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Low-Velocity-Favored Transition Radiation

Physical Review Letters 2023年第11期131卷 113002-113002页

作者： Jialin Chen Ruoxi Chen Fuyang Tay Zheng Gong Hao Hu Yi Yang Xinyan Zhang Chan Wang Ido Kaminer Hongsheng Chen Baile Zhang Xiao Lin Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science & Electronic Engineering Zhejiang University Hangzhou 310027 China International Joint Innovation Center the Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa 32000 Israel Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Department of Physics University of Hong Kong Hong Kong 999077 China Key Lab of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Zhejiang University Jinhua 321099 China Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing 312000 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore 637371 Singapore

When a charged particle penetrates through an optical interface, photon emissions emerge—a phenomenon known as transition radiation. Being paramount to fundamental physics, transition radiation has enabled many applications from high-energy particle identification to novel light sources. A rule of thumb in transition radiation is that the radiation intensity generally decreases with the decrease of particle velocity v; as a result, low-energy particles are not favored in practice. Here, we find that there exist situations where transition radiation from particles with extremely low velocities (e.g., v/c<10−3) exhibits comparable intensity as that from high-energy particles (e.g., v/c=0.999), where c is the light speed in free space. The comparable radiation intensity implies an extremely high photon extraction efficiency from low-energy particles, up to 8 orders of magnitude larger than that from high-energy particles. This exotic phenomenon of low-velocity-favored transition radiation originates from the interference of the excited Ferrell-Berreman modes in an ultrathin epsilon-near-zero slab. Our findings may provide a promising route toward the design of integrated light sources based on low-energy electrons and specialized detectors for beyond-standard-model particles.

关键词： Atom or molecule scattering from surfaces Atomic & molecular collisions Cherenkov radiation Crystal optics Electron beams & optics Light-matter interaction Optical sources & detectors Optical transient phenomena Plasmonics

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Mine-to-client planning with Markov Decision Process

Mine-to-client planning with Markov Decision Process

引用

European Control Conference (ECC)

作者： João Marcelo Leal Gomes Leite Edilson F. Arruda Laura Bahiense Lino G. Marujo Industrial Engineering Program Alberto Luiz Coimbra Institute – Graduate School and Research in Engineering Federal University of Rio de Janeiro Rio de Janeiro Brazil Systems Engineer and Computer Science Program Alberto Luiz Coimbra Institute – Graduate School and Research in Engineering Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (数字)9783907144022

ISBN: (纸本)9781728188133

This works presents an innovative application of Markov Decision Process (MDP) to a medium-term mining logistics planning problem considering the mine-to-client supply chain. We implemented three distinct algorithms based on state-of-the-art approaches to solve large-scale problems, and compared their results. Furthermore, we combined all three variants in a single novel algorithm that attained fast convergence and may be an alternative to circumvent the curse of dimensionality underlying large scale problems.

关键词： Supply chains Planning Uncertainty Markov processes Computational modeling

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Understanding automated and human-based technical debt identification approaches-a two-phase study

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Journal of the Brazilian computer Society 2019年第1期25卷 1页

作者： Spínola, Rodrigo O. Zazworka, Nico Vetro, Antonio Shull, Forrest Seaman, Carolyn Graduate Program in Systems and Computer Salvador University State University of Bahia SalvadorBahia Brazil Elsevier Frankfurt Germany Nexa Center for Internet & Society DAUIN Politecnico di Torino Torino Italy Carnegie Mellon University Software Engineering Institute ArlingtonVA United States Department of Information Systems University of Maryland Baltimore County BaltimoreMD United States

Context: The technical debt (TD) concept inspires the development of useful methods and tools that support TD identification and management. However, there is a lack of evidence on how different TD identification tools could be complementary and, also, how human-based identification compares with them. Objective: To understand how to effectively elicit TD from humans, to investigate several types of tools for TD identification, and to understand the developers’ point of view about TD indicators and items reported by tools. Method: We asked developers to identify TD items from a real software project. We also collected the output of three tools to automatically identify TD and compared the results in terms of their locations in the source code. Then, we collected developers’ opinions on the identification process through a focus group. Results: Aggregation seems to be an appropriate way to combine TD reported by developers. The tools used cannot help in identifying many important TD types, so involving humans is necessary. Developers reported that the tools would help them to identify TD faster or more accurately and that project priorities and current development activities are important to be considered together, along with the values of principal and interest, when deciding to pay off a debt. Conclusion: This work contributes to the TD landscape, which depicts an understanding between different TD types and how they are best discovered. © 2019, The Author(s).

关键词： Software engineering

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Big Data Governance for Building A Smart Cities 10

Big Data Governance for Building A Smart Cities

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10th International Conference on ICT for Smart Society, ICISS 2019

作者： Zulkarnain, Novan Kosala, Raymond Ranti, Benny Supangkat, Suhono Harso Bina Nusantara University Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Universitas Indonesia Computer Science Department Depok16424 Indonesia Institute of Technology Bandung School of Electrical and Informatics Engineering Bandung40132 Indonesia

ISBN: (纸本)9781728148809

There have been many studies conducted related to Smart City, IT Governance and Big Data. In this study aims to find out how the relationship between the three and how to form a framework to explain it. The methodology used is qualitative by looking for some literature on smart city framework, IT Governance framework, and a Big Data framework. From these results, an overall picture of the relationship between the three is concluded, where Big Data has a role in IT Governance. and also the relationship of IT Governance to the realization of Smart City. And the final results of this study produce a framework to explain the relationship between Smart City, IT Governance and Big Data. © 2019 IEEE.

关键词： Big data

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Technical debt and agile software development practices and processes: An industry practitioner survey

arXiv

引用

arXiv 2021年

作者： Holvitie, Johannes Licorish, Sherlock A. Spínola, Rodrigo O. Hyrynsalmi, Sami MacDonell, Stephen G. Mendes, Thiago S. Buchan, Jim Leppänen, Ville Turku Centre for Computer Science Software Development Laboratory Turku Finland University of Turku Department of Information Technology Turku Finland University of Otago Department of Information Science Otago Dunedin New Zealand Salvador University Graduate Program in Systems and Computer Bahia Salvador Brazil Federal University of Bahia Fraunhofer Project Center for Software and System Engineering Salvador Brazil Tampere University of Technology Pori Campus Pori Finland Federal Institute of Bahia Information Technology Department Bahia Santo Amaro Brazil Auckland University of Technology School of Engineering Computer and Mathematical Sciences Auckland New Zealand

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how technical debt specifically manifests in and affects software processes, and how the software development techniques employed accommodate or mitigate the presence of this debt. Objectives: We sought to draw on practitioner insights and experiences in order to classify the effects of agile method use on technical debt management, given the popularity and perceived success of agile methods. We explore the breadth of practitioners' knowledge about technical debt;how technical debt is manifested across the software process;and the perceived effects of common agile software development practices and processes on technical debt. In doing so, we address a research gap in technical debt knowledge and provide novel and actionable managerial recommendations. Method: We designed, tested and executed a multi-national survey questionnaire to address our objectives, receiving 184 responses from practitioners in Brazil, Finland, and New Zealand. Results: Our findings indicate that: 1) Practitioners are aware of technical debt, although, there was under utilization of the concept, 2) Technical debt commonly resides in legacy systems, however, concrete instances of technical debt are hard to conceptualize which makes it problematic to manage, 3) Queried agile practices and processes help to reduce technical debt;in particular, techniques that verify and maintain the structure and clarity of implemented artifacts (e.g., Coding standards and Refactoring) positively affect technical debt management. Conclusions: The fact that technical debt instances tend to have characteristics in common means that a systematic approach to its management is feasible. However, notwithstanding the positive effects of some agile practices on technical debt management, comp

关键词： Legacy systems

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Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

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Informatics in Medicine Unlocked 2023年 42卷

作者： Azim, Sayed Mehedi Sabab, Noor Hossain Nuri Noshadi, Iman Alinejad-Rokny, Hamid Sharma, Alok Shatabda, Swakkhar Dehzangi, Iman Center for Computational and Integrative Biology Rutgers University Camden 08102 NJ United States Department of Computer Science and Engineering United International University Plot 2 United City Madani Avenue BaddaDhaka 1212 Bangladesh Department of Bioengineering University of California Riverside 92507 CA United States BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering The University of New South Wales (UNSW Sydney) Sydney NSW 2052 Australia UNSW Data Science Hub UNSW Sydney Sydney NSW 2052 Australia Health Data Analytics Program AI-enabled Processes Research Centre Macquarie University Sydney 2109 Australia Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230-0045 Japan Department of Computer Science Rutgers University Camden 08102 NJ United States

The use of therapeutic peptides for the treatment of cancer has received tremendous attention in recent years. Anticancer peptides (ACPs) are considered new anticancer drugs which have several advantages over chemistry-based drugs including high specificity, strong tumor penetration capacity, and low toxicity level for normal cells. Due to the rise of experimentally verified bioactive peptides, several in silico approaches became imperative for the investigation of the characteristics of ACPs. In this paper, we proposed a new machine learning tool named iACP-RF that uses a combination of several sequence-based features and an ensemble of three heterogeneously trained Random Forest classifiers to accurately predict anticancer peptides. Experimental results show that our proposed model achieves an accuracy of 75.9% which outperforms other state-of-the-art methods by a significant margin. We also achieve 0.52, 75.6%, and 76.2% in terms of Matthews Correlation Coefficient (MCC), Sensitivity, and Specificity, respectively. iACP-RF as a standalone tool and its source code are publicly available at: https://***/MLBC-lab/iACP-RF. © 2023 The Authors

关键词： Anticancer peptides Ensemble learning Feature extraction Heterogeneous classifiers Machine learning Random Forest

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Enriching and Characterizing T-Cell Repertoires from 3' Barcoded Single-Cell Whole Transcriptome Amplification Products

arXiv

引用

arXiv 2022年

作者： Jivanjee, Tasneem Ibrahim, Samira Nyquist, Sarah K. James Gatter, G. Bromley, Joshua D. Jaiswal, Swati Berger, Bonnie Behar, Samuel M. Christopher Love, J. Shalek, Alex K. Institute for Medical Engineering & Science Department of Chemistry Massachusetts Institute of Technology CambridgeMA United States Koch Institute for Integrative Cancer Research Massachusetts Institute of Technology CambridgeMA United States Ragon Institute of MGH MIT and Harvard CambridgeMA United States Broad Institute of MIT and Harvard CambridgeMA United States Massachusetts Institute of Technology CambridgeMA United States Program in Computational and Systems Biology Massachusetts Institute of Technology CambridgeMA United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA United States Microbiology Graduate Program Massachusetts Institute of Technology CambridgeMA02139 United States Department of Microbiology and Physiological Systems University of Massachusetts Medical School WorcesterMA United States Department of Mathematics Massachusetts Institute of Technology CambridgeMA United States Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA United States

Antigen-specific T cells play an essential role in immunoregulation and many diseases such as cancer. Characterizing the T cell receptor (TCR) sequences that encode T cell specificity is critical for elucidating the antigenic determinants of immunological diseases and designing therapeutic remedies. However, methods of obtaining single-cell TCR sequencing data are labor and cost intensive, typically requiring both cell sorting and full length single-cell RNA-sequencing (scRNA-seq). New high-throughput 3' cell-barcoding scRNA-seq methods can simplify and scale this process;however, they do not routinely capture TCR sequences during library preparation and sequencing. While 5' cell-barcoding scRNA-seq methods can be used to examine TCR repertoire at single-cell resolution, doing so requires specialized reagents which cannot be applied to samples previously processed using 3' cell-barcoding methods. Here, we outline a method for sequencing TCRα and TCRβ transcripts from samples already processed using 3' cell-barcoding scRNA-seq platforms, ensuring TCR recovery at a single-cell resolution. In short, a fraction of the 3' barcoded whole transcriptome amplification (WTA) product typically used to generate a massively parallel 3' scRNA-seq library is enriched for TCR transcripts using biotinylated probes, and further amplified using the same universal primer sequence from WTA. Primer extension using TCR V-region primers and targeted PCR amplification using a second universal primer results in a 3' barcoded single-cell CDR3-enriched library that can be sequenced with custom sequencing primers. Coupled with 3' scRNA-seq of the same WTA, this method enables simultaneous analysis of single-cell transcriptomes and TCR sequences which can help interpret inherent heterogeneity among antigen-specific T cells and salient disease biology. The method presented here can also be adapted readily to enrich and sequence other transcripts of interest from both 3' and 5' barcoded scRNA-seq

关键词： RNA

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Classification of the Structural Integrity by the General Vibration Method

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Procedia computer Science 2019年 157卷 382-387页

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information Systems Information Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Traditionally, for the purpose of classifying the integrity of an engineering structure, one may use the information of the natural frequencies or mode shapes or some other measures derived from the two. In this research, we propose a classification method on the basis of the general vibration model. The general vibration model is essentially a set of differential equations describing the dynamics of the structure under consideration. For the purpose of damage detection, a deviation of the general vibration model from the dynamic equilibrium point marks the occurrence of the damage. To demonstrate the effectiveness of the method, we study two simplest dynamical systems consisting of one- and two-concentrated masses subjected to a prescribed dynamic load. The structural damages are introduced artificially by reducing the stiffness of spring in the structures. We find that the general vibration model is more sensitive to damages than the traditional methods.

关键词： General Vibration Model Structural Integrity Structural Health Monitoring Power Spectral Density Damage Index

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A Study of the Sensitivity of the Fuel Consumption to Driving Strategy by Micro Simulation

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Procedia computer Science 2019年 157卷 375-381页

Global warming due to excessive emission greenhouse gases is a significant issue faced by humanity, and collectively, cars and trucks contribute about 20% to the entire global-warming gases. For a reason, recently, many attempts have been endured to reduce the emission and to increase fuel efficiency, including vehicle platooning, better driving strategy, and increasing engine efficiency. This study intends to provide a more detail assessment regarding the effects of the driving strategy to fuel consumption. For the purpose, the vehicle dynamics are quantified by employing the car-following model based on the optimal velocity model. The fuel consumption is estimated from the regression model of Ahn 18 . The result suggests that the braking distance strongly affects fuel consumption.

关键词： Optimal Velocity Model Micro Simulation Car-Following Model Fuel Efficiency

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Direct Comparison of RT-ddPCR and Targeted Amplicon Sequencing for SARS-CoV-2 Mutation Monitoring in Wastewater

SSRN

引用

SSRN 2022年

作者： Lou, Esther G. Sapoval, Nicolae McCall, Camille Bauhs, Lauren Carlson-Stadler, Russell Kalvapalle, Prashant Lai, Yanlai Palmer, Kyle Penn, Ryker Rich, Whitney Wolken, Madeline Ensor, Katherine B. Hopkins, Loren Treangen, Todd J. Stadler, Lauren B. Department of Civil and Environmental Engineering Rice University 6100 Main Street MS 519 HoustonTX77005 United States Department of Computer Science Rice University 6100 Main Street HoustonTX77005 United States Systems Synthetic and Physical Biology Graduate Program Rice University 6100 Main Street HoustonTX77005 United States Houston Health Department 8000 N. Stadium Dr. HoustonTX77054 United States Department of Statistics Rice University 6100 Main Street MS 138 HoustonTX77005 United States

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3;hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing. © 2022, The Authors. All rights reserved.

关键词： SARS

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