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Simultaneous creation of multiple vortex-antivortex pairs in momentum space in photonic lattices

Advanced Photonics 2023年第6期5卷 92-100页

作者： Feng Li Sergei V.Koniakhin Anton V.Nalitov Evgeniia Cherotchenko Dmitry D.Solnyshkov Guillaume Malpuech Min Xiao Yanpeng Zhang Zhaoyang Zhang Xi'an Jiaotong University Key Laboratory for Physical Electronics and Devices of the Ministry of EducationShaanxi Key Laboratory of Information Photonic TechniqueSchool of Electronic Science and EngineeringFaculty of Electronics and InformationXi’anChina Institute for Basic Science Center for Theoretical Physics of Complex SystemsDaejeonRepublic of Korea Korea University of Science and Technology(UST) Basic Science ProgramDaejeonRepublic of Korea Moscow Institute of Physics and Technology DolgoprudnyiRussia University of Wolverhampton Faculty of Science and EngineeringWolverhamptonUnited Kingdom ITMO University St.PetersburgRussia Ioffe Institute St.PetersburgRussia UniversitéClermont Auvergne Institut PascalPHOTON-N2CNRSClermont INPClermont-FerrandFrance Institut Universitaire de France ParisFrance University of Arkansas Department of PhysicsFayettevilleArkansasUnited States Nanjing University School of PhysicsNational Laboratory of Solid State MicrostructuresNanjingChina

engineering of the orbital angular momentum(OAM)of light due to interaction with photonic lattices reveals rich physics and motivates potential *** report the experimental creation of regularly distributed quantized vortex arrays in momentum space by probing the honeycomb and hexagonal photonic lattices with a single focused Gaussian *** the honeycomb lattice,the vortices are associated with Dirac ***,we show that the resulting spatial patterns of vortices are strongly defined by the symmetry of the wave packet evolving in the photonic lattices and not by their topological *** findings reveal the underlying physics by connecting the symmetry and OAM conversion and provide a simple and efficient method to create regularly distributed multiple vortices from unstructured light.

关键词： vortex photonic lattice orbital angular momentum topology symmetry

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Characterization of Polyimide Thin Films on Metals

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MRS Online Proceedings Library 2020年第1期264卷 199-204页

作者： Jiong-Ping Lu Pradnya V. Nagarkar David Volfson Klavs F. Jensen Stephen D. Senturia Electronics Packaging Program and Departments of Chemical Electrical and Materials Engineering Massachusetts Institute of Technology Cambridge

We describe an approach using thin films on metals as models to study interfacial interactions. Thin films of biphenyl-tetracarboxylic dianhydride (BPDA) - p-phenylene diamine (PPD) based polyimide on Cr and Au surfaces have been investigated using infrared reflection absorption spectroscopy (IRRAS) and x-ray photoelectron spectroscopy (XPS). IRRAS was used for in-situ monitoring of polymer curing processes. Cured polyimide thin films on metals were characterized ex-situ by both XPS and IRRAS. Anhydride was observed to be an intermediate during chemical transformation of polyamic acid to polyimide. Imidization processes were found to be completed after curing at 250°C for thin films. Strong chemical modification of polyimide thin films resulting from interaction with Cr substrates were observed by infrared spectroscopy. These observations were consistent with angle-resolved XPS data showing a different C 1s emission spectrum of polyimide-Cr interfacial region, compared to the polyimide spectrum.

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Exhaled volatile organic compounds for cholangiocarcinoma diagnosis

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Liver Research 2022年第3期6卷 191-197页

作者： Nanicha Siriwong Thanikan Sukaram Rossarin Tansawat Terapap Apiparakoon Thodsawit Tiyarattanachai Sanparith Marukatat Rungsun Rerknimitr Roongruedee Chaiteerakij Department of Medicine Faculty of MedicineChulalongkorn UniversityBangkokThailand Division of Gastroenterology Department of MedicineFaculty of MedicineChulalongkorn Universityand King Chulalongkorn Memorial HospitalThai Red Cross SocietyBangkokThailand Department of Food and Pharmaceutical Chemistry Faculty of Pharmaceutical SciencesChulalongkorn UniversityBangkokThailand Department of Computer Engineering Faculty of EngineeringChulalongkorn UniversityBangkokThailand Clinical Sciences PhD International Program Faculty of MedicineChulalongkorn UniversityThailand Image Processing and Understanding Team Artificial Intelligence Research GroupNational Electronics and Computer Technology Center(NECTEC)Thailand Center of Excellence for Innovation and Endoscopy in Gastrointestinal Oncology Chulalongkorn UniversityBangkokThailand

Objectives:The difficulties in the early detection consequent to the lack of sensitive biomarkers render patients with cholangiocarcinoma(CCA)to have poor ***,sensitive and specific volatile organic compounds(VOCs)were identified in several ***,the VOC profiles in CCA are not ***,we investigated the VOC profiles in exhaled breath of CCA patients and ***:We prospectively collected exhaled breath samples from 30 consecutive patients newly diagnosed with CCA and 30 controls who did not have CCA(seven had benign biliary strictures and 23 had other medical conditions).Exhaled VOCs were identified using gas chromatography mass spectrometry Triple Quadrupoles *** of the significant differences in VOCs between cases and controls was conducted using supervised multivariate regression *** validation was performed for these VOCs in another cohort of 18 CCA patients and 22 ***:Levels of six compounds were significantly different between CCA patients and controls,namely,acetone,isopropyl alcohol,dimethyl sulfide,1,4-pentadiene,allyl methyl sulfide,and N,*** and dimethyl sulfide were independently associated with CCA as demonstrated in the multivariate *** the cut-off value of 8.59107 arbitrary unit(AU),acetone had a sensitivity and specificity of 82.1%and 75.8%,respectively,with an area under the receiving operator curve(AUROC)of 0.85 for the CCA *** level was also significantly different between cases and controls in the validation *** the same cut-off value,the sensitivity,specificity,and AUROC was 59.1%,66.7%,and 0.85,***:Breath analysis may potentially be useful for CCA diagnosis.A cohort of patients with earlystage CCA in further studies is needed to confirm the ability of exhaled VOCs for the early detection of CCA.

关键词： Cholangiocarcinoma(CCA) Bile duct cancer Volatile organic compounds(VOCs) Biomarker Cancer screening Diagnostic model

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Investigations of Curing Chemistry and Hydrolytic Stability of Polyimide - on - Metal Interfaces

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MRS Online Proceedings Library 2020年第1期323卷 351-357页

作者： B.H. Cumpston P.V. Nagarkar G. Cornella D. Volfson F. Trusell K.F. Jensen S.D. Senturian] Departments of Chemical and Electrical Engineering and Materials Science and Engineering and the Electronics Packaging Program Massachusetts Institute of Technology Cambridge USA

Polyimide-on-metal interfaces relevant to electronics packaging applications have been studied by Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). Two polyimides with different backbone structures were considered: (i) biphenyltetracarboxylic dianhydride (BPDA) - p-phenylene diamine (PDA) and (ii) 4,4'-(hexafluroisopropylidene)-bis(phthalic anhydride) (6FDA) - 4,4'-bis(4-aminophenoxy) biphenyl (APBP). Thin polymer films (10-100 nm) were cured on Al, Cr and Cu surfaces at different temperatures to allow probing of chemical interactions by surface spectroscopies. Anhydride intermediates were detected on all three substrates for both polyimides. Carboxylate intermediates were detected in BPDA-PDA films on Cr and Cu and resulted in increased adhesion at these interfaces. XPS data revealed a nitrogen deficiency at the BPDA-PDA/Cr interface. A mechanism explaining the formation of this intermediate and the deficiency of nitrogen is proposed. Hydrolytic stability of the interface was investigated using ex situ total internal reflection FTIR spectroscopy and XPS. The results show that the fluorinated polyimide, 6FDA-APBP, is more stable than BPDA-PDA when treated at 85 °C and 85% relative humidity for 100 hours.

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Demonstration of a Bosonic Quantum Classifier with Data Reuploading

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Physical Review Letters 2023年第1期131卷 013601-013601页

作者： Takafumi Ono Wojciech Roga Kentaro Wakui Mikio Fujiwara Shigehito Miki Hirotaka Terai Masahiro Takeoka Program in Advanced Materials Science Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Takamatsu Kagawa 761-0396 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan Department of Electronics and Electrical Engineering Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama 223-8522 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology (NICT) Koganei Tokyo 184-8795 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi Kobe 651-2492 Japan

In a single qubit system, a universal quantum classifier can be realized using the data reuploading technique. In this study, we propose a new quantum classifier applying this technique to bosonic systems and successfully demonstrate it using a silicon-based photonic integrated circuit. We established a theory of quantum machine learning algorithm applicable to bosonic systems and implemented a programmable optical circuit combined with an interferometer. Learning and classification using part of the implemented optical quantum circuit with uncorrelated two photons resulted in a classification with a success probability of 94±0.8% in the proof of principle experiment. As this method can be applied to an arbitrary two-mode N-photon system, further development of optical quantum classifiers, such as extensions to quantum entangled and multiphoton states, is expected in the future.

关键词： Machine learning Optical quantum information processing Quantum algorithms

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Photon avalanche-driven multicolor emission: yttrium vanadate upconversion phosphors for optical thermometry, forensics, and healing light applications

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Chemical engineering Journal 2025年 516卷

作者： Pavitra, Eluri Antony, Lintymol Park, Jin Young Hwang, Seung Kyu Lee, Jeong-Hwan Chandra, Gogineni Rajesh Basaveswara Rao, M.V. Raju, Ganji Seeta Rama Han, Young-Kyu Huh, Yun Suk NanoBio High-Tech Materials Research Center Department of Biological Sciences and Bioengineering Inha University Incheon22212 Korea Republic of 3D Convergence Center Inha University Incheon22212 Korea Republic of Department of Energy and Materials Engineering Dongguk University-Seoul Seoul04620 Korea Republic of Department of Electrical Electronics and Software Engineering Pukyong National University Yongdang Campus Busan48547 Korea Republic of Department of Materials Science and Engineering Inha University Incheon22212 Korea Republic of Program in Semiconductor Convergence Inha University Incheon22212 Korea Republic of Department of Computer Science and Engineering Vignan's Lara Institute of Technology & Science Andhra Pradesh Guntur India Department of Chemistry Krishna University Andhra Pradesh Machillipatnam521001 India

The exploration of photon upconversion has led to the development of multifunctional lanthanide-based materials, particularly through the mechanism of photon avalanche, marking a transformative advancement in material science. In this study, yttrium vanadate upconversion nanocrystalline phosphors (UCNCPs) activated by Ho3+/Er3+/Tm3+/Yb3+ ions are reported. These UCNCPs demonstrate a remarkable ability in the photon avalanche, offering highly intense and tunable emissions across the visible spectrum at room temperature under low excitation power of 980 nm laser. The average number of photons involved in the UC process at threshold pump power, highlighting the intricate interplay of cross-relaxation and energy transfer loops in avalanche mechanism. Notably, these UCNCPs have shown exceptional temperature sensing capabilities, where non-thermally coupled levels of the Ho3+ and Tm3+ ions provide higher relative sensitivity and accuracy than thermally coupled levels of Er3+ ions. The versatility of these UCNCPs is further established by their application in solid-state lighting, where they can produce vibrant red, green, blue, and warm-white light, and in security, serving as multi-level anti-counterfeiting inks that respond to 980 nm laser illumination. These developments not only pave the way for more energy-efficient lighting solutions but also offer new avenues for enhancing the security of valuable items. The temperature sensing capabilities of these phosphors add another layer of functionality, making them ideal for high-tech applications ranging from medical diagnostics to environmental monitoring. © 2025 Elsevier B.V.

关键词： Phosphors

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Efficiency Analysis of Suspension Energy Harvesting besed on Supercapacitor for Electric Vehicles

Efficiency Analysis of Suspension Energy Harvesting besed on...

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International Electrical engineering Congress (iEECON)

作者： Kunagone Kiddee Taweesak Sukcharoensup Program in Electronics and Telecommunication Engineering Rajamangala University of Technology Thanyaburi Thanyaburi

ISBN: (数字)9781728130767

ISBN: (纸本)9781728130774

This experimental research proposes a supercapacitor-based regenerative shock absorber (RSA) capable of harvesting the vehicular suspension-vibration energy and converting it into electrical energy to extend the battery life and driving range of electric vehicles (EV). The proposed RSA composed of three main parts; the suspension vibration energy, conversion mechanism and energy storage modules. Simulations were carried out and an RSA prototype fabricated and bench-tested subject to sinusoidal vibration. The experimental total energy harvesting efficiency (β) of the supercapacitor-based RSA is in the range of 38.70% - 67.29%, with the average total efficiency of 53.15%. In addition, the RSA total efficiency is positively correlated to the vibrational frequency and amplitude. The proposed supercapacitor-based regenerative shock absorber is thus capable of harvesting the suspension vibration energy and efficiently converting it into electrical energy used for renewable energy applications to extend the EV driving range.

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Reconstructing suspended sediment concentrations in the Mekong River Basin via semi-supervised-based deep neural networks

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Science of the Total Environment 2024年 955卷 176758页

作者： Nguyen, Thi Thu Ha Vu, Duc Quang Doan, Ngoc Phu Chi, Huynh Thi Khanh Li, Peixin Binh, Doan Van An, Yimeng Dung, Pham Tuan Hoang, Tuan A. Son, Mai Thai Laboratory of Environmental Sciences and Climate Change Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Environment School of Technology Van Lang University Ho Chi Minh City Viet Nam Department of Computer Science and Information System Thai Nguyen University of Education Viet Nam School of Electronics Electrical Engineering and Computer Science Queen's University Belfast United Kingdom College of Economics and Management Nanjing University of Aeronautics and Astronautics China Master program in Water Technology Reuse and Management Faculty of Engineering Vietnamese-German University Binh Duong Province Ben Cat City Viet Nam

The Mekong River Basin (MRB) is crucial for the livelihoods of over 60 million people across six Southeast Asian countries. Understanding long-term sediment changes is crucial for management and contingency plans, but the sediment concentration data in the MRB are extremely sporadic, making analysis challenging. This study focuses on reconstructing long-term suspended sediment concentration (SSC) data using a novel semi-supervised machine learning (ML) model. The key idea of this approach is to exploit abundant available hydroclimate data to reduce training overfitting rather than solely relying on sediment concentration data, thus enhancing the accuracy of the employed ML models. Extensive experiments on daily hydroclimate and SSC data obtained from 1979 to 2019 at the three main stations (i.e., Chiang Saen, Nong Khai, and Mukdahan) are conducted to demonstrate the superior performance of the proposed method compared to the state-of-the-art supervised techniques (i.e., Random Forest, XGBoost, CatBoost, MLP, CNN, and LSTM), and surpasses existing semi-supervised methods (i.e., CoReg, ⊓ Model, ICT, and Mean Teacher). This approach is the first semi-supervised method to reconstruct sediment data in the field and has the potential for broader application in other river systems. © 2024 The Author(s)

关键词： Self-supervised learning

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A Conceptual Exploration of Generative AI-Induced Cognitive Dissonance and its Emergence in University-Level Academic Writing

arXiv

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arXiv 2025年

作者： Seran, Carl Errol Tan, Myles Joshua Toledo Karim, Hezerul Abdul AlDahoul, Nouar Biology Program College of Arts and Sciences University of St. La Salle Bacolod Philippines Department of Natural Sciences College of Arts and Sciences University of St. La Salle Bacolod Philippines Faculty of Education University of the Philippines Open University Los Baños Philippines Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health and Health Professions College of Medicine University of Florida GainesvilleFL United States Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Yo-Vivo Corporation Bacolod Philippines Faculty of Engineering Multimedia University Persiaran Multimedia Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Abu Dhabi United Arab Emirates

The integration of Generative Artificial Intelligence (GenAI) intouniversity-level academic writing presents both opportunities and challenges,particularly in relation to cognitive dissonance (CD). This work explores howGenAI serves as both a trigger and amplifier of CD, as students navigateethical concerns, academic integrity, and self-efficacy in their writingpractices. By synthesizing empirical evidence and theoretical insights, weintroduce a hypothetical construct of GenAI-induced CD, illustrating thepsychological tension between AI-driven efficiency and the principles oforiginality, effort, and intellectual ownership. We further discuss strategiesto mitigate this dissonance, including reflective pedagogy, AI literacyprograms, transparency in GenAI use, and discipline-specific task *** approaches reinforce critical engagement with AI, fostering a balancedperspective that integrates technological advancements while safeguarding humancreativity and learning. Our findings contribute to ongoing discussions on AIin education, self-regulated learning, and ethical AI use, offering aconceptual framework for institutions to develop guidelines that align AIadoption with academic values. © 2025, CC BY.

关键词： Generative adversarial networks

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Eye-Zheimer: A Deep Transfer Learning Approach of Dementia Detection and Classification from NeuroImaging 7

Eye-Zheimer: A Deep Transfer Learning Approach of Dementia D...

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7th IEEE International Conference on engineering Technologies and Applied Sciences, ICETAS 2020

作者： Alon, Helcy D. Ligayo, Michael Angelo D. Misola, Maribel A. Sandoval, Allan A. Fontanilla, Marites V. Technological Institute of the Philippines Graduate Program Manila Philippines Quezon City University Department of Electronics Engineering Quezon City Philippines FEU Institute of Technology Department of Computer Engineering Manila Philippines St. Paul University Department of Information Technology Quezon City Philippines

ISBN: (纸本)9780738105048

Dementia is a common term for memory loss, speech, problem-solving, and other cognitive skills that are serious enough to interfere with everyday life, and Alzheimer's is the leading cause of dementia. Alzheimer's disease is presumed to develop 20 years or more before symptoms occur, with degenerative changes that are unapparent to the person affected. The deep learning approach for early detection and Alzheimer's disease classification has recently gained significant attention. This study proposed disease detection trained by utilizing the YOLO v3 algorithm that aims to detect Alzheimer's disease based solely on Magnetic Resonance Imaging (MRI). Pascal VOC format and LabelImg tool are used for annotating the datasets, categorizing the image as non-demented and mild-demented. Model 4 was used in the system having 98.617% training accuracy, 98.8207% validation accuracy, and mAP of 96.17%. To test the accuracy of the used model, images of MRI scans are presented and it recorded 80% testing accuracy. © 2020 IEEE.

关键词： Object detection

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