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Studying the effect of surfactant assisted low-salinity water flooding on clay-rich sandstones

Petroleum 2024年第2期10卷 306-318页

作者： Saeed Khezerloo-ye Aghdam Alireza Kazemi mohammad Ahmadi Department of Petroleum Engineering Amirkabir University of Technology (AUT) Department of Petroleum and Chemical Engineering College of Engineering Sultan Qaboos University

Sandstone reservoirs often contain clay particles that can cause damage and reduce permeability during low-salinity water flooding. In this study, the effect of surfactants on fine migration in clay-rich sandstones and its impact on oil recovery was ***, the impact of surfactants on interparticle forces in fine-matrix, fine-fine, and oil-matrix systems was modeled. The results showed that both CTAB(cetyltrimethyl ammonium bromide) and QS(quillaja saponin) cause EDL compaction, weakening the repulsive forces. However, SDS(sodium dodecyl sulfate)and TX(triton X-100) do not affect the EDL. Next, the effect of surfactants on IFT reduction and wettability alteration was experimentally investigated. All surfactants reduced IFT due to the surface excessive concentration mechanism. The wettability alteration experiment illustrated that although QS and CTAB compact EDL around oil and matrix particles leading to attraction force augmentation, they both alter wettability through adsorption on matrix and carboxylic groups present in crude oil, *** aqueous solutions were then injected into various clay-rich sandstone sanpacks, which resulted in increased oil recovery. However, the mechanisms leading to enhanced oil recovery variedby surfactant type. CTAB increased recovery by 10% through IFT reduction and wettability alteration, while SDS and TX increased recovery by 12% and 9%, respectively, through wettability alteration and extreme fine migration. In contrast, partial fine migration in the QS flooding experiment reached a recovery increase of 18%. Permeability trends through experiments were also recorded. During CTAB injection,permeability did not reduce, while QS aqueous solution reduced rock permeability to 5 m D. SDS and TX reduced the magnitude of permeability to 2 m *** conclusion, this study demonstrates that surfactants can effectively improve oil recovery in clay-rich sandstones by altering the interparticle forces, reducing IFT, a

关键词： Surfactant flooding Smart water Fine migration Recovery factor

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Characterization and Selection of Microcrystalline Cellulose from Oil Palm Empty Fruit Bunches for Strengthening Hydrogel Films

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Journal of Renewable Materials 2024年第3期12卷 513-537页

作者： Susi Susi Makhmudun Ainuri Wagiman Wagiman mohammad Affan Fajar Falah Department of Agroindustrial Technology Faculty of AgricultureUniversitas Lambung MangkuratJl A Yani Km 36BanjarbaruSouth Kalimantan70714Indonesia Doctoral Programme of Agroindustrial Technology Faculty of Agricultural TechnologyUniversitas Gadjah MadaJl Flora No.1BulaksumurYogyakarta55281Indonesia Department of Agroindustrial Technology Faculty of Agricultural TechnologyUniversitas Gadjah MadaJl Flora No.1BulaksumurYogyakarta55281Indonesia

Microcrystalline cellulose(MCC)is one of the cellulose derivatives produced as a result of the depolymerization of a part of cellulose to achieve high *** implemented in other polymers,high crystallinity correlates with greater strength and stiffnes,but it can reduce the water-holding *** acid concentration and hydrolysis time will affect the acquisition of crystallinity and water absorption capacity,both of which have significance as properties of hydrogel *** study aimed to evaluate the properties and select the MCC generated from varying the proportion of hydrochloric acid(HCl)and the appropriate hydrolysis time as a filler for film *** was produced by hydrolyzing cellulose of oil palm empty fruit bunches(OPEFB)with the HCl solution at varied concentrations and *** results show that the longer hydrolysis times and higher HCl concentrations increase crystallinity and density while lowering yield and water *** extensive acid hydrolysis reduces the amorphous area significantly,allowing the depolymerization to occur and extend the crystalline *** morphological properties of the MCC,which are smaller but compact,indicate the presence of disintegrating and diminishing structures.A 2.5 N HCl concentration and a 45-min hydrolysis time succeed in sufficient crystallinity as well as maintaining good water absorption *** treatment produced MCC with absorption capacity of 4.03±0.26 g/g,swelling capacity of 5.03±0.26 g/g,loss on drying of 1.44%±0.36,bulk and tapped density of 0.27±0.031 g/cm^(3) and 0.3±0.006 g/cm^(3),respectively,with a crystallinity index of 88.89%±4.76 and a crystallite size of 4.23±0.70 *** MCC generated could potentially be utilized as a hydrogel film filler,since a given proportion will be able to maintain the strength of the hydrogel,not readily dissolve but absorb water significantly.

关键词： Acid hydrolysis hydrogel OPEFB microcrystalline cellulose water absorption

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Coupling of reduced inorganic fertilizer with plant-based organic fertilizer as a promising fertilizer management strategy for colored rice in tropical regions

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Journal of Integrative Agriculture 2024年第1期23卷 93-107页

作者： Tingcheng Zhao Aibin He mohammad Nauman Khan Qi Yin Shaokun Song Lixiao Nie Research Center for Physiology and Ecology and Green Cultivation of Tropical Crops School of Breeding and Multiplication(Sanya Institute of Breeding and Multiplication)Hainan UniversitySanya 572000China

Colored rice is a type of high-quality,high-added-value rice that has attracted increasing attention in recent *** use of large amounts of inorganic nitrogen fertilizer in rice fields results in low fertilizer use efficiency and high environmental *** fertilizer is a promising way to improve soil quality and sustain high ***,most studies focus on the effect of animal-based organic *** effects of different ratios of plantbased organic fertilizer and inorganic fertilizer on the grain yield and quality of colored rice have rarely been ***,a two-year field experiment was conducted in 2020 and 2021 to study the effects of replacing inorganic N fertilizers with plant-based organic fertilizers on the yield,nitrogen use efficiency(NUE),and anthocyanin content of two colored rice varieties in a tropical region in *** experimental treatments included no nitrogen fertilization(T1),100% inorganic nitrogen fertilizer(T2),30%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T3),60%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T4),and 100% plantbased organic fertilizer(T5).The total nitrogen provided to all the treatments except T1 was the same at 120 kg *** results showed that the T3 treatment enhanced the grain yield and anthocyanin content of colored rice by increasing nitrogen use efficiency compared with *** average,grain yields were increased by 9 and 8%,while the anthocyanin content increased by 16 and 10% in the two colored rice varieties under T3 across the two years,respectively,as compared with *** study of the residual effect of partial substitution of inorganic fertilizers showed that the substitution of inorganic fertilizer with plant-based organic fertilizer improved the soil physiochemical properties,and thus increased the rice grain yield,in the subsequent *** highest grain yield of the subsequent rice crop was observe

关键词： colored rice organic fertilizer soil quality grain yield anthocyanin

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Revealing connectivity in residential Architecture: An algorithmic approach to extracting adjacency matrices from floor plans

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Frontiers of Architectural Research 2024年第2期13卷 370-386页

作者： mohammad Amin Moradi Omid mohammadrashidi Navid Niazkar Morteza Rahbar School of Architecture and Engineering University College of RouzbahanMazandaranIran School of Architecture Islamic Azad UniversitySafaDasht CampusTehranIran A.James Clark School of Engineering University of MarylandCollege ParkMDUSA School of Architecture and Environmental Design Iran University of Science and TechnologyTehranIran

In today's world, various approaches and parameters exist for designing a plan and determining its spatial, placement. Hence, various modes for identifying crucial locations can be explored when an architectural plan is designed in different dimensions. While designing all these modes takes considerable time, there are numerous potential applications for artificial intelligence (AI) in this domain. This study aims to compute and use an adjacency matrix to generate architectural residential plans. Additionally, it develops a plan generation algorithm in Rhinoceros software, utilizing the Grasshopper plugin to create a dataset of architectural plans. In the following step, the data was entered into a neural network to identify the architectural plan's type, furniture, icons, and use of spaces, which was achieved using YOLOv4, EfficientDet, YOLOv5, DetectoRS, and RetinaNet. The algorithm's execution, testing, and training were conducted using Darknet and PyTorch. The research dataset comprises 12,000 plans, with 70% employed in the training phase and 30% in the testing phase. The network was appropriately trained practically and precisely in relation to an average precision (AP) resulting of 91.50%. After detecting the types of space use, the main research algorithm has been designed and coded, which includes determining the adjacency matrix of architectural plan spaces in seven stages. All research processes were conducted in Python, including dataset preparation, network object detection, and adjacency matrix algorithm design. Finally, the adjacency matrix is given to the input of the proposed plan generator network, which consequently, based on the resulting adjacency, obtains different placement modes for spaces and furniture.

关键词： Algorithm design Adjacency matrix Generate floor plan Detection plan

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Platform Evolution in an Oligo-Miocene Back-arc Basin:An Example from the Central Iran Basin

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Acta Geologica Sinica(English Edition) 2024年第1期98卷 185-206页

作者： Masoud SHARIFI-YAZDI Amirhossein ENAYATI Jamal SALEHI AGHDAM mohammad BAHREHVAR Seyed Mustafa rezaEI Department of Geology Faculty of Earth SciencesGeography and AstronomyUniversity of Vienna1090 Vienna.Austria Geology and Geophysics Department Tehran Energy Consultants(TEC Co.)TehranIran School of Geology College of ScienceUniversity of TehranTehranIran Department of Geology Tarbiat Modares UniversityTehranIran

The Qom Formation is the most important hydrocarbon reservoir target in Central *** Qom platform developed in a back-arc basin during the Oligo-Miocene due to the closing of the Tethyan *** formation consists of a variety of carbonate and non-carbonate facies deposited on a platform ranging from supratidal to basin.A combination of tectonic and eustatic events led to some lateral and vertical facies variations in the study *** third-order depositional sequences and related surfaces were identified regarding vertical facies changes in the studied sections of this Oligo-Miocene *** to all results and data,this succession was initially deposited during the Chattian upon a distally steepened ramp of siliciclastic-carbonate composition,including the Bouma ***,from the late Chattian to the Aquitanian,the platform changed into a homoclinal carbonate ramp with a gentle *** respect to tectonic activity,this phase was a calm period during the deposition of the Qom ***,a drowned carbonate platform and a rimmed shelf emerged during the Burdigalian,terminated by the continental deposits of the Upper Red *** all geological characteristics,three main tectono-eustatic evolutionary phases have been recognized in the Qom back-arcbasin.

关键词： carbonate ramp depositional facies submarine fan eustasy basement faults back-arc basin

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Transparent and Accurate COVID-19 Diagnosis:Integrating Explainable AI with Advanced Deep Learning in CT Imaging

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3101-3123页

作者： mohammad Mehedi Hassan Salman A.AlQahtani Mabrook S.AlRakhami Ahmed Zohier Elhendi Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Science Technology and Innovation Department King Saud UniversityRiyadh11543Saudi Arabia

In the current landscape of the COVID-19 pandemic,the utilization of deep learning in medical imaging,especially in chest computed tomography(CT)scan analysis for virus detection,has become increasingly *** its potential,deep learning’s“black box”nature has been a major impediment to its broader acceptance in clinical environments,where transparency in decision-making is *** bridge this gap,our research integrates Explainable AI(XAI)techniques,specifically the Local Interpretable Model-Agnostic Explanations(LIME)method,with advanced deep learning *** integration forms a sophisticated and transparent framework for COVID-19 identification,enhancing the capability of standard Convolutional Neural Network(CNN)models through transfer learning and data *** approach leverages the refined DenseNet201 architecture for superior feature extraction and employs data augmentation strategies to foster robust model *** pivotal element of our methodology is the use of LIME,which demystifies the AI decision-making process,providing clinicians with clear,interpretable insights into the AI’s *** unique combination of an optimized Deep Neural Network(DNN)with LIME not only elevates the precision in detecting COVID-19 cases but also equips healthcare professionals with a deeper understanding of the diagnostic *** method,validated on the SARS-COV-2 CT-Scan dataset,demonstrates exceptional diagnostic accuracy,with performance metrics that reinforce its potential for seamless integration into modern healthcare *** innovative approach marks a significant advancement in creating explainable and trustworthy AI tools for medical decisionmaking in the ongoing battle against COVID-19.

关键词： Explainable AI COVID-19 CT images deep learning

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An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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Ionotropic receptors mediate olfactory learning and memory in Drosophila

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Insect Science 2024年第4期31卷 1249-1269页

作者： Md Zeeshan Ali Anushree Aarif Ahsan mohammad Shamsul Ola Rizwanul Haque Jawaid Ahsan Department of Biotechnology Central University of South BiharGayaBiharIndia Department of Radiation Oncology University of MichiganAnn ArborMichiganUSA Department of Biochemistry College of ScienceKing Saud UniversityRiyadhSaudi Arabia

Phenylacetaldehyde(PAH),an aromatic compound,is present in a diverse range of fruits including overripe bananas and prickly pear cactus,the two major host fruits for Drosophila *** acts as a potent ligand for the ionotropic receptor 84a(IR84a)in the adult fruit fly and it is detected by the IR84a/IR8a heterotetrameric *** role in the male courtship behavior through IR84a as an environmental aphrodisiac is of additional *** ***,two distinct kinds of olfactory receptors,that is,odorant receptors(ORs)and ionotropic receptors(IRs),perceive the odorant *** display unique structural,molecular,and functional characteristics in addition to having different evolutionary ***,olfactory cues detected by the ORs such as ethyl acetate,1-butanol,isoamyl acetate,1-octanol,4-methylcyclohexanol,*** as aliphatic esters and alcohols have been employed in olfactory classical conditioning using fruit *** underlines the participation of OR-activated olfactory pathways in learning and memory *** study elucidates that likewise ethyl acetate(EA)(an OR-responsive odorant),PAH(an IR-responsive aromatic compound)too can form learning and memory when associated with an appetitive gustatory *** association of PAH with sucrose(PAH/SUC)led to learning and formation of the long-term memory(LTM).Additionally,the Orco^(1),Ir84a^(MI00501),and Ir8a^(1)mutant flies were used to confirm the exclusive participation of the IR84a/IR8a complex in PAH/SUC olfactory associative *** results highlight the involvement of IRs via an IR-activated pathway in facilitating robust olfactory behavior.

关键词： appetitive conditioning Drosophila melanogaster ethyl acetate ionotropic receptors learning and memory phenylacetaldehyde

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Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani Alshahrani Mohammed Hamdi mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

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Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay Kumar Sharma mohammad Khalid Imam Rahmani Baijnath Kaushik Rania Almajalid Department of Computer Science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer Science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

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