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Machine Learning-Based Routing Protocol in Flying Ad Hoc Networks: A Review

Computers, Materials & Continua 2025年第2期82卷 1615-1643页

作者： Priyanka Manjit Kaur Deepak Prashar Leo Mrsic Arfat Ahmad Khan Department of Computer Science and Engineering(CSE) Lovely Professional UniversityPhagwara144411India Department for Program Engineering Algebra UniversityGradiscanska 24Zagreb10000Croatia Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand

“Flying Ad Hoc Networks(FANETs)”,which use“Unmanned Aerial Vehicles(UAVs)”,are developing as a critical mechanism for numerous applications,such as military operations and civilian *** dynamic nature of FANETs,with high mobility,quick node migration,and frequent topology changes,presents substantial hurdles for routing protocol *** the preceding few years,researchers have found that machine learning gives productive solutions in routing while preserving the nature of FANET,which is topology change and high *** paper reviews current research on routing protocols and Machine Learning(ML)approaches applied to FANETs,emphasizing developments between 2021 and *** research uses the PRISMA approach to sift through the literature,filtering results from the SCOPUS database to find 82 relevant *** research study uses machine learning-based routing algorithms to beat the issues of high mobility,dynamic topologies,and intermittent connection in *** compared with conventional routing,it gives an energy-efficient and fast decision-making solution in a real-time environment,with greater fault tolerance *** protocols aim to increase routing efficiency,flexibility,and network stability using ML’s predictive and adaptive *** comprehensive review seeks to integrate existing information,offer novel integration approaches,and recommend future research topics for improving routing efficiency and flexibility in ***,the study highlights emerging trends in ML integration,discusses challenges faced during the review,and discusses overcoming these hurdles in future research.

关键词： FANET protocol machine learning

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A self-assembling nanoplatform for pyroptosis and ferroptosis enhanced cancer photoimmunotherapy

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Light(science & Applications) 2025年第1期14卷 153-166页

作者： Zhichao Wang Yuqi Tang Quan Li Institute of Advanced Materials and School of Chemistry and Chemical Engineering Southeast UniversityNanjing211189China Materials Science Graduate Program Kent State UniversityKentOH44242USA

The microenvironment of immunosuppression and low immunogenicity of tumor cells has led to unsatisfactory therapeutic effects of the currently developed *** cell death,such as pyroptosis and ferroptosis,can efficiently boost antitumor ***,the exploration of nanoplatform for dual function inducers and combined immune activators that simultaneously trigger pyroptosis and ferroptosis remains ***,a multifunctional pH-responsive theranostic nanoplatform(M@P)is designed and constructed by self-assembly of aggregation-induced emission photosensitizer MTCN-3 and immunoadjuvant Poly(l:C),which are further encapsulated in amphiphilic *** nanoplatform is found to have the characteristics of cancer cell targeting,pH response,near-infrared fluorescence imaging,and lysosome ***,after targeting lysosomes,M@P can cause lysosome dysfunction through the generation of reactive oxygen species and heat under light irradiation,triggering pyroptosis and ferroptosis of tumor cells,achieving immunogenic cell death,and further enhancing immunotherapy through the combined effect with the immunoadjuvant Poly(I:C).The anti-tumor immunotherapy effect of M@P has been further demonstrated in in vivo antitumor experiment of 4T1 tumor-bearing mouse model with poor *** research would provide an impetus as well as a novel strategy for dual function inducers and combined immune activators enhanced photoimmunotherapy.

关键词： immunotherapy cancer aggregation

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Rheological and stability analysis of cement pastes incorporating silica-based wastes

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Particuology 2024年第6期89卷 144-152页

作者： Julia da Rosa Martins Janaíde Cavalcante Rocha Dachamir Hotza Luciano Senff Graduate Program in Materials Science and Engineering(PPGMAT) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Graduate Program in Civil Engineering(PPGEC) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Graduate Program in Chemical Engineering(POSENQ) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Department of Mobility Engineering Federal University of Santa Catarina(UFSC)Joinville89219-600SCBrazil

This study investigates the influence of waste characteristics,especially zeta potential,on the properties of cement pastes and *** focus is to evaluate the impact of the zeta potential of cement particles and waste materials on the sedimentation speed,rheology,and hardening time of stabilized cement *** Cement II F 40,retarder additive,silica,and fly ash were used in the *** pastes were prepared,and during the stabilization period,their rheological properties and pH were *** zeta potential and sedimentation speed of the cement and waste particles were measured at the pH that the pastes presented during the entire stabilization *** the stabilization period,the pastes were subjected to the hardening time *** zeta potential analyses revealed diverse values for the different powder types,with the cement particles exhibiting a zeta potential of−3.0 mV,the silica particles exhibiting−10.5 mV,and the fly ash particles exhibiting−20.3 *** influence of the high zeta potential modulus was observed on the sedimentation speed,with the solution containing fly ash exhibiting a speed of 40.01μm/s,whereas the solution containing only cement exhibited a speed of 99.38μm/*** the pastes,the results indicate that the presence of fly ash particles with a significantly negative zeta potential led to a 16%reduction in hardening time compared to particles with a lower modulus of zeta *** tests showed that the inclusion of fly ash particles prevented the formation of *** the zeta potential influenced agglomerate formation and hardening time,it was found to have no effect on yield stress or viscosity.

关键词： Wastes Zeta potential Setting time Rheometry

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Team Sharingans at SimpleText: Fine-Tuned LLM based approach to Scientific Text Simplification 25

Team Sharingans at SimpleText: Fine-Tuned LLM based approach...

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25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024

作者： Ali, Syed Muhammad Sajid, Hammad Aijaz, Owais Waheed, Owais Alvi, Faisal Samad, Abdul Computer Science Program Dhanani School of Science and Engineering Habib University Karachi75290 Pakistan

This paper reports Habib University's Team Sharingans' participation in the CLEF 2024 SimpleText track, which aims to simplify scientific texts for improved readability and comprehension for non-experts. Our goal is to use state-of-the-art language models for simple yet accurate explanations of scientific texts for the general public. Our solution is based on a multi-step approach utilizing the GPT-3.5 model to solve Tasks 1, 2, and 3 i.e. passage extraction, identification and explanation of difficult concepts, and summarization. Our approach for Task 1 involved sentence embedding-based vector database for narrowing the corpus, MS-Marco for document ranking, and GPT-3.5 for selecting informative passages. For Task 2, we fine-tuned the GPT-3.5 model to identify and explain difficult terms and generate explanations. For Task 3 also, we fine-tuned the GPT-3.5 model with a specific prompt to simplify given scientific abstracts and sentences. The effectiveness of our approach was assessed based on the quality of results, demonstrating the potential of advanced language models in making scientific education more accessible to the general public. Our solution proposes using fine-tuned large language models as a reliable source for scientific education. © 2024 Copyright for this paper by its authors.

关键词： BERT Elastic Search GPT-3.5 Turbo Large Language Models SimpleText Text simplification

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Separation of microalgae from bacterial contaminants using spiral microchannel in the presence of a chemoattractant

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Bioresources and Bioprocessing 2024年第1期11卷 511-525页

作者： Leticia F.Ngum Y.Matsushita Samir F.El-Mashtoly Ahmed M.R.Fath El-Bab Ahmed L Abdel-Mawgood Institute of Basic and Applied Sciences Biotechnology ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Institute of Basic and Applied Sciences Nanoscience ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Mechatronics and Robotics Engineering Department Egypt-Japan University of Science and TechnologyAlexandria 21934Egypt.

Cell separation using microfluidics has become an effective method to isolate biological contaminants from bodily fluids and cell cultures,such as isolating bacteria contaminants from microalgae cultures and isolating bacteria contaminants from white blood *** this study,bacterial cells were used as a model contaminant in microalgae culture in a passive microfluidics device,which relies on hydrodynamic forces to demonstrate the separation of microalgae from bacteria contaminants in U and W-shaped cross-section spiral microchannel fabricated by defocusing CO_(2) laser *** a flow rate of 0.7 ml/min in the presence of glycine as bacteria chemoattractant,the spiral microfluidics devices with U and W-shaped cross-sections were able to isolate microalgae(Desmodesmus sp.)from bacteria(***)with a high separation efficiency of 92%and 96%*** the same flow rate,in the absence of glycine,the separation efficiency of microalgae for U-and W-shaped cross-sections was 91%and 96%,*** was found that the spiral microchannel device with a W-shaped cross-section with a barrier in the center of the channel showed significantly higher separation *** microchannel chips with U-or W-shaped cross-sections were easy to fabricate and exhibited high *** these advantages,these devices could be widely applicable to other cell separation applications,such as separating circulating tumor cells from blood.

关键词： W-shaped cross-section CO_(2)laser ablation Glycine Separation efficiency Removal ratio

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Recent advances on the systems metabolically engineered Pseudomonas species as versatile biosynthetic platforms for the production of polyhydroxyalkanoates

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Systems Microbiology and Biomanufacturing 2024年第2期4卷 473-499页

作者： Hye Min Song Seo Young Jo Haeyoung Lee Subeen Jeon Dohye Yun Chaerin Kim Jina Son Yu Jung Sohn Jong-Il Choi Si Jae Park Department of Chemical Engineering and Materials Science Graduate Program in System Health Science and EngineeringEwha Womans UniversitySeoul 03760Republic of Korea Department of Biotechnology and Bioengineering Chonnam National UniversityGwangju 61186Republic of Korea

Pseudomonas *** been considered one of the most promising microbial platform strains due to its versatile metabolism,enabling the valorization of waste materials into value-added chemical *** the native producer of polyhydroxyal-kanoates(PHAs),the biodegradable biopolyesters,it has been widely engineered by various metabolic engineering tools for the production of PHAs composed of short-chain-length and medium-chain-length monomers with adjustable composition from diverse carbon sources,ranging from pure sugars to crude oils and fatty *** review discusses the feasibility of Pseudomonas *** the industrial host strain and the recent advances regarding the systems metabolic engineering strategies for PHAs production in Pseudomonas sp.

关键词： Pseudomonas sp. Polyhydroxyalkanoates Systems metabolic engineering Synthetic biology Fermentation

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Efficient predictions of formation energies and convex hulls from density functional tight binding calculations

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Journal of Materials science & Technology 2023年第10期141卷 236-244页

作者： Anshuman Kumar Zulfikhar A.Ali Bryan M.Wong Materials Science&Engineering Program University of California-RiversideRiverside92521CAUSA Department of Physics&Astronomy University of California-RiversideRiverside92521CAUSA Materials Science&Engineering Program Department of Chemical&Environmental EngineeringDepartment of Physics&Astronomyand Department of ChemistryUniversity of California-RiversideRiverside92521CAUSA

Defects in materials significantly alter their electronic and structural properties,which affect the per-formance of electronic devices,structural alloys,and functional ***,calculating all the possible defects in complex materials with conventional Density Functional Theory(DFT)can be compu-tationally *** enhance the efficiency of these calculations,we interfaced Density Functional Tight Binding(DFTB)with the Clusters Approach to Statistical Mechanics(CASM)software package for the first *** SiC and ZnO as representative examples,we show that DFTB gives accurate results and can be used as an efficient computational approach for calculating and pre-screening formation ener-gies/convex *** DFTB+CASM implementation allows for an efficient exploration(up to an order of magnitude faster than DFT)of formation energies and convex hulls,which researchers can use to probe other complex systems.

关键词： CASM DFTB DFT Formation energy Convex hull

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Constructing Semantical Structure by Segmentation Integrated Video Embedding for Temporal Action Detection

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IEEE Transactions on Circuits and Systems for Video Technology 2025年第6期35卷 5980-5992页

作者： Zhao, Zixuan Liu, Shuming Zhao, Chengze Zhao, Xu Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China King Abdullah University of Science and Technology Computer Science Program Thuwal23599 Saudi Arabia

Video embedding is the pivot in Temporal Action Detection (TAD). Once the video embedding can robustly capture the essence of actions and perceive activities in complex scenes, the TAD model can more accurately localize action boundaries. Currently, video embedding is typically based on rule-based pixel convolution or cube-based transformer, wherein structured semantic information is intertwined, leading to the submergence of crucial spatial semantic information, such as the intrinsic motion of key semantic objects and interactions among semantic objects. To address these limitations, it is imperative to explore alternative approaches. With the remarkable performance of general semantic segmentation models in visual representation, we introduce the general segmentation model SEEM into the video embedding paradigm, constructing a semantically structured representation from perceptual semantics to cognitive semantics. To more effectively utilize SEEM for structured video representation, we designed the Semantic Adapter (Sem-Adapter) as a bridge to connect the two models. Firstly, we design a Self-Motion Module (SMM) to pay attention to the self-motion of key semantic regions. Secondly, we propose a Mutual Relation Module (MRM) to construct the interactions between semantic regions. Extensive experiments on ActivityNet-1.3, THUMOS-14 and EPIC-Kitchens-100 reveal that our method significantly outperforms state-of-the-art methods under the same input modality, and our method improves the average mAP from 60.6% to 64.2% on THUMOS-14 with the same backbone. The code is available on https://***/shouxiaozixuan/semtad. © 1991-2012 IEEE.

关键词： Semantic Segmentation

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Artificial visual perception neural system using a solution-processable MoS_(2)-based in-memory light sensor

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Light(science & Applications) 2023年第8期12卷 1583-1594页

作者： Dayanand Kumar Lana Joharji Hanrui Li Ayman Rezk Ammar Nayfeh Nazek El-Atab Smart Advanced Memory Devices and Applications(SAMA)LaboratoryElectrical and Computer Engineering ProgramComputer Electrical Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science Khalifa UniversityAbu Dhabi 127788United Arab Emirates

Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing *** study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual *** memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program ***,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 *** larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the *** array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%*** study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.

关键词： visual neural process

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Dictionary-based Sentiment Analysis at Subword Level

Dictionary-based Sentiment Analysis at Subword Level

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2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

作者： Yang, Janghoon Computer Science Program Division of Science and Engineering Penn State Abington AbingtonPA United States

ISBN: (纸本)9798350353464

While deep learning can offer a promising approach to sentiment analysis, it often presents challenges in complexity and explainability. Alternatively, sentiment analysis based on dictionaries has been explored. In this paper, subword-level dictionaries in English are considered to address performance degradation resulting from domain mismatches. To work at subword level, a framework based on naïve bayes machine learning algorithm is exploited. Furthermore, stopwords at the subword level have been proposed to remove additional interference intrinsic to subword tokenization. Numerical experiments demonstrate that the proposed method achieves higher accuracy and F1 scores compared to the conventional dictionary-based method when there is a mismatch between the dictionary and the corpus of documents while performing marginally worse than state-of-the-art deep learning methods when applied to datasets from the same domain. ©2024 IEEE.

关键词： Contrastive Learning

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