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Overcoming the surface paradox: Buried perovskite quantum dots in wide-bandgap perovskite thin films

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arXiv 2025年

作者： Zhang, Hao Pasha, Altaf Metcalf, Isaac Zhou, Jianlin Staunstrup, Mathias Zhu, Yunxuan Liao, Shusen Ssennyimba, Ken Chen, Jia-Shiang Reddy, Surya Prakash Thébaud, Simon Hou, Jin Shuai, Xinting Mandani, Faiz Sidhik, Siraj Jones, Matthew R. Ma, Xuedan Balakrishna, R. Geetha Susarla, Sandhya Ginger, David S. Katan, Claudine Kanatzidis, Mercouri G. Bawendi, Moungi G. Natelson, Douglas Tamarat, Philippe Lounis, Brahim Even, Jacky Mohite, Aditya D. Department of Chemical and Biomolecular Engineering Rice University HoustonTX77005 United States Applied Physics Program Smalley‐Curl Institute Rice University HoustonTX77005 United States Centre for Nano and Material Sciences Jain University Jain Global Campus Kanakapura Karnataka Bangalore562112 India Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Université de Bordeaux LP2N Talence France Institut d’Optique CNRS LP2N Talence France Department of Physics and Astronomy Rice University HoustonTX77005 United States Center for Nanoscale Materials Argonne National Laboratory LemontIL60439 United States School for Engineering of Matter Transport and Energy Arizona State University TempeAZ85281 United States UMR 6082 CNRS INSA de Rennes Rennes35708 France Department of Chemistry Rice University HoustonTX77005 United States Department of Chemistry University of Washington Box 351700 SeattleWA98195-1700 United States UMR 6226 Rennes35000 France Department of Chemistry Northwestern University EvanstonIL United States Department of Chemistry Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States

Colloidal perovskite quantum dots (PQDs) are an exciting platform for on-demand quantum, and classical optoelectronic and photonic devices. However, their potential success is limited by the extreme sensitivity and low stability arising from their weak intrinsic lattice bond energy and complex surface chemistry. Here we report a novel platform of buried perovskite quantum dots (b-PQDs) in a three-dimensional perovskite thin-film, fabricated using one-step, flash annealing, which overcomes surface related instabilities in colloidal perovskite dots. The b-PQDs demonstrate ultrabright and stable single-dot emission, with resolution-limited linewidths below 130 μeV, photon-antibunching (g2(0)=0.1), no blinking, suppressed spectral diffusion, and high photon count rates of 104/s, consistent with unity quantum yield. The ultrasharp linewidth resolves exciton fine-structures (dark and triplet excitons) and their dynamics under a magnetic field. Additionally, b-PQDs can be electrically driven to emit single photons with 1 meV linewidth and photon-antibunching (g2(0)=0.4). These results pave the way for on-chip, low-cost single-photon sources for next generation quantum optical communication and sensing. © 2025, CC BY.

关键词： Photons

Achieving trust-based and privacy-preserving customer selection in ubiquitous computing

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arXiv 2019年

作者： Zhang, Chuan Zhu, Liehuang Xu, Chang Sharif, Kashif Liu, Ximeng Du, Xiaojiang Guizani, Mohsen Beijing Engineering Research Center of Massive Language Information Processing and Cloud Computing Application School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Information Systems Singapore Management University College of Mathematics and Computer Science Fuzhou University Department of Computer and Information Sciences Temple University Philadelphia United States Department of Electrical and Computer Engineering University of Idaho MoscowID United States

The recent proliferation of smart devices has given rise to ubiquitous computing, an emerging computing paradigm which allows anytime & anywhere computing possible. In such a ubiquitous computing environment, customers release different computing or sensing tasks, and people, also known as data processors, participate in these tasks and get paid for providing their idle computing and communication resources. Thus, how to select an appropriate and reliable customer while not disclosing processors' privacy has become an interesting problem. In this article, we present a trust-based and privacy-preserving customer selection scheme in ubiquitous computing, called TPCS, to enable potential processors select the customers with good reputation. The basic concept of TPCS is that each data processor holds a trust value, and the reputation score of the customer is calculated based on processors' trust values and feedbacks via a truth discovery process. To preserve processors' privacy, pseudonyms and Paillier cryptosystem are applied to conceal each processor's real identity. In addition, three authentication protocols are designed to ensure that only the valid data processors (i.e., the processors registering in the system, holding the truthful trust values, and joining the computing tasks) can pass the authentication. A comprehensive security analysis is conducted to prove that our proposed TPCS scheme is secure and can defend against several sophisticated attacks. Moreover, extensive simulations are conducted to demonstrate the correctness and effectiveness of the proposed scheme. Copyright © 2019, The Authors. All rights reserved.

关键词： Ubiquitous computing

Radiotherapy Communication Skills Training using Chatbot-Based Prototype (SCIMORT)

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Journal of Medical Imaging and Radiation sciences 2022年第4期53卷 S1-S1页

作者： Nor, A Nur, S Muhamad, K Rozilawati, A Noorazrul, Y Muhammad, F Nani, S Noraini, W Saiful, H Liyana, S Diagnostic Imaging and Radiotherapy Program School of Diagnostic and Applied Health Sciences Faculty of Health Sciences Universiti Kebangsaan Malaysia Jalan Raja Muda Abdul Aziz 50300 Kuala Lumpur Malaysia Department of Mathematical Sciences Faculty of Science and Technology Universiti Kebangsaan Malaysia UKM Bangi 43600 Selangor Darul Ehsan Malaysia Department of Information Systems Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

IntroductionEffective communication skills are integral to providing adequate patient care and are fundamental to its effectiveness. This is particularly important for radiotherapy students while interacting with patients. Students tend to feel disempowered and inadequate to communicate effectively due to repeated miscommunication between students and patients. For students seeking to develop their abilities, confidence, knowledge, and critical thinking, blended learning-based communication skills training may have been an alternative approach. In this study, a chatbot-based prototype model (SCIMORT module) was designed to effectively improve the communication skills of undergraduates in Diagnostic Imaging and Radiotherapy at Universiti Kebangsaan Malaysia. MethodsSCIMORT was developed in compliance with the Clinical Practice for Radiotherapy course's academic syllabus and learning objectives. SCIMORT was constructed using Blender with final exportation to Bot Libre. The research study is divided into two phases. The first phase focuses on developing the SCIMORT module, while the second phase includes properly evaluating the prototype created in the first phase via a survey questionnaire. ResultsThe virtual patient created in the first phase was displayed a visual cue (e.g. blinking, eye movement) and auditory cues (e.g. verbal response, intonation of voice). In the second phase, the expert validation of the questionnaire resulted in a high Content Validity Ratio of more than 0.83 percent and a Cronbach Alpha Coefficient of more than 70%. Both the control group's (users' acceptance = 3.919 ± 1.245; users' engagement = 3.526 ± 1.270) and Trial group's (users' acceptance = 3953 ± 1.114; users' engagement = 3.568 ± 1.142) users' acceptance and engagement with SCIMORT were neutral. ConclusionThe SCIMORT has proven to be an effective and acceptable tool for pre-clinical learning, but with limited levels of engagement. The SCIMORT module should be continually improved by

关键词： SCIMORT module communication skill virtual patients virtual clinical experience breast cancer simulation

Multiwavelength Constraints on the Origin of a Nearby Repeating Fast Radio Burst Source in a Globular Cluster

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arXiv 2023年

作者： Pearlman, Aaron B. Scholz, Paul Bethapudi, Suryarao Hessels, Jason W.T. Kaspi, Victoria M. Kirsten, Franz Nimmo, Kenzie Spitler, Laura G. Fonseca, Emmanuel Meyers, Bradley W. Stairs, Ingrid H. Tan, Chia Min Bhardwaj, Mohit Chatterjee, Shami Cook, Amanda M. Curtin, Alice P. Dong, Fengqiu Adam Eftekhari, Tarraneh Gaensler, B.M. Güver, Tolga Kaczmarek, Jane Leung, Calvin Masui, Kiyoshi W. Michilli, Daniele Prince, Thomas A. Sand, Ketan R. Shin, Kaitlyn Smith, Kendrick M. Tendulkar, Shriharsh P. Department of Physics McGill University MontréalQC Canada Trottier Space Institute McGill University MontréalQC Canada Division of Physics Mathematics and Astronomy California Institute of Technology PasadenaCA United States Dunlap Institute for Astronomy and Astrophysics University of Toronto TorontoON Canada Department of Physics and Astronomy York University TorontoON Canada Max-Planck-Institut für Radioastronomie Bonn Germany Anton Pannekoek Institute for Astronomy University of Amsterdam Amsterdam Netherlands ASTRON Netherlands Institute for Radio Astronomy Dwingeloo Netherlands Department of Space Earth and Environment Chalmers University of Technology Onsala Space Observatory Onsala Sweden MIT Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA United States Department of Physics and Astronomy West Virginia University MorgantownWV United States Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building MorgantownWV United States International Centre for Radio Astronomy Research Curtin University BentleyWA Australia Department of Physics and Astronomy University of British Columbia VancouverBC Canada McWilliams Center for Cosmology Department of Physics Carnegie Mellon University PittsburghPA United States Cornell Center for Astrophysics and Planetary Science Cornell University IthacaNY United States David A. Dunlap Department of Astronomy and Astrophysics University of Toronto TorontoON Canada Center for Interdisciplinary Exploration and Research in Astrophysics Department of Physics and Astronomy Northwestern University EvanstonIL United States Department of Astronomy and Astrophysics University of California Santa Cruz Santa CruzCA United States Department of Astronomy and Space Sciences Science Faculty Istanbul University Istanbul Turkey Istanbul University Observatory Research and Application Center Istanbul University Istanbul T

The precise origins of fast radio bursts (FRBs) remain unknown. Multiwavelength observations of nearby FRB sources can provide important insights into the enigmatic FRB phenomenon. Here, we present results from a sensitive, broadband X-ray and radio observational campaign of FRB 20200120E, the closest known extragalactic repeating FRB source (located 3.63 Mpc away in an ∼10-Gyr-old globular cluster). We place deep limits on the persistent and prompt X-ray emission from FRB 20200120E, which we use to constrain possible origins for the source. We compare our results with various classes of X-ray sources, transients, and FRB models. We find that FRB 20200120E is unlikely to be associated with ultraluminous X-ray bursts, magnetar-like giant flares, or an SGR 1935+2154-like intermediate flare. Although other types of bright magnetar-like intermediate flares and short X-ray bursts would have been detectable from FRB 20200120E during our observations, we cannot entirely rule them out as a class. We show that FRB 20200120E is unlikely to be powered by an ultraluminous X-ray source or a young extragalactic pulsar embedded in a Crab-like nebula. We also provide new constraints on the compatibility of FRB 20200120E with accretion-based FRB models involving X-ray binaries. These results highlight the power of multiwavelength observations of nearby FRBs for discriminating between FRB models. © 2023, CC BY.

关键词： X-ray astronomy

Initial ASEAN digital security and interoperability standard proposal

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AIP Conference Proceedings 2023年第1期2739卷

作者： Sangsuree Vasupongayya Gunawan Hutagalung Obrina Candra Chalee Vorakulpipat Doni Purnomo Parinda Wattanasri Eko Supriyanto Shukor Abd Razak Othman Ibrahim Anazida Zainal Sri Devi Ravana Hiep Cong Pham Tharith Sriv Daw Khin Myo Su Mora Hertanto Agus Winarno Prabaswari Raden Muhammad Taufik Yuniantoro Badrus Zaman Fatmawati Retna Apsari Yutika Amelia Effendi Norjihan Abdul Ghani Zarina Shukur Hamidah Ibrahim Nur Izura Udzir Marnel Peradilla Jude Michael Teves Nestor Michael Tiglao Cenon Alfonso Pg Emeroylariffion Abas Mueen Uddin Agustin Kusumayati Brian Sri Prahastuti Department of Computer Engineering Faculty of Engineering Prince of Songkla University Hatyai Songkhla 90110 THAILAND Directorate General of Post and Information Technology Ministry of Communication and Information Technology Jakarta INDONESIA Politeknik Siber dan Sandi Negara National Cyber & Crypto Agency (BSSN) Depok West Java INDONESIA Information Security Research Team at National Electronics and Computer Technology Center Bangkok THAILAND National Standardization Agency of Indonesia Jakarta INDONESIA Department of Disease Control Ministry of Public Health Mueang Nonthaburi Nonthaburi THAILAND School of Biomedical Engineering and Health Sciences Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Johor MALAYSIA IJN-UTM Cardiovascular Engineering Center Institute of Human Centered Engineering Universiti Teknologi Malaysia Johor Bahru Johor MALAYSIA School of Computing Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Johor MALAYSIA Faculty of Computer Science & Information Technology Universiti Malaya Kuala Lumpur MALAYSIA RMIT University Vietnam Ho Chi Minh City VIETNAM Royal University of Phnom Penh Phnom Penh CAMBODIA Yangon University of Economics Yangon MYANMAR Agency for the Assessment and Application of Technology (BPPT) Jakarta INDONESIA Faculty of Science and Technology Universitas Airlangga Surabaya East Java INDONESIA Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya East Java INDONESIA Centre for Cyber Security Universiti Kebangsaan Malaysia Bangi Selangor MALAYSIA Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang Selangor MALAYSIA Computer Technology Department College of Computer Studies De La Salle University Manila PHILIPPINES Software Technology Department College of Computer Studies De La Salle University Manila PHILIPPINES Electrical and Electronics Engineering Institute University of the Philippines Diliman Quezon City P

In this work, the result of the initial attempt to propose an Association of Southeast Asian Nations (ASEAN) digital security and interoperability standard to support the mobility among ASEAN countries is presented. Literature reviews on existing coronavirus disease 2019 (COVID-19) related digital technologies of six ASEAN member countries are conducted. Several concerns related to creating/implementing the ASEAN digital security and interoperability standard are discussed including the technology accessing concern, the data security and privacy concern, and the data interoperability and availability concern. The proposed solution toward creating an ASEAN digital security and interoperability standard is then presented. To evaluate the proposed solution, a survey has been conducted on representatives of nine ASEAN countries on four main issues including the security standards and requirements, the interoperability standard and requirements, the certifications, and the implementation challenges. According to the survey and the discussion, seven recommendations were proposed toward creating an ASEAN digital security and interoperability standard. First, each country collects and maintains the data of its own citizens and also provides a method to authenticate and access the data by authorized requests. Second, QR code standard or ASEAN QR code standard must be agreed upon so that it can be authenticated and verified by ASEAN countries. Third, health risk assessment must be agreed upon to be used. Forth, the security standard, the data, the data format and the exchange protocol must be agreed upon at the ASEAN policy level while adoption of international standards as an implementation guideline will ease of the process and neutralize different requirements from various countries. Fifth, any accountability of incidents must be agreed upon at the ASEAN policy level. Sixth, certification might be extended to certification of risk assessment for organizations, products or

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A learning strategy for contrast-agnostic MRI segmentation

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arXiv 2020年

作者： Billot, Benjamin Greve, Douglas N. van Leemput, Koen Fischl, Bruce Iglesias, Juan Eugenio Dalca, Adrian V. Center for Medical Image Computing University College London United Kingdom Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School United States Department of Health Technology Technical University of Denmark Denmark Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Program in Health Sciences and Technology Massachusetts Institute of Technology United States

We present a deep learning strategy that enables, for the first time, contrast-agnostic semantic segmentation of completely unpreprocessed brain MRI scans, without requiring additional training or fine-tuning for new modalities. Classical Bayesian methods address this segmentation problem with unsupervised intensity models, but require significant computational resources. In contrast, learning-based methods can be fast at test time, but are sensitive to the data available at training. Our proposed learning method, SynthSeg, leverages a set of training segmentations (no intensity images required) to generate synthetic scans of widely varying contrasts on the fly during training. These scans are produced using the generative model of the classical Bayesian segmentation framework, with randomly sampled parameters for appearance, deformation, noise, and bias field. Because each mini-batch has a different synthetic contrast, the final network is not biased towards any MRI contrast. We comprehensively evaluate our approach on four datasets comprising over 1,000 subjects and four MR contrasts. The results show that our approach successfully segments every contrast in the data, performing slightly better than classical Bayesian segmentation, and three orders of magnitude faster. Moreover, even within the same type of MRI contrast, our strategy generalizes significantly better across datasets, compared to training using real images. Finally, we find that synthesizing a broad range of contrasts, even if unrealistic, increases the generalization of the neural network. Our code and model are open source at https://***/BBillot/SynthSeg. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

Micro-supervised disturbance learning: A perspective of representation probability distribution

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arXiv 2020年

作者： Chu, Jielei Liu, Jing Wang, Hongjun Meng, Hua Gong, Zhiguo Li, Tianrui The School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China The School of Business Sichuan University Sichuan Chengdu610065 China The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China

The instability is shown in the existing methods of representation learning based on Euclidean distance under a broad set of conditions. Furthermore, the scarcity and high cost of labels prompt us to explore more expressive representation learning methods which depends on the labels as few as possible. To address these issues, the small-perturbation ideology is firstly introduced on the representation learning model based on the representation probability distribution. The positive small-perturbation information (SPI) which only depend on two labels of each cluster is used to stimulate the representation probability distribution and then two variant models are proposed to fine-tune the expected representation distribution of RBM, namely, Micro-supervised Disturbance GRBM (Micro-DGRBM) and Micro-supervised Disturbance RBM (Micro-DRBM) models. The Kullback-Leibler (KL) divergence of SPI is minimized in the same cluster to promote the representation probability distributions to become more similar in Contrastive Divergence (CD) learning. In contrast, the KL divergence of SPI is maximized in the different clusters to enforce the representation probability distributions to become more dissimilar in CD learning. To explore the representation learning capability under the continuous stimulation of the SPI, we present a deep Micro-supervised Disturbance Learning (Micro-DL) framework based on the Micro-DGRBM and Micro-DRBM models and compare it with a similar deep structure which has not any external stimulation. Experimental results demonstrate that the proposed deep Micro-DL architecture shows better performance in comparison to the baseline method, the most related shallow models and deep frameworks for clustering. © 2020, CC0.

关键词： Probability distributions

Diffusive topological transport in spatiotemporal thermal lattices

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arXiv 2021年

作者： Xu, Guoqiang Yang, Yihao Zhou, Xue Chen, Hongsheng Alù, Andrea Qiu, Cheng-Wei Department of Electrical and Computer Engineering National University of Singapore Kent Ridge117583 Singapore Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou China School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing400067 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining314400 China Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center of the City University of New York New YorkNY10016 United States

Topological insulating phases are usually found in periodic lattices stemming from collective resonant effects, and it may thus be expected that similar features may be prohibited in thermal diffusion, given its purely dissipative and largely incoherent nature. We report the diffusion-based topological states supported by spatiotemporally-modulated advections stacked over a fluidic surface, thereby imitating a periodic propagating potential in effective thermal lattices. We observe edge and bulk states within purely nontrivial and trivial lattices, respectively. At interfaces between these two types of lattices, the diffusive system exhibits interface states, manifesting inhomogeneous thermal properties on the fluidic surface. Our findings establish a framework for topological diffusion and thermal edge/bulk states, and it may empower a distinct mechanism for flexible manipulation of robust heat and mass transfer. © 2021, CC BY.

关键词： Interface states

Traffic Management using Logistic Regression with Fuzzy Logic

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Traffic Management using Logistic Regression with Fuzzy Logi...

2018 International Conference on Computational Intelligence and Data science, ICCIDS 2018

作者： Tomar, Anurag Singh Singh, Mridula Sharma, Girish Arya, K.V. School of Computer Science University of Petroleum and Energy Studies Dehradun India Department of Computer Science Engineering Uttarakhand Technical University Dehradun India Department of Electronics and Telecommunication College of Engineering Roorkee India Department of Master of Computer Application Bhai Parmanand Institute of Business Studies Shakarpur New Delhi India Department of Computer Science Engineering Institute of Engineering and Technology Lucknow India

Traffic congestion is one of the major problems in most of the cities across the globe and it leads to several other problems like pollution, time wastage, long traffic queues on roads and may cause accidents. Improvement of Road infrastructure is not always the feasible solution to resolve the problem. In real life scenario shorter distance route towards the destination attracts majority of people and at times it may aggravate traffic jam conditions. Therefore, a real time traffic information for intelligent decision making to decide the route preference is required. Moreover, a system which considers the factor of distance towards the destination along with real time traffic situation on that route will add to the solution to the congestion problem. certain parameters such as distance, weather condition, road location, day of week and time are considered to formulate the problem and to find solutions to these problems This paper outlines a combination of logistic regression with fuzzy logic such that a smart decision to preferred path can be taken. It is used to compute the probability of each possible path by considering the real time traffic information, distance and road condition and later is used to take decisions in an uncertain scenario. Proposed Method considers the number of parameters like distance, weather condition, road location, day of week and time. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Fuzzy logic