizes on the volatile organic compounds (VOCs) and characteristic aroma compounds of silver carp surimi gel. VOCs of nano-sized IdF (NIdF), micro-sized IdF (MIdF), and silver carp surimi gels with 0.8% (w/w) NIdF or 0.8% (w/w) MIdF were analyzed by electronic nose, gas chromatography-ion mobility spectrometry (GC-IMS) and Solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC–MS) combined with sensory evaluation. results revealed that the addition of NIdF and MIdF could affect the VOCs of surimi gels. NIdF reduced the odor activity value of some fishy aroma compounds, such as hexanal, nonanal, (E,E)-2,4-heptadienal, and 1-octen-3-ol. Moreover, NIdF increased the concentrations of VOCs with branched chains or a benzene ring, such as 2-methylbutanal, 3-methylbutanal, benzaldehyde, and phenylacetaldehyde. The overall sensory preference of surimi gel could be improved with the addition of NIdF. This study provides new ideas for the applications of okara in aroma regulation of surimi products. © 2023

关键词： Aroma compounds Gas chromatography-ion mobility spectrometry Okara, Insoluble dietary fiber Solid-phase microextraction-gas chromatography-mass spectrometry Surimi, Volatile organic compounds

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Effect and mechanism of cold plasma treatment on the heat pump drying performance of mussel (Mytilus coruscus) meat

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Food chemistry 2025年 488卷 144821页

作者： Sheng Wan Yilin Lu Xuxia Zhou Yuting ding Shulai Liu Zhigang Ke College of Food Science and Technology Zhejiang University of Technology Hangzhou 310014 China Zhejiang Key Laboratory of Green Low-carbon and Efficient Development of Marine Fishery Resources Hangzhou 310014 China National R&D Branch Center for Pelagic Aquatic Products Processing (Hangzhou) Hangzhou 310014 China. Institutes of Physical Science and Information Technology Anhui University Hefei 230601 China. National R&D Branch Center for Pelagic Aquatic Products Processing (Hangzhou) Hangzhou 310014 China Food Science Research Institute of Zhangzhou Zhangzhou 363000 Fujian China. National R&D Branch Center for Pelagic Aquatic Products Processing (Hangzhou) Hangzhou 310014 China. Electronic address: slliu@***. National R&D Branch Center for Pelagic Aquatic Products Processing (Hangzhou) Hangzhou 310014 China. Electronic address: kezg@***.

Cold plasma (CP) can enhance the drying efficiency of plant-based foods, but its impact on animal-based foods remains unclear. This study found that both air and argon CP treatments can improve the heat pump drying efficiency of mussel meat, with air CP better. It raised effective moisture diffusivity from 3.32 × 10 m/h to 5.22 × 10 m/h and cut drying time by 38.67 % under the optimal conditions. Mechanism analysis showed air CP exhibits a more pronounced etching effect on the surface of mussel tissue, with the capability to penetrate beyond 1.52 mm into the underlying tissue. CP-generated charged particles and reactive oxygen/nitrogen species contribute to these changes, which may enhance moisture transfer during drying. Moreover, CP treatment improves dried mussel meat quality, e.g., increasing rehydration and reducing lipid oxidation. This study provides a deeper understanding of CP-assisted drying and highlights its application in aquatic products.

关键词： Cold plasma drying efficiency Etching effect Mussel Penetration depth Quality

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Fault detection in Solar Power System with Internet of Things using Multi resolution Sinusoidal Neural Network - Snow Geese Optimization Approach

Fault Detection in Solar Power System with Internet of Thing...

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Sustainable Expert Systems (ICSES), International Conference on

作者： Pramod Kumar K.E. Purushothaman Arunmozhi r V Jayachitra S d. Leela rani S. Kaliappan Department of Computer Science and Engineering Ganga Institute of Technology and Management Kablana Haryana India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamil Nadu India Department of Electrical and Electronic Engineering Karpagam Academy of Higher Education Coimbatore Tamil Nadu India Department of Chemistry S.A. Engineering College Chennai Tamil Nadu India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Tirupati Andhra Pradesh India Division of Research and Development Lovely Professional University Jalandhar Delhi Punjab India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Fault detection in power systems, including Photovoltaic (PV) systems, using Internet of Things (IoT) involves deploying sensors to monitor key parameters and analyzing the data identify anomalies. The accuracy of these systems can be compromised by issues such as noisy or low-quality sensor data, which may lead to false positives or missed faults. Additionally, the complexity of managing large volumes of data from numerous IoT devices can strain the system, further affecting detection accuracy. To overcome these drawbacks, this paper proposes an efficient approach for fault uncovering in solar power system grounded on IoT. The data are collected from solar power generation dataset. Subsequently, the data are nourished to preprocessing. In preprocessing segment removes the absent values in the data utilizing reverse Lognormal Kalman Filter (rLKF). The consequence after the preprocessing data is transported to the Multiresolution Sinusoidal Neural Network (MSNN). The line-line faults, ground faults, line-ground faults and partial shading are successfully predicted and classified by using MSNN. The Snow Geese Optimization (SGO) is rummage-sale to optimize the weight structure of MSNN. The projected MSNN-SGO is utilized within the MATLAB platform. Performance metrics counting precision, accuracy, root Mean Squared Error (rMSE), F1-score, and Mean Squared Error (MSE) were examined in order to determine the proposed method. The proposed dAGCN-COA technique yields 14.89%, 16.89%, and 18.23% higher precision, 16.65%, 18.85%, and 17.89% higher accuracy, 22.36%, 15.42% and 28.27% lower rMSE when analysed the existing methods. The proposed MSNN-SGO technique is associated with the existing methods for instance spatial-temporal recurrent graph neural network (STrGNN), convolutional neural network (CNN), and long short-term memory network (LSTMN), respectively.

关键词： Accuracy Fault detection Snow Electrical fault detection Sensor systems Power systems Sensors Internet of Things Spatial resolution Optimization

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