Enhanced optical and structural traits of irradiated lead borate glasses via Ce3+ and Dy3+ ions with studying Radiation shielding performance by O. I. Sallam, Y. S. Rammah, Islam M. Nabil, Ahmed M. A. El-Seidy

“…The samples were also tested before and after exposure to gamma irradiation from a 60Co source at a dose of 75 kGy to assess their stability against radiation. …”
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Deteksi Kejadian Lalu Lintas pada Teks Twitter dengan Pendekatan Klasidikasi Multi-Label Berbasis Deep Learning by Luthfi Atikah, Diana Purwitasari, Nanik Suciati

“…This can be detrimental to road users, therefore it is necessary to detect traffic events accurately and efficiently. Currently, Twitter is used as a source of information to detect an incident. …”
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MALDI imaging mass spectrometry differentiates basal cell carcinoma from trichoblastoma and trichoepithelioma: A proof of principle study. by Jennifer M C Ranes, Jessica L Moore, Nathan H Patterson, Sarah P Nicholson, Sara Kantrow, Jason Robbins, Richard M Caprioloi, Jeremy L Norris, Rami N Al-Rohil

“…The limitations of this study included a small sample set, which included easily identifiable cases obtained from a single tissue source.<h4>Conclusions</h4>Our study proves that BCC and TB/TE exhibit different proteomic profiles that one can use to enable accurate differential diagnosis. …”
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Fire and Ice in the Whirlpool: Spatially Resolved Scaling Relations between X-Ray-emitting Hot Gas and Cold Molecular Gas in M51 by Chunyi Zhang, Junfeng Wang, Tian-Wen Cao

“…We demonstrate that the core-collapse supernovae (SNe) are the primary source of energy for heating gas in the galactic center of M51, leading to the observed steep ${L}_{0.5-2\,{\rm{keV}}}^{{\rm{gas}}}$ – L _IR and ${L}_{0.5-2\,{\rm{keV}}}^{{\rm{gas}}}$ – ${L}_{{\rm{gas}}}^{{\rm{{\prime} }}}$ relations, as their X-ray radiation efficiencies ( η  ≡  ${L}_{0.5-2\,{\rm{keV}}}^{{\rm{gas}}}$ / ${\dot{E}}_{{\rm{SN}}}$ ) increase with the star formation rate surface densities (Σ _SFR ), where ${\dot{E}}_{{\rm{SN}}}$ is the SN mechanical energy input rate.…”
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Research on optimization technology of new pipeline design for regional natural gas pipeline network by Jingyi CUI, Kunfeng ZHU, Cuixian GAO, Li GU, Jing REN, Yuxing LI, Wuchang WANG

“…There is an urgent need to develop a set of design optimization methods suitable for complex pipeline network systems with multiple gas sources, numerous users, and aging pipeline infrastructures. …”
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Taguchi Method-Based Synthesis of a Circular Antenna Array for Enhanced IoT Applications by Wided Amara, Ramzi Kheder, Ridha Ghayoula, Issam El Gmati, Amor Smida, Jaouhar Fattahi, Lassaad Latrach

“…To address this limitation, the synthesis method utilizing the Taguchi approach, originally designed for linear arrays, can be effectively extended to two-dimensional or planar antenna arrays. …”
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Experimental determination and theoretical calculation for CO2 liquid-solid phase equilibrium in PLNG by Zihe LI, Jianlu ZHU, Qing MIAO, Feng YAN, Xin OUYANG, Chaofei NIE, Hui HAN, Yuxing LI

“…However, their current high cost presents challenges in terms of economic efficiency for some gas fields, limiting their widespread adoption and application to some extent. …”
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New method for landslide susceptibility evaluation in alpine valley regions that considers the suitability of InSAR monitoring and introduces deformation rate grading by Dingyi Zhou, Zhifang Zhao, Wenfei Xi, Xin Zhao, Jiangqin Chao

“…Incorporating Interferometric Synthetic Aperture Radar (InSAR) data sources into the landslide susceptibility evaluation process has yielded favorable outcomes in some studies. …”
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Building sustainable information systems and transformer models on demand by Thomas Asselborn, Sylvia Melzer, Simon Schiff, Magnus Bender, Florian Andreas Marwitz, Said Aljoumani, Stefan Thiemann, Konrad Hirschler, Ralf Möller

“…On the other hand, we have developed a chatbot that not only provides project-specific responses but also references the sources.…”
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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…These approaches have network sparsity and data nonlinearity problems, and they do not even capture the intricate relationships between various information sources. Deep learning approaches like graph autoencoders are utilized to perform anomaly detection through obtaining node embeddings while dealing with the network nonlinearity and sparsity issues. …”
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Unveiling Theranostics: Nanocomplex-Assisted Photodynamic Eradication of Aggressive Cancer Cells and Modulation of Tumor-Associated Macrophages by Butkute A, Kazlauske E, Mlynska A, Peciukaityte E, Karabanovas V, Rotomskis R, Steponkiene S

“…The nanocomplex accumulated efficiently and uniformly across all CRC cell lines, regardless of their aggressiveness or drug sensitivity. …”
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Integrating Artificial Intelligence in urban redesign: A collaborative approach to post-war design phases by I. Alshafei, R. Almashhour

“…The study structure is a literature review and theoretical approach development, data collection, and analysis, depending on multiple sources, including government reports and academic research, as well as hybrid approach development.FINDINGS: The discussion provides theoretical evidence of the potential advances in this empirical approach, highlighting the efficiency improvements achievable by using Artificial Intelligence technologies in a hybrid phased approach that integrates traditional post-war processes with Artificial Intelligence -assisted ones. …”
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An Adiabatic-Expansion-Induced Perturbation Study on Gas–Aerosol Partitioning in Ambient Air—Formation of NH₄NO₃ and Microdroplet Nitrogen Fixation (2) by Yating Gao, Qinchu Fan, Yujiao Zhu, Hengqing Shen, Qi Yuan, Yang Gao, Huiwang Gao, Xiaohong Yao

“…Recent observations have increasingly challenged the conventional understanding of atmospheric NH₃ and its potential sources in remote environments. Laboratory studies suggest that the microdroplet redox generation of NH₃ could offer an alternative explanation. …”
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Generation of effective and specific human TCRs against tumor/testis antigen NY-ESO-1 in mice with humanized T cell recognition system by Xiaojing Tina Chen, Xiaojing Tina Chen, Matthias Leisegang, Matthias Leisegang, Ioannis Gavvovidis, Ioannis Gavvovidis, Seth M. Pollack, Felix K. M. Lorenz, Ton N. Schumacher, Ton N. Schumacher, Oliver Daumke, Thomas Blankenstein

“…Our data indicate that highly effective TCRs against NY-ESO-1 are likely deleted in humans due to tolerance mechanisms, and that the TCR gene loci transgenic mice represent a reliable source to isolate effective and highly-specific TCRs for adoptive T cell therapies.…”
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Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs by Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan

“…These results highlight the potential of combining advanced thermodynamic systems with machine learning methodologies to improve the efficiency and effectiveness of renewable energy sources.…”
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Chondroitin Sulfate-Based Imatinib Nanoparticles Targeting Activated Hepatic Stellate Cells Against Hepatic Fibrosis by Xunzhi Liu, Changlong Fang, Hongling Yu, Lu Huang, Jiaxing Feng, Shiqin Luo, Li Song, Mengying Wu, Yulu Tan, Jianxia Dong, Tao Gong, Peihong Xiao

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Heat Re-process approach and thermally integrated renewable energy system for power, compressed hydrogen, and freshwater production; ANN boosted optimization and techno-enviro-econ... by Zhaoyang Zuo, Junhua Wang, Mohammed A. Alghassab, Nashwan Adnan Othman, Ahmad Almadhor, Fahad M. Alhomayani, Hind Albalawi, Samah G. Babiker, Barno Abdullaeva, Aboulbaba Eladeb

“…Ultimately, the optimized simulation utilizing a hybrid machine learning approach achieved a peak exergy efficiency of 27.37 % and a minimized total cost rate of 96.2 $/h. …”
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FLAML version 2.3.3 model-based assessment of gross primary productivity at forest, grassland, and cropland ecosystem sites by J. Lai, J. Lai, Y. Zhang, A. Wang, W. Fei, Y. Diao, R. Li, J. Wu

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Development of neutron diffusion and transport algorithms based on finite volume method by LI Wei, LIU Xiaojing, CHAI Xiang, ZHAO Pengcheng

“…Simultaneous solutions to the conservation equations of multiple physics fields need to be pursued, providing a unified approach to modeling, discretization, and iterative computation processes.PurposeThis study aims to achieve discrete and iterative solutions for multigroup neutron diffusion equations and neutron transport equations, considering the strong coupling between neutronics and thermal-hydraulics.MethodsFirstly, based on the open-source computational fluid dynamics (CFD) platform OpenFOAM, the finite volume method (FVM) was employed to discretize the control equations for neutron diffusion and neutron transport using the Gauss theorem. …”
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A deep learning-based reconstruction model for 3D sound speed field combining underwater vertical information by Hongchen Li, Yuhang Liu, Ming Li, Penghao Wang, Yuhang Zhu, Kefeng Mao, Xi Chen

“…The usual used single empirical orthogonal function (sEOF) method, which reconstructs sound speed profiles (SSP) by establishing statistical relationships between empirical orthogonal coefficients of SSP and sea surface environmental factors, may have several limitations: (1) The principal modes extracted by the EOF method may lose some sound speed information, resulting in low reconstruction accuracy; (2) The grid-by-grid inversion of SSP is computationally inefficient for acquiring large-scale 3D sound speed fields; (3) Oceanic dynamic activities cause disturbances in the sound speed field, and relying solely on sea surface environmental information can limit the accuracy of full-ocean-depth sound speed inversion.MethodIn this paper, we propose a region-oriented reconstruction model named 3dCNN-DEN for 3D sound speed fields using the Convolutional Neural Network (CNN). The model utilizes multi-source satellite remote sensing data and CMEMS temperature-salinity reanalysis data, simultaneously incorporating sea surface environmental factors (SST, SLA, and EKE) and underwater information (average density) as inputs. …”
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