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U-Net Inspired Deep Neural Network-Based Smoke Plume Detection in Satellite Images

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Computers, Materials & Continua 2024年第4期79卷 779-799页

作者： Ananthakrishnan Balasundaram Ayesha Shaik Japmann Kaur Banga aman Kumar Singh Centre for Cyber Physical Systems Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India

Industrial activities, through the human-induced release of Green House Gas (GHG) emissions, have beenidentified as the primary cause of global warming. Accurate and quantitative monitoring of these emissions isessential for a comprehensive understanding of their impact on the Earth’s climate and for effectively enforcingemission regulations at a large scale. This work examines the feasibility of detecting and quantifying industrialsmoke plumes using freely accessible geo-satellite imagery. The existing systemhas so many lagging factors such aslimitations in accuracy, robustness, and efficiency and these factors hinder the effectiveness in supporting timelyresponse to industrial fires. In this work, the utilization of grayscale images is done instead of traditional colorimages for smoke plume detection. The dataset was trained through a ResNet-50 model for classification and aU-Net model for segmentation. The dataset consists of images gathered by European Space Agency’s Sentinel-2 satellite constellation from a selection of industrial sites. The acquired images predominantly capture scenesof industrial locations, some of which exhibit active smoke plume emissions. The performance of the abovementionedtechniques and models is represented by their accuracy and IOU (Intersection-over-Union) *** images are first trained on the basic RGB images where their respective classification using the ResNet-50model results in an accuracy of 94.4% and segmentation using the U-Net Model with an IOU metric of 0.5 andaccuracy of 94% which leads to the detection of exact patches where the smoke plume has occurred. This work hastrained the classification model on grayscale images achieving a good increase in accuracy of 96.4%.

关键词： Smoke plume ResNet-50 U-Net geo satellite images early warning global monitoring

Chemical Approaches to Emerging Advancements in Deformable Bioelectronics:Synthesis,Device Concepts,Performance,and Applications

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CCS Chemistry 2024年第1期6卷 11-26页

作者： Jj Abu-Halimah aman Majmudar Bozhi Tian Department of Chemistry University of ChicagoChicagoIllinois 60637 The James Franck Institute University of ChicagoChicagoIllinois 60637 The Institute for Biophysical Dynamics University of ChicagoChicagoIllinois 60637

This mini review examines the current advances and future prospects of chemical approaches in deformable bioelectronics,emphasizing their transformative potential in healthcare and other *** mini review outlines novel fabrication strategies that rely on chemical principles to create adaptable,comfortable,and durable bioelectronic devices that are capable of seamlessly integrating into the dynamic biological *** discussion also extends to the integration of innovative device concepts that enhance the outcomes in both sensing and modulation ***-enhancing strategies that use chemistry to refine the sensitivity and precision of these devices are also ***,the mini review explores the emerging applications of chemically enhanced bioelectronic devices in healthcare,reflecting the potential of this field to revolutionize patient care and improve health *** the outlook section,this mini review investigates the promising future of transient and living bioelectronics,emphasizing the pivotal role of chemical approaches in their *** additionally covers the potential of chemical techniques in powering bioelectronic devices using biological systems and discusses the prospective applications of chemically synthesized bioelectronic devices outside of *** the field has made substantial progress,this mini review also identifies challenges that must be addressed,thus underlining the necessity for continued research and chemical innovation in bioelectronics.

关键词： deformable bioelectronics hydrogels biointerfaces sensing modulation semiconductors cells and tissues

氧化型光电催化促进的C—H键官能团化反应研究进展

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有机化学 2024年第3期44卷 728-747页

作者： Hasil aman 常瑞叶俊涛上海交通大学化学化工学院、上海市手性药物分子工程重点实验室上海200240

惰性C—H键直接选择性官能团化反应是有机合成领域长久以来的挑战之一.虽然已经发展了多种策略,但仍亟待发展无需添加过渡金属和氧化剂的新方法.近年来,光电催化作为一种新兴策略,能够在温和条件下实现包括直接C—H键官能团化在内的多... 详细信息

惰性C—H键直接选择性官能团化反应是有机合成领域长久以来的挑战之一.虽然已经发展了多种策略,但仍亟待发展无需添加过渡金属和氧化剂的新方法.近年来,光电催化作为一种新兴策略,能够在温和条件下实现包括直接C—H键官能团化在内的多种挑战性转化反应,表现出强大的潜力.从机理的角度出发,总结了通过阳极氧化的光电催化策略实现C—H键官能团化反应的最新研究进展,并简单讨论了这个新兴领域所面临的挑战和机遇.

关键词：光电催化电化学 C—H键官能团化氧化反应

An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1051-1075页

作者： Shazia Shamas Surya Narayan Panda Ishu Sharma Kalpna Guleria aman Singh Ahmad Ali AlZubi Mallak Ahmad AlZubi Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Higher Polytechnic School Universidad Europea del AtlánticoC/Isabel Torres 21Santander39011Spain Department of Engineering Universidad Internacional IberoamericanaAreciboPR00613USA Uttaranchal Institute of Technology Uttaranchal UniversityDehradunUttarakhand248007India Computer Science Department King Saud UniversityRiyadhSaudi Arabia Faculty of Medicine Jordan University of Science and TechnologyIrbidJordan

The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis andplanning intervention. This research work addresses the major issues pertaining to the field of medical imageprocessing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposesan improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. Thebetter resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In thisprocess, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarmintelligent techniques. The techniques experimented in this paper are K-means with Artificial Bee Colony (ABC),K-means with Cuckoo Search Algorithm (CSA), K-means with Particle Swarm Optimization (PSO), and Kmeanswith Firefly Algorithm (FFA). The testing and evaluation are performed on Early Lung Cancer ActionProgram (ELCAP) database. The simulation analysis is performed using lung cancer images set against metrics:precision, sensitivity, specificity, f-measure, accuracy,Matthews Correlation Coefficient (MCC), Jaccard, and *** detailed evaluation shows that the K-means with Cuckoo Search Algorithm (CSA) significantly improved thequality of lung cancer segmentation in comparison to the other optimization approaches utilized for lung cancerimages. The results exhibit that the proposed approach (K-means with CSA) achieves precision, sensitivity, and Fmeasureof 0.942, 0.964, and 0.953, respectively, and an average accuracy of 93%. The experimental results prove thatK-meanswithABC,K-meanswith PSO,K-meanswith FFA, andK-meanswithCSAhave achieved an improvementof 10.8%, 13.38%, 13.93%, and 15.7%, respectively, for accuracy measure in comparison to K-means segmentationfor lung cancer images. Further, it is highlighted that the proposed K-means with CSA have achieved a significantimprovement in accuracy, hence can be utilized by resea

关键词： Lesion lung cancer segmentation medical imaging meta-heuristic Artificial Bee Colony(ABC) Cuckoo Search Algorithm(CSA) Particle Swarm Optimization(PSO) Firefly Algorithm(FFA) segmentation

CHD4-induced up-regulation of ERα activity contributes to breast cancer progression

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Genes & Diseases 2024年第3期11卷 132-135页

作者： aman Sattout Xiaomin Yu Zhuo Sun Yanan Li Yulin Li Shujing Li Wei Huo Huijian Wu School of Bioengineering&Key Laboratory of Protein Modification and Disease Liaoning ProvinceDalian University of TechnologyDalianLiaoning 116024China Department of Oncology Central Hospital Affiliated with Dalian University of TechnologyDalianLiaoning 116089China

The estrogen signaling system is a crucial regulator of ***,abnormal activation of estrogen signaling may play a role in breast cancer initiation and *** to this pathway is the interaction between estrogen receptor alpha(ERa)and various co-transcription activators.1 Although numerous studies have investigated ER coregulators,the protein-protein interaction networks of ERa are not fully *** research has shown that high chromodomain helicase DNA-binding 4(CHD4)expression is linked to poor prognosis in various cancers.2,?In this study,we demonstrated that both CHD4 and ERαcontribute to breast cancer progression while providing evidence of the regulatory processes and functional interplay between these two proteins.

关键词： breast cancer ERα

Relationship between Helium Degassing of Cattle-Manure-Compost Adsorbents and Copper Ions Removal

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International Journal of Organic Chemistry 2012年第3期2卷 262-266页

作者： Muhammad Abbas Ahmad Zaini Mohd Azizi Che Yunus yoshimasa aman Motoi Machida Centre of Lipids Engineering & Applied Research Universiti Teknologi Malaysia Skudai Johor Malaysia Safety and Health Organization Chiba University Chiba Japan

This work was aimed to investigate the effect of helium degassing of cattle-manure-compost (CMC) based activated carbons on the adsorptive removal of copper ions from aqueous solution. Degassing temperatures were 500℃, 800℃ and 1000℃. Activated carbons were characterized according to surface chemistry and pore structures. Adsorption of copper ions was carried out using the conventional bottle-point technique to which the equilibrium data were correlated to Langmuir and Freundlich models. Results indicated that the uptake of copper ions could be well characterized by Langmuir model. It was found that the adsorption of copper ions decreased with significant decrease in surface area as a result of helium degassing at higher temperature. The increase of electron density on graphene layers offered higher affinity towards copper ions at lower equilibrium concentration. It was inferred that copper ions favorably adsorbed on mesopores at lower equilibrium concentration and switched to micropores at higher equilibrium concentration.

关键词： Activated Carbon Adsorption Copper Ions Cattle-Manure-Compost Helium Degassing

Elasto-inertial focusing and particle migration in high aspect ratio microchannels for highthroughput separation

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Microsystems & Nanoengineering 2024年第3期10卷 381-394页

作者： Selim Tanriverdi Javier Cruz Shahriar Habibi Kasra Amini Martim Costa Fredrik Lundell Gustaf Mårtensson Luca Brandt Outi Tammisola aman Russom Division of Nanobiotechnology Department of Protein ScienceScience for Life LaboratoryKTH Royal Institute of TechnologySolna 17165Sweden Division of Microsystems Technology Department of Materials Science and EngineeringUppsala UniversityUppsala 75237Sweden FLOW and SeRC(Swedish e-Science Research Centre) Department of Engineering MechanicsRoyal Institute of TechnologyStockholm SE 10044Sweden FLOW and Fluid Physics Laboratory Department of Engineering MechanicsRoyal Institute of TechnologyStockholmSweden Wallenberg Wood Science Center Royal Institute of TechnologyStockholm SE 10044Sweden Department of Energy and Process Engineering Norwegian University of Science and Technology(NTNU)TrondheimNorway AIMES Center for the Advancement of Integrated Medical and Engineering Sciences at Karolinska Institutet and KTH Royal Institute of Technology StockholmSweden

The combination of flow elasticity and inertia has emerged as a viable tool for focusing and manipulating particles using *** there is considerable interest in the field of elasto-inertial microfluidics owing to its potential applications,research on particle focusing has been mostly limited to low Reynolds numbers(Re<1),and particle migration toward equilibrium positions has not been extensively *** this work,we thoroughly studied particle focusing on the dynamic range of flow rates and particle migration using straight microchannels with a single inlet high aspect *** initially explored several parameters that had an impact on particle focusing,such as the particle size,channel dimensions,concentration of viscoelastic fluid,and flow *** experimental work covered a wide range of dimensionless numbers(0.05

关键词： particle separation straight

Mechanism of Universal Quantum Computation in the Brain

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Journal of Applied Mathematics and Physics 2024年第2期12卷 468-474页

作者： aman Chawla Salvatore Domenic Morgera Department of Computer Science and Engineering Indian Institute of Technology Delhi India Department of Electrical Engineering University of South Florida Tampa USA

In this paper, the authors extend [1] and provide more details of how the brain may act like a quantum computer. In particular, positing the difference between voltages on two axons as the environment for ions undergoing spatial superposition, we argue that evolution in the presence of metric perturbations will differ from that in the absence of these waves. This differential state evolution will then encode the information being processed by the tract due to the interaction of the quantum state of the ions at the nodes with the “controlling’ potential. Upon decoherence, which is equal to a measurement, the final spatial state of the ions is decided and it also gets reset by the next impulse initiation time. Under synchronization, several tracts undergo such processes in synchrony and therefore the picture of a quantum computing circuit is complete. Under this model, based on the number of axons in the corpus callosum alone, we estimate that upwards of 50 million quantum states might be prepared and evolved every second in this white matter tract, far greater processing than any present quantum computer can accomplish.

关键词： Axons Quantum computation Metric perturbation Decoherence Time-coded information

Performance Analysis of Support Vector Machine (SVM) on Challenging Datasets for Forest Fire Detection

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International Journal of Communications, Network and System Sciences 2024年第2期17卷 11-29页

作者： Ankan Kar Nirjhar Nath Utpalraj Kemprai aman Department of Computer Science Chennai Mathematical Institute Chennai India Department of Mathematics & Computer Science Chennai Mathematical Institute Chennai India Department of Data Science Chennai Mathematical Institute Chennai India

This article delves into the analysis of performance and utilization of Support Vector Machines (SVMs) for the critical task of forest fire detection using image datasets. With the increasing threat of forest fires to ecosystems and human settlements, the need for rapid and accurate detection systems is of utmost importance. SVMs, renowned for their strong classification capabilities, exhibit proficiency in recognizing patterns associated with fire within images. By training on labeled data, SVMs acquire the ability to identify distinctive attributes associated with fire, such as flames, smoke, or alterations in the visual characteristics of the forest area. The document thoroughly examines the use of SVMs, covering crucial elements like data preprocessing, feature extraction, and model training. It rigorously evaluates parameters such as accuracy, efficiency, and practical applicability. The knowledge gained from this study aids in the development of efficient forest fire detection systems, enabling prompt responses and improving disaster management. Moreover, the correlation between SVM accuracy and the difficulties presented by high-dimensional datasets is carefully investigated, demonstrated through a revealing case study. The relationship between accuracy scores and the different resolutions used for resizing the training datasets has also been discussed in this article. These comprehensive studies result in a definitive overview of the difficulties faced and the potential sectors requiring further improvement and focus.

关键词： Support Vector Machine Challenging Datasets Forest Fire Detection Classification