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Research in Equity and Sustained Participation in engineering, Computing, and Technology (RESPECT)

作者： Fernando Alegre Juana Moreno Trent Dawson Egbeyong E. Tanjong David H. Kirshner Gordon A. Cain Center for STEM Literacy Louisiana State University Baton Rouge LA U.S.A. Physics & Astronomy and Center for Computation & Technology Louisiana State University Baton Rouge LA U.S.A. School of Education Louisiana State University Baton Rouge LA U.S.A. Computer Science & Engineering Louisiana State University Baton Rouge LA U.S.A.

ISBN: (数字)9781728171722

ISBN: (纸本)9781728171739

We developed and piloted a new course titled computer science Teaching Methods (CSM) in the fall semester of 2019. This course was based on materials developed from a previous program that trained high school teachers in computational thinking and programming through LSU's Cain center. Pedagogical content knowledge informed the design of this course. Also, data gathered from teacher and instructor interaction at multiple sites during the summer STEM professional development program contributed to the courses' design. The CS Methods course targeted undergraduate computer science majors who were considering a career in teaching or who were interested in CS pedagogy. We encountered several challenges recruiting and retaining students and found that computer science students attracted to teaching careers do not fall into the stereotype of most computer science majors. Participation of women was higher than the average undergraduate CS courses. A disconnect appeared between the pedagogical practices promoted for teaching computing at the high school level and those being practiced at the college level. After learning about the 5E pedagogical model for teaching computing, students expressed interest in the potential of using more student-centered instruction, not only for high school instruction, but also for their own college courses. An area of disconnect also emerged in the programming formats, as all the students were comfortable with Java but all were unfamiliar with popular block-based programming platforms, such as Scratch. The transition from the CS curriculum taught in high schools to what follows in college needs to be smoother.

关键词： Programming profession computational modeling Training STEM Encoding Planning Interviews

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The ideal wavelength for daylight free-space quantum key distribution

APL Quantum

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APL Quantum 2024年第1期1卷

作者： Mostafa Abasifard Chanaprom Cholsuk Roberto G. Pousa Anand Kumar Ashkan Zand Thomas Riel Daniel K. L. Oi Tobias Vogl Abbe Center of Photonics Institute of Applied Physics Friedrich Schiller University Jena 07745 Jena Germany Department of Computer Engineering School of Computation Information and Technology Technical University of Munich 80333 Munich Germany Computational Nonlinear and Quantum Optics SUPA Department of Physics University of Strathclyde Glasgow G4 0NG United Kingdom University of Applied Sciences Wiener Neustadt 2700 Wiener Neustadt Austria Walton Institute for Information and Communication Systems Science South East Technological University Waterford X91 P20H Ireland

Quantum key distribution (QKD) has matured in recent years from laboratory proof-of-principle demonstrations to commercially available systems. One of the major bottlenecks is the limited communication distance in fiber networks due to the exponential signal damping. To bridge intercontinental distances, low Earth orbit satellites transmitting quantum signals over the atmosphere can be used. These free-space links, however, can only operate during the night, as the sunlight otherwise saturates the detectors used to measure the quantum states. For applying QKD in a global quantum internet with continuous availability and high data rates, operation during daylight is required. In this work, we model a satellite-to-ground quantum channel for different quantum light sources to identify the optimal wavelength for free-space QKD under ambient conditions. Daylight quantum communication is possible within the Fraunhofer lines or in the near-infrared spectrum, where the intrinsic background from the sun is comparably low. The highest annual secret key length considering the finite key effect is achievable at the Hα Fraunhofer line. More importantly, we provide the fundamental model that can be adapted, in general, to any other specific link scenario taking into account the required modifications. We also propose a true single-photon source based on a color center in hexagonal boron nitride coupled to a microresonator that can implement such a scheme. Our results can also be applied in roof-to-roof scenarios and are, therefore, relevant for near-future quantum networks.

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Direct Cation Exchange in Monolayer MoS2 via Recombination-Enhanced Migration

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Physical Review Letters 2019年第10期122卷 106101-106101页

作者： Shi-Ze Yang Weiwei Sun Yu-Yang Zhang (张余洋) Yongji Gong Mark P. Oxley Andrew R. Lupini Pulickel M. Ajayan Matthew F. Chisholm Sokrates T. Pantelides Wu Zhou (周武) Center for Nanophase Materials Science Oak Ridge National Laboratory Oak Ridge Tennessee 37831 USA Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science Vanderbilt University Nashville Tennessee 37235 USA School of Physical Sciences and CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing 100049 China School of Materials Science and Engineering Beihang University Beijing 100191 China Department of Materials Science and NanoEngineering Rice University Houston Texas 77005 USA

In addition to their unique optical and electronic properties, two-dimensional materials provide opportunities to directly observe atomic-scale defect dynamics. Here we use scanning transmission electron microscopy to observe substitutional Re impurities in monolayer MoS2 undergo direct exchanges with neighboring Mo atoms in the lattice. Density-functional-theory calculations find that the energy barrier for direct exchange, a process that has only been studied as a diffusion mechanism in bulk materials, is too large for either thermal activation or energy directly transferred from the electron beam. The presence of multiple sulfur vacancies next to the exchanged Re-Mo pair, as observed by electron microscopy, does not lower the energy barrier sufficiently to account for the observed atomic exchange. Instead, the calculations find that a Re dopant and surrounding sulfur vacancies introduce an ever-changing set of deep levels in the energy gap. We propose that these levels mediate an “explosive” recombination-enhanced migration via multiple electron-hole recombination events. As a proof of concept, we also show that Re-Mo direct exchange can be triggered via controlled creation of sulfur vacancies. The present experimental and theoretical findings lay a fundamental framework towards manipulating single substitutional dopants in two-dimensional materials.

关键词： Defects Diffusion Dopants Transition metal dichalcogenides Density functional theory Scanning transmission electron microscopy

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Critical Role of Removing Impurities in Nickel Oxide on High-Efficiency and Long-Term Stability of Inverted Perovskite Solar Cells

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Angewandte Chemie 2022年第18期134卷

作者： Dr. Shuangjie Wang Dr. Yuke Li Dr. Jiabao Yang Dr. Tong Wang Dr. Bowen Yang Dr. Qi Cao Dr. Xingyu Pu Prof. Lioz Etgar Dr. Jian Han Dr. Junsong Zhao Prof. Xuanhua Li Prof. Anders Hagfeldt State key Laboratory of Solidification Processing Center for Nano Energy Materials School of Materials Science and Engineering Northwestern Polytechnical University 710000 Shaanxi Xi'an China Department Department of Chemistry and Centre for Scientific Modeling and Computation Chinese University of Hong Kong 999077 Shatin Hong Kong P.R. China Department of Chemistry-Ångström Laboratory Uppsala University 75120 Uppsala Sweden Institute of Chemistry Casali Center for Applied Chemistry The Hebrew University of Jerusalem 91904 Jerusalem Israel Laboratory of Photomolecular Science Institute of Chemical Sciences and Engineering School of Basic Sciences Ecole Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland

The performance enhancement of inverted perovskite solar cells applying nickel oxide (NiO x ) as the hole transport layer (HTL) has been limited by impurity ions (such as nitrate ions). Herein, we have proposed a strategy to obtain high-quality NiO x nanoparticles via an ionic liquid-assisted synthesis method (NiO x -IL). Experimental and theoretical results illustrate that the cation of the ionic liquid can inhibit the adsorption of impurity ions on nickel hydroxide through a strong hydrogen bond and low adsorption energy, thereby obtaining NiO x -IL HTL with high conductivity and strong hole-extraction ability. Importantly, the removal of impurity ions can effectively suppress the redox reaction between the NiO x film and the perovskite film, thus slowing down the deterioration of device performance. Consequently, the modified inverted device shows a striking efficiency exceeding 22.62 %, and superior stability maintaining 92 % efficiency at a maximum power point tracking under one sun illumination for 1000 h.

关键词： Hole Transport Layer Interfacial Redox Reaction Nickel Oxide Perovskite Solar Cells

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AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline

arXiv

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arXiv 2019年

作者： Perrault, Andrew Fang, Fei Sinha, Arunesh Tambe, Milind The Center for Research on Computation and Society The John A. Paulson School of Engineering and Applied Science Harvard University United States The Institute for Software Research The School of Computer Science Carnegie Mellon University United States The School of Information Systems Singapore Management University Singapore Center for Research on Computation and Society Harvard University United States AI for Social Good Google Research India India

With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems. In pursuit of this goal of AI for Social Impact, we as AI researchers must go beyond improvements in computational methodology;it is important to step out in the field to demonstrate social impact. To this end, we focus on the problems of public safety and security, wildlife conservation, and public health in low-resource communities, and present research advances in multiagent systems to address one key cross-cutting challenge: how to effectively deploy our limited intervention resources in these problem domains. We present case studies from our deployments around the world as well as lessons learned that we hope are of use to researchers who are interested in AI for Social Impact. In pushing this research agenda, we believe AI can indeed play an important role in fighting social injustice and improving society. Copyright © 2019, The Authors. All rights reserved.

关键词： Multi agent systems

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Identifying laguerre-gaussian modes using convolutional neural network 18

Identifying laguerre-gaussian modes using convolutional neur...

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18th IEEE International Conference on Machine Learning and Applications, ICMLA 2019

作者： Sharifi, Safura Brown, Sofia Novikova, Irina Mikhailov, Eugeniy Veronis, Georgios Dowling, Jonathan Banadaki, Yaser Siddiqui, Elisha Cuzzo, Savannah Bhusal, Narayan Cohen, Lior Kalasky, Austin Prajapati, Nik Soto-Garcia, Rachel School of Electrical Engineering and Computer Science Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States Center for Computation and Technology Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States Hearne Institute for Theoretical Physics Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States School of Computer Science Southern University and A and M College Baton RougeLA70813 United States Department of Physics College of William and Marry WilliamburgVA8795 United States

ISBN: (纸本)9781728145495

An automated determination of Laguerre-Gaussian (LG) modes benefits cavity tuning and optical communication. In this paper, we employ machine learning techniques to automatically detect the lowest sixteen LG modes of a laser beam. Convolutional neural networks (CNN) are trained by collecting the experimental and simulated datasets of LG modes that relies only on the intensity images of their unique patterns. We demonstrate that the trained CNN model can detect LG modes with the maximum accuracy greater than 96% after 60 epochs. The study evaluates the CNN's ability to generalize to new data and adapt to experimental conditions. © 2019 IEEE.

关键词： Optical communication

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stClinic dissects clinically relevant niches by integrating spatial multi-slice multi-omics data in dynamic graphs

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Nature communications 2025年第1期16卷 5317页

作者： Chunman Zuo Junjie Xia Yupeng Xu Ying Xu Pingting Gao Jing Zhang Yan Wang Luonan Chen School of Life Sciences Sun Yat-sen University Guangzhou China. zuochm@***. Institute of Artificial Intelligence Donghua University Shanghai China. zuochm@***. Shanghai Collaborative Innovation Center of Endoscopy Fudan University Shanghai China. zuochm@***. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China. zuochm@***. Institute of Artificial Intelligence Donghua University Shanghai China. System Biology Lab for Metabolic Reprogramming Department of Human Genetics and Cell Biology School of Medicine Southern University of Science and Technology Shenzhen China. Shanghai Collaborative Innovation Center of Endoscopy Fudan University Shanghai China. Department of Pathology Changzheng Hospital Secondary Military Medical University Shanghai China. College of Computer Science and Technology Jilin University Changchun China. School of Mathematical Sciences Shanghai Jiao Tong University Shanghai China. lnchen@***. School of AI Shanghai Jiao Tong University Shanghai China. lnchen@***. Key Laboratory of Systems Biology Shanghai Institute of Biochemistry and Cell Biology Center for Excellence in Molecular Cell Science Chinese Academy of Sciences Shanghai China. lnchen@***. Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Chinese Academy of Sciences Hangzhou China. lnchen@***. West China Biomedical Big Data Center Med-X Center for Informatics West China Hospital Sichuan University Chengdu China. lnchen@***.

Spatial multi-slice multi-omics (SMSMO) integration has transformed our understanding of cellular niches, particularly in tumors. However, challenges like data scale and diversity, disease heterogeneity, and limited sample population size, impede the derivation of clinical insights. Here, we propose stClinic, a dynamic graph model that integrates SMSMO and phenotype data to uncover clinically relevant niches. stClinic aggregates information from evolving neighboring nodes with similar-profiles across slices, aided by a Mixture-of-Gaussians prior on latent features. Furthermore, stClinic directly links niches to clinical manifestations by characterizing each slice with attention-based geometric statistical measures, relative to the population. In cancer studies, stClinic uses survival time to assess niche malignancy, identifying aggressive niches enriched with tumor-associated macrophages, alongside favorable prognostic niches abundant in B and plasma cells. Additionally, stClinic identifies a niche abundant in SPP1+ MTRNR2L12+ myeloid cells and cancer-associated fibroblasts driving colorectal cancer cell adaptation and invasion in healthy liver tissue. These findings are supported by independent functional and clinical data. Notably, stClinic excels in label annotation through zero-shot learning and facilitates multi-omics integration by relying on other tools for latent feature initialization.

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Correction: Numerical and experimental evaluation of thermal enhancement using zinc nano-suspensions in a square flow passage

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Journal of Thermal Analysis and Calorimetry 2023年第2期148卷 571-571页

作者： Ahmed, Waqar Alawi, Omer A. Abdelrazek, Ali H. Yaseen, Zaher Mundher Falah, Mayadah W. Hussein, Omar A. Eltaweel, Mahmoud Homod, Raad Z. Sidik, Nor Azwadi Che Takasago I-Kohza Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Institute for Advanced Studies University of Malaya Kuala Lumpur Malaysia Department of Thermofluids School of Mechanical Engineering Universiti Teknologi Malaysia Skudai Malaysia Civil and Environmental Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Building and Construction Engineering Technology Department Building and Construction Techniques Engineering Department AL-Mustaqbal University College Hillah Iraq New Era And Development İn Civil Engineering Research Group Scientific Research Center Tikrit Al-Ayen University Thi-Qar Iraq School of Physics Engineering and Computer Science University of Hertfordshire Hatfield UK Department of Oil and Gas Engineering Basrah University for Oil and Gas Basrah Iraq

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Corrigendum to “Flat-gain and wide-band partial double-pass erbium co-doped fiber amplifier with hybrid gain medium” [Opt. Fiber Technol. 52 (2019) 101952–101956]

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Optical Fiber Technology 2023年 75卷

作者： Aya A. Almukhtar Alabbas A. Al-Azzawi B.A. Ahmad X.S. Cheng P.H. Reddy A. Dhar M.C. Paul H. Ahmad S.W. Harun Department of Electrical Engineering University of Malaya 50603 Kuala Lumpur Malaysia Department of Computer Techniques Engineering Al-Esraa University College Baghdad Iraq Department of Communication Engineering Al-Ma'moon University College Al-Washash 700921 Baghdad Iraq School of Engineering KDU University College 40150 Selangor Malaysia Fiber Optics and Photonics Division CSIR-Central Glass and Ceramic Research Institute Kolkata India Academy of Scientific and Innovative Research (AcSIR) Ghaziabad 201002 India Photonics Research Center University of Malaya 50603 Kuala Lumpur Malaysia Department of Physics Faculty of Science and Technology Airlangga University Surabaya Indonesia

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Beware of "Explanations" of AI

arXiv

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arXiv 2025年

作者： Martens, David Shmueli, Galit Evgeniou, Theodoros Bauer, Kevin Janiesch, Christian Feuerriegel, Stefan Gabel, Sebastian Goethals, Sofie Greene, Travis Klein, Nadja Kraus, Mathias Kühl, Niklas Perlich, Claudia Verbeke, Wouter Zharova, Alona Zschech, Patrick Provost, Foster University of Antwerp Department of Engineering Management Antwerp2000 Belgium National Tsing Hua University Institute of Service Science Hsinchu30013 Taiwan INSEAD Technology and Business Fontainebleau77300 France Goethe University Frankfurt Department of Information Systems Frankfurt60629 Germany TU Dortmund University Department of Computer Science Dortmund44227 Germany LMU Munich Munich Center for Machine Learning Munich80539 Germany Erasmus University Rotterdam School of Management Rotterdam3062 Netherlands Copenhagen Business School Department of Digitalization Copenhagen2000 Denmark Karlsruhe Institute of Technology Scientific Computing Center Karlsruhe76131 Germany University of Regensburg Faculty of Informatics and Data Science Regensburg93053 Germany University of Bayreuth Faculty of Law Business and Economics Bayreuth95440 Germany New York University Department of Technology Operations and Statistics New YorkNY10012 United States KU Leuven Faculty of Economics and Business Leuven3000 Belgium Humboldt-Universität zu Berlin School of Business and Economics Berlin10099 Germany Leipzig University Faculty of Economics and Management Science Leipzig04109 Germany

Understanding the decisions made and actions taken by increasingly complex AI system remains a key challenge. This has led to an expanding field of research in explainable artificial intelligence (XAI), highlighting the potential of explanations to enhance trust, support adoption, and meet regulatory standards. However, the question of what constitutes a "good" explanation is dependent on the goals, stakeholders, and context. At a high level, psychological insights such as the concept of mental model alignment can offer guidance, but success in practice is challenging due to social and technical factors. As a result of this ill-defined nature of the problem, explanations can be of poor quality (e.g. unfaithful, irrelevant, or incoherent), potentially leading to substantial risks. Instead of fostering trust and safety, poorly designed explanations can actually cause harm, including wrong decisions, privacy violations, manipulation, and even reduced AI adoption. Therefore, we caution stakeholders to beware of explanations of AI: while they can be vital, they are not automatically a remedy for transparency or responsible AI adoption, and their misuse or limitations can exacerbate harm. Attention to these caveats can help guide future research to improve the quality and impact of AI explanations. © 2025, CC BY.

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