IOP SciNotes最新文献_第4页

An analytical approach for frequency modulated thermal wave imaging for testing and evaluation of glass fiber reinforced polymers 一种用于玻璃纤维增强聚合物测试和评价的调频热波成像分析方法

IOP SciNotes Pub Date : 2021-02-12 DOI: 10.1088/2633-1357/abe5b6

Anju Rani, Ravibabu Mulaveesala, V. Kher

引用次数: 2

Learning human insight by cooperative AI: Shannon-Neumann measure 通过合作人工智能学习人类的洞察力:香农-诺伊曼测量

IOP SciNotes Pub Date : 2021-02-01 DOI: 10.1088/2633-1357/abec9e

Edouard Siregar

{"title":"Learning human insight by cooperative AI: Shannon-Neumann measure","authors":"Edouard Siregar","doi":"10.1088/2633-1357/abec9e","DOIUrl":"https://doi.org/10.1088/2633-1357/abec9e","url":null,"abstract":"A conceptually sound solution to a complex real-world challenge, is built on a solid foundation of key insights, gained by posing ‘good’ questions, at the ‘right’ times/places. If the foundation is weak, due to insufficient human insight, the resulting, conceptually flawed solution, can be very costly or impossible to correct downstream. The response to the global 2020 pandemic, by countries using just-in-time supply/production chains and fragmented health-care systems, are striking examples. Here, Artificial intelligence (AI) tools to help human insight, are of significant value. We present a computational measure of insight gains, which a cooperative AI agent can compute, by having a specific internal framework, and by observing how a human behaves. This measure enables a cooperative AI to maximally boost human insight, during an iterated questioning process—a solid foundation for solving complex open-ended challenges. It is an AI-Human insight bridge, built on Shannon entropy and von Neumann utility. Our next paper will addresses how this measure and its associated strategy, reduce a hard cooperative inverse reinforcement learning game, to simple Q-Learning, proven to converge to a near-optimal policy.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45390621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Temperature variance portends and indicates the extent of abrupt climate shifts 温度变化预示并表明气候突变的程度

IOP SciNotes Pub Date : 2021-01-29 DOI: 10.1088/2633-1357/abda14

C. Ramadhin, C. Yi, G. Hendrey

引用次数: 1

Performance of the Scheduled Relaxation Jacobi method in a geometric multilevel setting. I. Linear case 调度松弛Jacobi方法在几何多级设置中的性能。I.线性情况

IOP SciNotes Pub Date : 2021-01-19 DOI: 10.1088/2633-1357/abd8e3

E. Bentivegna

引用次数: 0

A novel dataset for analysing sub-national socioeconomic developments in the Indian coal industry 用于分析印度煤炭行业次国家社会经济发展的新数据集

IOP SciNotes Pub Date : 2021-01-14 DOI: 10.1088/2633-1357/abdbbb

Sandeep Pai, Hisham Zerriffi

{"title":"A novel dataset for analysing sub-national socioeconomic developments in the Indian coal industry","authors":"Sandeep Pai, Hisham Zerriffi","doi":"10.1088/2633-1357/abdbbb","DOIUrl":"https://doi.org/10.1088/2633-1357/abdbbb","url":null,"abstract":"Coal use needs to rapidly decline in the global energy mix in the next few decades in order to meet the Paris climate goals of keeping global warming well below 2-degrees Celsius. In emerging economies such as India (the second largest producer and consumer of coal) this would entail reducing long-term coal dependency. Prior work has focused on a coal transition in India from a techno-economic point of view, yet little attention has been given to the socio-economic dimensions of this transition. This is in part due to lack of availability of datasets required for such analysis. The first step in understanding the socio-economic dimensions of a coal transition in India is to understand the scale of current socio-economic dependency on coal at the sub-national level. We contribute to this literature by creating a novel dataset comprised of all 459 operational coal mines in India, using multiple Right to Information Act applications (India’s Freedom of Information Act) and then combining this dataset with coal company wise employment factors to estimate direct job numbers at the district level (a sub-administrative unit). We find that coal is produced in 51 districts in 13 states in India with large variations in employment numbers among these districts. While Korba district in Chhattisgarh state is the highest coal producing district, Dhanbad district in Jharkhand state is home to the highest number of coal mining workers. This is the first attempt at understanding the socio-economic dependency on coal at a district level and future work could focus on quantifying other district level socio-economic indicators such as coal related revenues. The new dataset and the results of this paper will be useful for scholars conducting future work on coal transitions and related topics.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42876701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Explorations on the electronic structure and spectroscopic IR assignments of 5-methyl-2-(2-oxopropyl)-pyrazolo[5,1-b]quinazolin-9(3H)-one molecule 5-甲基-2-（2-氧丙基）-吡唑并[5,1-b]喹唑啉-9（3H）-酮分子的电子结构和红外光谱研究

IOP SciNotes Pub Date : 2021-01-06 DOI: 10.1088/2633-1357/abe4b8

Dilip Kumar, V. Kushwaha, U. Yadava

引用次数: 0

Genome description of Nostoc ellipsosporum strain NOK (Nostocales, Cyanobacteria) isolated from an arsenic contaminated paddy field of the Bengal Delta Plains 孟加拉三角洲平原砷污染稻田中分离的褐藻菌(Nostoc ellipsosporum)菌株NOK的基因组描述

IOP SciNotes Pub Date : 2021-01-01 DOI: 10.1088/2633-1357/ac202f

Anwesha Ghosh, P. Bhadury

{"title":"Genome description of Nostoc ellipsosporum strain NOK (Nostocales, Cyanobacteria) isolated from an arsenic contaminated paddy field of the Bengal Delta Plains","authors":"Anwesha Ghosh, P. Bhadury","doi":"10.1088/2633-1357/ac202f","DOIUrl":"https://doi.org/10.1088/2633-1357/ac202f","url":null,"abstract":"A diazotrophic cyanobacterium, Nostoc ellipsosporum strain NOK, was isolated from an arsenic contaminated paddy field of the Bengal Delta Plains (BDP). Located across India and Bangladesh, BDP, is one of the worst arsenic (As)-affected regions of the world. Previous studies have shown this isolate to be tolerant to high concentration of arsenic (≦400 μM). The genome of this isolate was sequenced to identify the genes involved in various metabolic pathways including arsenic resistance and biofilm formation. Whole genome analyses showed Nostoc ellipsosporum strain NOK to be closely related to N. punctiforme strain PCC73102. The genome is about 10.9 Mbp which assembled into 694 contigs. Genome annotation identified 10120 genes out of which 10000 were CDSs. There are a total of 9927 protein coding genes in addition to 120 RNA coding genes. The genome codes three 5S rRNA, four 16S rRNA and three 23S rRNA genes along with 103 tRNAs, 7 ncRNAs and 73 pseudo-genes. The G + C% of the genome is 54.28. The genome codes for crucial genes involved in biofilm formation in response to stress conditions including arsenic stress. The arsBHC operon is present within the genome which makes this tolerant to high concentration of arsenic which might lead to biofilm formation. A number of ABC transporters including cysUW and sbp (sulfate/thiosulfate), nrtABC (nitrate/nitrite/cyanate), cmpABCD (bicarbonate), ssuABC (alkane sulfonate), modABCF (molybdate; 2 copies), afuAC (iron), pstA (phosphate; 2 copies), pstBC, pstS (4 copies), cbiOQ (cobalt and nickel) and opuBC, opuBB and opuBA (osmoprotectants) were identified.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61193904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two point-source interference: a study of the formation of concentric circular fringes 两个点源干涉:同心圆条纹形成的研究

IOP SciNotes Pub Date : 2021-01-01 DOI: 10.1088/2633-1357/ac13bb

J. I. Thomas

引用次数: 1

An AI-assisted chatbot for radiation safety education in radiotherapy 一种人工智能辅助放射安全教育聊天机器人

IOP SciNotes Pub Date : 2021-01-01 DOI: 10.1088/2633-1357/ac1f88

David Kovacek, J. Chow

{"title":"An AI-assisted chatbot for radiation safety education in radiotherapy","authors":"David Kovacek, J. Chow","doi":"10.1088/2633-1357/ac1f88","DOIUrl":"https://doi.org/10.1088/2633-1357/ac1f88","url":null,"abstract":"Purpose. We created a virtual assistant chatbot that will serve as a tool for radiation safety training for clinical staff, including radiation oncologist, radiotherapist and medical physicist, in cancer treatment. The Bot can also be used to test their knowledge on radiation safety. Methods. The Bot was constructed using IBM’s Watson Assistant functionalities on the IBM cloud. A layered structure approach was used in the workflow of the Bot to interact with the user. Through answering various questions concerning radiation safety in radiotherapy, the users can learn the essential information to gain knowledge, when working in a cancer centre/hospital. Results. The user interface of the Bot was a front-end window operating on Internet, which could easily be accessed by any Internet-of-things such as smartphone, tablet or laptop. The Bot could communicate with the user for radiation safety Q&A. If the Bot could not identify what the user needed, the Bot would provide a list of options as a guidance. Using the natural language processing in communication, knowledge transfer from the Bot to user could be carried out. Conclusion. It is concluded that the radiation safety chatbot worked as intended, utilizing all the tools provided by the IBM Watson Assistant. The Bot could provide radiation safety information to the radiation staff effectively, and be used in staff training in radiotherapy.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":"244 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61193753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Effects of fuel cost and driving behaviors on operational costs of gasoline and electric vehicles in the US 燃料成本和驾驶行为对美国汽油和电动汽车运营成本的影响

IOP SciNotes Pub Date : 2021-01-01 DOI: 10.1088/2633-1357/ac10bd

Isaac Schmidt, E. Grubert

{"title":"Effects of fuel cost and driving behaviors on operational costs of gasoline and electric vehicles in the US","authors":"Isaac Schmidt, E. Grubert","doi":"10.1088/2633-1357/ac10bd","DOIUrl":"https://doi.org/10.1088/2633-1357/ac10bd","url":null,"abstract":"Internal combustion engine vehicles have long dominated personal vehicle sales in the United States. As electric vehicles gain market share, understanding fuel costs of gasoline versus electric vehicles (EVs) is increasingly relevant for potential buyers and for researchers. In particular, understanding the influence of fuel price volatility on fuel costs is of interest. Although it is well known that fueling an EV is cheaper than fueling a gasoline vehicle, costs are less commonly expressed in explicit spatially and temporally resolved terms. This note presents an Excel model that includes state-specific gasoline and residential electricity price data for US states between 2015–2020, including both average overall electricity prices and lowest-cost time-of-use electricity rates (measured over a consecutive 8-hour potential residential charging period) for each state. This model, which we call the Fuel Cost Calculator, also allows users to evaluate the impact of several major external and driver behavior factors on fuel costs for gasoline versus electric vehicles. These combinations of these factors result in unique scenarios which make price differences for the fuel costs more variable. With the Fuel Cost Calculator, the user can create specific scenarios reflecting potential real-world conditions to create cost estimates for gasoline and residential EV fueling over user-determined time periods and distances. Fuel costs for gasoline vehicles are generally higher than for electric vehicles in the US, consistent with prior studies. We also explicitly show that fuel cost budgets are much more volatile for gasoline versus electric vehicles charged at a residence, given the much less stable price of oil versus electricity. This volatility is sufficiently large so as to be relevant for vehicle owner budgets. The FCC also shows carbon dioxide (CO2) emissions associated with vehicle use, resolved at the state level.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61193617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1