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engineering 2025年第1期 12-16页

作者： Wei Xiang Lu Yu Xiaoyuan Chen Marco J.Herold Australian Centre for Artificial Intelligence in Medical Innovation La Trobe University School of Computing Engineering and Mathematical Sciences La Trobe University Department of Diagnostic Radiology Yong Loo Lin School of Medicine National University of Singapore Department of Chemical and Biomolecular Engineering College of Design and Engineering National University of Singapore Department of Biomedical Engineering College of Design and Engineering National University of Singapore Department of Pharmacy and Pharmaceutical Sciences Faculty of Science National University of Singapore Clinical Imaging Research Centre Centre for Translational Medicine Yong Loo Lin School of Medicine National University of Singapore Nanomedicine Translational Research Program Yong Loo Lin School of Medicine National University of Singapore Theranostics Center of Excellence(TCE) Yong Loo Lin School of Medicine National University of Singapore Institute of Molecular and Cell Biology Agency for Science Technology and Research(A*STAR) Olivia Newton-John Cancer Research Institute School of Cancer Medicine La Trobe University The Walter and Eliza Hall Institute of Medical Research Department of Medical Biology University of Melbourne

1. Introduction Cancer continues to be a major cause of global mortality rates, with conventional treatments such as chemotherapy and radiotherapy exhibiting inconsistent efficacy, high costs, and considerable side effects. Over the past decade, a promising alternative has emerged: cancer immunotherapy, which leverages the body's immune system to identify and eradicate cancer cells [1].

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Sp(2N) Yang-Mills theories on the lattice: scale setting and topology

arXiv

引用

arXiv 2022年

作者： Bennett, Ed Hong, Deog Ki Lee, Jong-Wan Lin, C.-J. David Lucini, Biagio Piai, Maurizio Vadacchino, Davide Swansea Academy of Advanced Computing Swansea University Fabian Way Swansea WalesSA1 8EN United Kingdom Department of Physics Pusan National University Busan46241 Korea Republic of Institute for Extreme Physics Pusan National University Busan46241 Korea Republic of Institute of Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Center for High Energy Physics Chung-Yuan Christian University Chung-Li32023 Taiwan Centre for Theoretical and Computational Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Physics Division National Centre for Theoretical Sciences Taipei10617 Taiwan Department of Mathematics Faculty of Science and Engineering Swansea University Fabian Way Swansea WalesSA1 8EN United Kingdom Department of Physics Faculty of Science and Engineering Swansea University Singleton Park Swansea WalesSA2 8PP United Kingdom School of Mathematics Hamilton Mathematics Institute Trinity College Dublin 2 Ireland Centre for Mathematical Sciences University of Plymouth PlymouthPL4 8AA United Kingdom

We study Yang-Mills lattice theories with Sp(Nc) gauge group, with Nc = 2N, for N = 1, ···, 4. We show that if we divide the renormalised couplings appearing in the Wilson flow by the quadratic Casimir C2(F) of the Sp(Nc) group, then the resulting quantities display a good agreement among all values of Nc considered, over a finite interval in flow time. We use this scaled version of the Wilson flow as a scale-setting procedure, compute the topological susceptibility of the Sp(Nc) theories, and extrapolate the results to the continuum limit for each Nc. © 2022, CC BY.

关键词： Lattice theory

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Stereoscopic human detection in a natural environment

Annals of Emerging Technologies in Computing

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Annals of Emerging Technologies in computing 2018年第2期2卷 15-23页

作者： Davies, Ross Wilson, Ian Ware, Andrew Faculty of Computing Engineering and Science University of South Wales United Kingdom

The algorithm presented in this paper is designed to detect people in real-time from 3D footage for use in Augmented Reality applications. Techniques are discussed that hold potential for a detection system when combined with stereoscopic video capture using the extra depth included in the footage. This information allows for the production of a robust and reliable system. To utilise stereoscopic imagery, two separate images are analysed, combined and the human region detected and extracted. The greatest benefit of this system is the second image, which contains additional information to which conventional systems do not have access, such as the depth perception in the overlapping field of view from the cameras. We describe the motivation behind using 3D footage and the technical complexity of human detection. The system is analysed for both indoor and outdoor usage, when detecting human regions. The developed system has further uses in the field of motion capture, computer gaming and augmented reality. Novelty comes from the camera not being fixed to a single point. Instead, the camera is subject to six degrees of freedom (DOF). In addition, the algorithm is designed to be used as a first filter to extract feature points in input video frames faster than real-time. © 2018 by the author(s).

关键词： Cameras

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Geometric analysis of oscillations in the frzilator model

arXiv

引用

arXiv 2019年

作者： Taghvafard, Hadi Jardón-Kojakhmetov, Hildeberto Szmolyan, Peter Cao, Ming Engineering and Technology Institute Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Faculty of Mathematics Technical University of Munich München85748 Germany Institute for Analysis and Scientific Computing Technische Universität Wien 1040 Wien Austria

A biochemical oscillator model, describing developmental stage of myxobacteria, is analyzed mathematically. Observations from numerical simulations show that in a certain range of parameters, the corresponding system of ordinary differential equations displays stable and robust oscillations. In this work, we use geometric singular perturbation theory and blow-up method to prove the existence of a strongly attracting limit cycle. This cycle corresponds to a relaxation oscillation of an auxiliary system, whose singular perturbation nature originates from the small Michaelis-Menten constants of the biochemical model. In addition, we give a detailed description of the structure of the limit cycle, and the timescales along it. Copyright © 2019, The Authors. All rights reserved.

关键词： Biochemistry

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Thermal conductivity and rheological behavior of silica / simulated body fluid - Dispersed Hardystonite and Åkermanite nanofluids: X-ray diffraction to analyze structure and morphology of a bio-ceramic

引用

International Communications in Heat and Mass Transfer 2025年 165卷

作者： Liu, Shulong Saidani, Taoufik Feng, Dulong Alawi, Mohammed Jameel Hussien, Mohamed Deebani, Wejdan Anhui Province Key Laboratory of Intelligent Computing and Applications Huaibei Normal University Huaibei235000 China Anhui Province Industrial Generic Technology Research Center for Alumics Materials Huaibei Normal University Huaibei235000 China School of Physics and Electronic Information Huaibei Normal University Huaibei235000 China Center for Scientific Research and Entrepreneurship Northern Border University Arar73213 Saudi Arabia Anhui Guangbo Mechanical Electronic Manufacturing Co. Ltd. Huaibei235000 China Electrical Engineering Department College of Engineering and Architecture Umm Al-Qura University Makkah Saudi Arabia Department of Chemistry Faculty of Science King Khalid University P.O. Box 9004 Abha61413 Saudi Arabia Department of Mathematics College of Science & Arts King Abdul Aziz University Rabigh21911 Saudi Arabia

Bioceramics are integral in biomedical applications due to their biocompatibility, bioactivity, and mechanical properties. This study compares the thermal and rheological behavior of two hybrid bio-nanofluids (bi-ns): Hardystonite/Silica and Åkermanite/Silica dispersed in simulated body fluid (SBF). Nanoparticle morphology and composition were analyzed using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM), confirming the crystalline phases of both composites. Åkermanite/Silica showed better dispersion stability, with a higher zeta potential (−16.19 mV) than Hardystonite/Silica (−7.23 mV). The addition of silica (SiO2) improved stability for both, with zeta potential increases of ∼203 % and 69 %, respectively. Thermal conductivity of both nanofluids increased with temperature and volume fraction, with Åkermanite/Silica achieving a maximum enhancement of 13.16 % (20–40 °C). However, both showed negative thermal conductivity enhancements compared to SBF, especially at higher concentrations. Hardystonite/Silica demonstrated greater thermal compatibility with SBF. Rheologically, both nanofluids exhibited shear-thinning behavior. Hardystonite/Silica showed a stronger reduction in viscosity with temperature increase—up to 43.43 % at 0.25 % volume fraction—compared to 32.74 % for Åkermanite/Silica. These results highlight the interaction between thermal and flow properties in bi-ns, indicating that Hardystonite/Silica may be better suited for applications requiring thermal compatibility and viscosity control. The findings contribute to the optimization of hybrid nanofluids for bone-related biomedical applications. © 2025 Elsevier Ltd

关键词： Medical nanotechnology

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Observation of the Crab Nebula with LHAASO-KM2A−a performance study

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Chinese Physics C 2021年第2期45卷 518-530页

作者： F.Aharonian Q.An Axikegu L.X.Bai Y.X.Bai Y.W.Bao D.Bastieri X.J.Bi Y.J.Bi H.Cai J.T.Cai Z.Cao J.Chang J.F.Chang X.C.Chang B.M.Chen J.Chen L.Chen M.J.Chen M.L.Chen Q.H.Chen S.H.Chen S.Z.Chen T.L.Chen X.L.Chen Y.Chen N.Cheng Y.D.Cheng S.W.Cui X.H.Cui Y.D.Cui B.Z.Dai H.L.Dai Z.G.Dai D.della Volpe B.D'Ettorre Piazzoli X.J.Dong J.H.Fan Y.Z.Fan Z.X.Fan J.Fang K.Fang C.F.Feng L.Feng S.H.Feng Y.L.Feng B.Gao C.D.Gao Q.Gao W.Gao M.M.Ge L.S.Geng G.H.Gong Q.B.Gou M.H.Gu J.G.Guo X.L.Guo Y.Q.Guo Y.Y.Guo Y.A.Han H.H.He H.N.He J.C.He S.L.He X.B.He Y.He M.Heller Y.K.Hor C.Hou X.Hou H.B.Hu S.Hu S.C.Hu X.J.Hu D.H.Huang Q.L.Huang W.H.Huang X.T.Huang Z.C.Huang F.Ji X.L.Ji H.Y.Jia K.Jiang Z.J.Jiang C.Jin D.Kuleshov K.Levochkin B.B.Li C.Li F.Li H.B.Li H.C.Li H.Y.Li J.Li K.Li W.L.Li X.Li X.R.Li Y.Li Y.Z.Li Z.Li E.W.Liang Y.F.Liang S.J.Lin B.Liu C.Liu D.Liu H.Liu H.D.Liu J.Liu J.L.Liu J.S.Liu J.Y.Liu M.Y.Liu R.Y.Liu S.M.Liu W.Liu Y.N.Liu Z.X.Liu W.J.Long R.Lu H.K.Lv B.Q.Ma L.L.Ma X.H.Ma J.R.Mao A.Masood W.Mitthumsiri T.Montaruli Y.C.Nan B.Y.Pang P.Pattarakijwanich Z.Y.Pei M.Y.Qi D.Ruffolo V.Rulev A.Sáiz L.Shao O.Shchegolev X.D.Sheng J.R.Shi H.C.Song Yu.V.Stenkin V.Stepanov Q.N.Sun X.N.Sun Z.B.Sun P.H.T.Tam Z.B.Tang W.W.Tian B.D.Wang C.Wang H.Wang H.G.Wang J.C.Wang J.S.Wang L.P.Wang L.Y.Wang R.N.Wang W.Wang X.G.Wang X.J.Wang X.Y.Wang Y.D.Wang Y.J.Wang Y.P.Wang Z.Wang Z.H.Wang Z.X.Wang D.M.Wei J.J.Wei Y.J.Wei T.Wen C.Y.Wu H.R.Wu S.Wu W.X.Wu X.F.Wu S.Q.Xi J.Xia J.J.Xia G.M.Xiang G.Xiao H.B.Xiao G.G.Xin Y.L.Xin Y.Xing D.L.Xu R.X.Xu L.Xue D.H.Yan C.W.Yang F.F.Yang J.Y.Yang L.L.Yang M.J.Yang R.Z.Yang S.B.Yang Y.H.Yao Z.G.Yao Y.M.Ye L.Q.Yin N.Yin X.H.You Z.Y.You Y.H.Yu Q.Yuan H.D.Zeng T.X.Zeng W.Zeng Z.K.Zeng M.Zha X.X.Zhai B.B.Zhang H.M.Zhang H.Y.Zhang J.L.Zhang J.W.Zhang L.Zhang L.X.Zhang P.F.Zhang P.P.Zhang R.Zhang S.R.Zhang S.S.Zhang X.Zhang X.P.Zhang Y.Zhang Y.F.Zhang Y.L.Zhang B.Zhao J.Zhao L.Zhao L.Z.Zhao S.P.Zhao F.Zheng Y.Zheng B.Zhou H.Zhou J.N.Zhou P.Zhou R.Zhou X.X.Zhou C.G.Zhu F.R.Zhu H.Zhu K.J.Zhu X.Zuo Key Laboratory of Particle Astrophyics&Experimental Physics Division&Computing Center Institute of High Energy PhysicsChinese Academy of Sciences100049 BeijingChina University of Chinese Academy of Sciences 100049 BeijingChina TIANFU Cosmic Ray Research Center ChengduSichuanChina State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China 230026 HefeiAnhuiChina Department of Engineering Physics Tsinghua University100084 BeijingChina National Astronomical Observatories Chinese Academy of Sciences100101 BeijingChina National Space Science Center Chinese Academy of Sciences100190 BeijingChina School of Physics Peking University100871 BeijingChina Center for Astrophysics Guangzhou University510006 GuangzhouGuangdongChina School of Physics and Astronomy&School of Physics(Guangzhou) Sun Yat-sen University519000 ZhuhaiGuangdongChina School of Physical Science and Technology Guangxi University530004 NanningGuangxiChina Hebei Normal University 050024 ShijiazhuangHebeiChina School of Physics and Microelectronics Zhengzhou University450001 ZhengzhouHenanChina School of Astronomy and Space Science Nanjing University210023 NanjingJiangsuChina Key Laboratory of Dark Matter and Space Astronomy Purple Mountain ObservatoryChinese Academy of Sciences210023 NanjingJiangsuChina Institute of Frontier and Interdisciplinary Science Shandong University266237 QingdaoShandongChina Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical ObservatoryChinese Academy of Sciences200030 ShanghaiChina Tsung-Dao Lee Institute&School of Physics and Astronomy Shanghai Jiao Tong University200240 ShanghaiChina School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong University610031 ChengduSichuanChina College of Physics Sichuan University610065 ChengduSichuanChina Key Laboratory of Cosmic Rays(Tibet University) Ministry of Education850000 LhasaTibetChina School of Physics and Tec

A sub-array of the Large High Altitude Air Shower Observatory(LHAASO),KM2A is mainly designed to observe a large fraction of the northern sky to hunt for γ-ray sources at energies above 10 *** though the detector construction is still underway,half of the KM2A array has been operating stably since the end of *** this paper,we present the KM2A data analysis pipeline and the first observation of the Crab Nebula,a standard candle in very high energy γ-ray *** detect γ-ray signals from the Crab Nebula in both energy ranges of 10-100 TeV and>100 TeV with high significance,by analyzing the KM2A data of 136 live days between December 2019 and May *** the observations,we test the detector performance,including angular resolution,pointing accuracy and cosmic-ray background rejection *** energy spectrum of the Crab Nebula in the energy range 10-250 TeV fits well with a single power-law function dN/dE=(1.13±0.05stat±0.08sys)×10^(-14).(E/20 TeV)-309±0.06stat±0.02syscm^(-2) s^(-1) TeV^(-1).It is consistent with previous measurements by other *** opens a new window of γ-ray astronomy above 0.1 PeV through which new ultrahigh-energy γ-ray phenomena,such as cosmic PeVatrons,might be discovered.

关键词： γ-ray Crab Nebula extensive air showers cosmic rays

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Enhanced heat transfer in nanofluid flow via prabhakar fractional models for solar thermal systems

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Journal of Radiation Research and Applied sciences 2025年第3期18卷

作者： Shajar Abbas Ghada Ragheb Elnaggar Ahmad Shafique Ioan-Lucian Popa S. Saleem Muhammad Ramzan Mumtaz Ahmad Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University Multan Pakistan AS (Ayub Shah) Institute of Mathematics and Research Centre Multan Pakistan Industrial and Systems Engineering Department College of Engineering Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Computing Mathematics and Electronics “1 Decembrie 1918” University of Alba Iulia 15 510009 Alba Iulia Romania Faculty of Mathematics and Computer Science Transilvania University of Brasov Iuliu Maniu Street 50 500091 Brasov Romania Department of Mathematics College of Science King Khalid University Abha 61413 Saudi Arabia Center for Artificial Intelligence (CAI) King Khalid University Abha 61421 Saudi Arabia Department of Mathematics University of Sargodha Sargodha Pakistan

This study presents a comprehensive thermal analysis of non-Newtonian nanofluid flow influenced by solar thermal radiation, with direct applications in industrial engineering, renewable energy systems, and thermal management. The objective is to evaluate the performance of a second-grade nanofluid in a parabolic trough solar collector (PTSC), focusing on the impacts of chemical reaction, mass and heat transport. The model assumes a copper–PVA-water nanofluid infused with gyrotactic microorganisms to enhance thermal conductivity and bioconvection. The dimensionless governing equations for velocity, temperature, concentration, and bioconvection are formulated using Fourier's and Fick's laws and calculated analytically via the Laplace integral transform. Results reveal that a 10 % increase in nanoparticle volume fraction leads to a 15 % improvement in temperature distribution, while the electric field parameter increases fluid velocity by 12 %. Aditionally, increase in bioconvection Lewis and Peclet numbers significantly reduce microorganism concentration by approximately 20 %. The study demonstrates that fractional-order models offer better control of transport mechanisms and that second-grade nanofluids improve heat transfer efficiency. These findings highlights the promise of of such fluids in solar thermal systems, industrial engineering processes, and energy-efficient system design.

关键词： Solar radiation Prabhakar derivative Gyrotactic microorganisms Laplace integral transform

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COVID-19 mRNA Vaccine Degradation Prediction Using LR and LGBM Algorithms

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Journal of Physics: Conference Series 2021年第1期1997卷

作者： Soon Hwai Ing Azian Azamimi Abdullah Nor Hazlyna Harun Shigehiko Kanaya Faculty of Electronic Engineering Technology Universiti Malaysia Perlis (UniMAP) Perlis Malaysia. Medical Devices and Life Sciences Cluster Sport Engineering Research Centre Centre of Excellence (SERC) Universiti Malaysia Perlis (UniMAP) Perlis Malaysia. Data Science Research Lab School of Computing School of Computing Universiti Utara Malaysia Sintok Kedah. Computational Systems Biology Lab Graduate School of Information Science Nara Institute of Science and Technology Ikoma Nara Japan.

The threatening Coronavirus which was assigned as the global pandemic concussed not only the public health but society, economy and every walks of life. Some measurements are taken to stifle the spread and one of the best ways is to carry out some precautions to prevent the contagion of SARS-CoV-2 virus to uninfected populaces. Injecting prevention vaccines is one of the precaution steps under the grandiose blueprint. Among all vaccines, it is found that mRNA vaccine which shows no side effect with marvellous effectiveness is the most preferable candidates to be considered. However, degradation had become its biggest drawback to be implemented. Hereby, this study is held with desideratum to develop prediction models specifically to predict the degradation rate of mRNA vaccine for COVID-19. Two machine learning algorithms, which are, Linear Regression (LR) and Light Gradient Boosting Machine (LGBM) are proposed for models development using Python language. Dataset comprises of thousands of RNA molecules that holds degradation rates at each position from Eterna platform is extracted, pre-processed and encoded with label encoding before loaded into algorithms. The results show that LGBM (0.2447) performs better than LR (0.3957) for this study when evaluated with the RMSE metric.

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Historical tree phenology data reveal the seasonal rhythms of the Congo Basin rainforest

Plant-Environment Interactions

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Plant-Environment Interactions 2024年第2期5卷 e10136页

作者： Kearsley, Elizabeth Verbeeck, Hans Stoffelen, Piet Janssens, Steven B. Yakusu, Emmanuel Kasongo Kosmala, Margaret De Mil, Tom Bauters, Marijn Kitima, Elasi Ramanzani Ndiapo, José Mbifo Chuda, Adelard Lonema Richardson, Andrew D. Wingate, Lisa Ilondea, Bhély Angoboy Beeckman, Hans van den Bulcke, Jan Boeckx, Pascal Hufkens, Koen Computational and Applied Vegetation Ecology Lab Department of Environment Faculty of Bioscience Engineering Ghent University Gent Belgium BlueGreen Labs Melsele Belgium Meise Botanic Garden Meise Belgium Department of Biology Leuven Plant Institute KULeuven Leuven Belgium UGent-Woodlab (Laboratory of Wood Technology) Department of Environment Faculty of Bioscience Engineering Ghent University Gent Belgium Service of Wood Biology Royal Museum for Central Africa Tervuren Belgium Faculté de gestion des ressources naturelles renouvelables Université de Kisangani Kisangani Democratic Republic Congo Department of Organismic and Evolutionary Biology Harvard University Cambridge MA United States CIBO Technologies Cambridge MA United States Forest is Life TERRA Teaching and Research Centre Gembloux Agro Bio-Tech University of Liège Gembloux Belgium Isotope Bioscience Laboratory - ISOFYS Department of Green Chemistry and Technology Ghent University Gent Belgium Research Group of Plants and Ecosystems (PLECO) Department of Biology University of Antwerp Wilrijk Belgium Institut National pour l'Etude et la Recherche Agronomiques-INERA Yangambi Democratic Republic Congo Center for Ecosystem Science and Society Northern Arizona University Flagstaff AZ United States School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff AZ United States INRAE UMR ISPA Villenave d'Ornon France Institut National pour l'Étude et la Recherche Agronomiques Kinshasa Democratic Republic Congo

Tropical forest phenology directly affects regional carbon cycles, but the relation between species-specific and whole-canopy phenology remains largely uncharacterized. We present a unique analysis of historical tropical tree phenology collected in the central Congo Basin, before large-scale impacts of human-induced climate change. Ground-based long-term (1937–1956) phenological observations of 140 tropical tree species are recovered, species-specific phenological patterns analyzed and related to historical meteorological records, and scaled to characterize stand-level canopy dynamics. High phenological variability within and across species and in climate–phenology relationships is observed. The onset of leaf phenophases in deciduous species was triggered by drought and light availability for a subset of species and showed a species-specific decoupling in time along a bi-modal seasonality. The majority of the species remain evergreen, although central African forests experience relatively low rainfall. Annually a maximum of 1.5% of the canopy is in leaf senescence or leaf turnover, with overall phenological variability dominated by a few deciduous species, while substantial variability is attributed to asynchronous events of large and/or abundant trees. Our results underscore the importance of accounting for constituent signals in canopy-wide scaling and the interpretation of remotely sensed phenology signals. © 2024 The Authors. Plant-Environment Interactions published by New Phytologist Foundation and John Wiley & Sons Ltd.

关键词： leaf senescence leaf turnover phenology scaling tropical forest

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Partition-aware adaptive switching neural networks for post-processing in HEVC

arXiv

引用

arXiv 2019年

作者： Lin, Weiyao He, Xiaoyi Han, Xintong Liu, Dong See, John Zou, Junni Xiong, Hongkai Wu, Feng Department of Electronic Engineering Shanghai Jiao Tong University China Huya Inc. China Faculty of Computing and Informatics Multimedia University Malaysia Department of Computer Science and Engineering Shanghai Jiao Tong University China School of Information Science and Technology University of Science and Technology of China

This paper addresses neural network based post-processing for the state-of-the-art video coding standard, High Efficiency Video Coding (HEVC). We first propose a partition-aware Convolution Neural Network (CNN) that utilizes the partition information produced by the encoder to assist in the post-processing. In contrast to existing CNN-based approaches, which only take the decoded frame as input, the proposed approach considers the coding unit (CU) size information and combines it with the distorted decoded frame such that the artifacts introduced by HEVC are efficiently reduced. We further introduce an adaptive-switching neural network (ASN) that consists of multiple independent CNNs to adaptively handle the variations in content and distortion within compressed-video frames, providing further reduction in visual artifacts. Additionally, an iterative training procedure is proposed to train these independent CNNs attentively on different local patch-wise classes. Experiments on benchmark sequences demonstrate the effectiveness of our partition-aware and adaptive-switching neural networks. The project page can be found in http://***/lwydemo/***. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

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