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Urban waterlogging control: A novel method to urban drainage pipes reconstruction, systematic and automated

JOUrNAL OF CLEANEr PrODUCTION 2023年第1期418卷

作者： Liu, Yang Zhao, Weigao Wei, Yingxia Sebastian, Fiallos Salguero Manuel Wang, Mingna Tianjin Univ Sch Civil Engn Tianjin 300072 Peoples R China Tianjin Univ Sch Environm Sci & Engn Tianjin 300072 Peoples R China Tianjin Univ Tianjin 300072 Peoples R China

reconstruction of the drainage system is an important measure for urban waterlogging control. For the drainage system of the community, factors such as upstream pipeline water capacity and downstream bottleneck pipeline are often neglected in the process of network reconstruction. Only the network in the waterlogged area is reformed, which is lack of systematicness, and may lead to the failure of waterlogging control. To solve this problem, the Storm Water Management Model (SWMM 5.1) is used to analyze the rationality of the current pipe network reconstruction methods using three indicators: the maximum overflow depth, the maximum overflow volume, and the conduit surcharge. And a new reconstruction method for drainage pipe networks is developed by r programming. The results show that the current pipe network reconstruction method is still insufficient to achieve the goal of eliminating node overflow. For different rainfall conditions, there are still existing low-risk areas, with maximum overflow depth can reach up to 0.15 m and maximum overflow volume can reach up to 7.12 m3. The novel developed drainage pipe network reconstruction method (optimizing pipe network) can effectively identify the bottleneck pipes, and by repeatedly expanding the bottleneck pipes, the goal of node overflow can be achieved under a given rainfall event.

关键词： Waterlogging control Pipe network reconstruction Storm water management model r programming

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Application of digital holographic microscopy to evaluate the dynamics of a single red blood cell influenced by low-power laser light

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OPTICS AND LASEr TECHNOLOGY 2021年 142卷 107262-107262页

作者： Kucharski, Dawid Bartczak, Monika Poznan Univ Tech Inst Mech Technol Div Metrol & Measurement Syst Poznan Poland

In the paper, a shift of individual human erythrocytes drifts speed, stimulated by various low-power lasers irradiation, was studied by digital holographic microscopy (DHM). Well known in physiotherapy, a low-levellaser-therapy (LLLT) scanner was used as the stimulation light source, with diode and He-Ne lasers to compare. In the article, an open-source image processing algorithm for simultaneous dynamics and geometrical properties evaluations of the red blood cells is proposed. A strong influence of the low-level red light on the red blood cells dynamics was observed. The effect is important for a better understanding of the laser treatment mechanism. The proposed phase image analysis algorithm significantly improves the individual cells tracing precision for a life science application. The programme might be useful for optical tweezer, imaging flow cytometry, or high precision cells-photon interaction research.

关键词： Digital holographic microscopy Optical tweezers Optical metrology Image processing algorithm red blood cells r programming

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rBioCloud: A Light-Weight Framework for Bioconductor and r-based Jobs on the Cloud

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IEEE-ACM TrANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFOrMATICS 2015年第4期12卷 871-878页

作者： Varghese, Blesson Patel, Ishan Barker, Adam Univ St Andrews Sch Comp Sci St Andrews KY16 9AJ Fife Scotland IBM Canada Ltd Markham ON L3R 9Z7 Canada

Large-scale ad hoc analytics of genomic data is popular using the r-programming language supported by over 700 software packages provided by Bioconductor. More recently, analytical jobs are benefitting from on-demand computing and storage, their scalability and their low maintenance cost, all of which are offered by the cloud. While biologists and bioinformaticists can take an analytical job and execute it on their personal workstations, it remains challenging to seamlessly execute the job on the cloud infrastructure without extensive knowledge of the cloud dashboard. How analytical jobs can not only with minimum effort be executed on the cloud, but also how both the resources and data required by the job can be managed is explored in this paper. An open-source light-weight framework for executing r-scripts using Bioconductor packages, referred to as 'rBioCloud', is designed and developed. rBioCloud offers a set of simple command-line tools for managing the cloud resources, the data and the execution of the job. Three biological test cases validate the feasibility of rBioCloud. The framework is available from http://***.

关键词： Cloud computing r programming Bioconductor Amazon web services data analytics

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SoilSpatvis: WEB Application for Geographical Data Visualization with r Language for Assessing Soil Pollution

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SOIL & SEDIMENT CONTAMINATION 2024年第7期33卷 961-975页

作者： Kaya, Efdal Senturk, Erman Erener, Arzu Ozkul, Cafer Akyol, Nihat Hakan Iskenderun Tech Univ Dept Architecture & Urban Planning Hatay Turkiye Kocaeli Univ Dept Geomat Engn Kocaeli Turkiye Dumlupinar Univ Dept Geol Engn Kutahya Turkiye Kocaeli Univ Dept Geol Engn Kocaeli Turkiye Univ Alabama Dept Geol Sci Tuscaloosa AL USA Univ Alabama Dept Geol Sci Tuscaloosa AL 35487 USA

recently, user-friendly internet-based applications are becoming popular in parallel with rapidly developing technology. With the growing information technology, computing power, and wealth of data available, analyzing spatial data has become an important subject for scientists who are interested in earth sciences. Thus, in terms of the software used for spatial data analysis, WEB-based applications have become the essential and increasingly popular for many applications. Here, a WEB-based software developed with r language is introduced. The software named as SoilSpatVis provides spatial data analysis and visualization. SoilSpatVis includes a desktop application that performs internet-based geographic data analysis using the K-means method, one of the machine learning algorithms. In the study, different soil pollution parameters collected from some sample sites in the border town of Kutahya, Turkey were used. These parameters were transferred into rStudio software which supports r language. The data were firstly clustered using the K-means algorithm and a visualization section was created for cluster analysis. The "Visualizations" page has been created which allows composing different graphs according to the desired parameter, and the "About" page provides information about the team that developed the application. Various geographic analysis tools are being added to the application and software codes are shared via GitHub.

关键词： Spatial data analysis r programming K-means WEB application

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Data Science in Social Politics with Particular Emphasis on Sentiment Analysis

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Procedia Computer Science 2022年 214卷 420-427页

作者： raúl Felipe Parra Aramburo Miguel Ângelo Lellis Moreira Luiz Paulo Lopes Fávero Igor Pinheiro de Araújo Costa Marcos dos Santos University of São Paulo São Paulo SP 05508-220 Brazil Fluminense Federal University Niterói RJ 24210-240 Brazil Naval Systems Analysis Center Rio de Janeiro RJ 20091-000 Brazil Military Institute of Engineering Urca RJ 22290-270 Brazil

The social network Twitter has become a way of promoting opinions that have not gone unnoticed in current societies' social and political events. This research focuses on performing sentiment analysis of the publications on the social network Twitter from March 2021 to August 2021 to analyze users' feelings, reactions, and perceptions regarding the 2021 National Strike in Cali-Colombia, through techniques based on Text Mining and Machine Learning. A five stages methodology is proposed, which is composed of: data set identification, data extraction, data pre-processing, data processing, and results. This work intends to serve as a basic methodological instrument for future research implementing the use of computational tools, particularly sentiment analysis, to identify and analyze behavior patterns based on information related to citizens' reactions in social networks.

关键词： Word Cloud Web Scraping r programming Social Perception Text Mining

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Metabolites rapid-annotation in mice by comprehensive method of virtual polygons and Kendric mass loss filtering: A case study of Dendrobium nobile Lindl

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JOUrNAL OF PHArMACEUTICAL AND BIOMEDICAL ANALYSIS 2024年 243卷 116106页

作者： Wu, Xingdong Fan, Qingjie Gao, Chunxue Wu, Jiajia Wu, Di Hu, Enming Tan, Daopeng Zhao, Yongxia Li, Xiaoshan Yang, Zhou Qin, Lin He, Yuqi Zunyi Med Univ Guizhou Engn Res Ctr Ind Key Technol Dendrobium No Joint Int Res Lab Ethnomed Minist Educ Zunyi 563000 Guizhou Peoples R China Shanghai Jiao Tong Univ Sch Pharm Shanghai Key Lab Mol Engn Chiral Drugs Shanghai 200240 Peoples R China Key Lab Chem Nat Prod Guizhou Prov Guiyang 550016 Guizhou Peoples R China Chinese Acad Sci Guiyang 550016 Guizhou Peoples R China Guizhou Stand Pharmaceut Hlth Co Ltd Zunyi 563000 Peoples R China

With significant advancements in high-resolution mass spectrometry, there has been a substantial increase in the amount of chemical component data acquired from natural products. Therefore, the rapid and efficient extraction of valuable mass spectral information from large volumes of high-resolution mass spectrometry data holds crucial significance. This study illustrates a targeted annotation of the metabolic products of alkaloid and sesquiterpene components from Dendrobium nobile (D. nobile) aqueous extract in mice serum through the integration of an in-houses database, r programming, a virtual metabolic product library, polygonal mass defect filtering, and Kendrick mass defect strategies. The research process involved initially establishing a library of alkaloids and sesquiterpenes components and simulating 71 potential metabolic reactions within the organism using r programming, thus creating a virtual metabolic product database. Subsequently, employing the virtual metabolic product library allowed for polygonal mass defect filtering, rapidly screening 1705 potential metabolites of alkaloids and 3044 potential metabolites of sesquiterpenes in the serum. Furthermore, based on the chemical composition database of D. nobile and online mass spectrometry databases, 95 compounds, including alkaloids, sesquiterpenes, and endogenous components, were characterized. Finally, utilizing Kendrick mass defect analysis in conjunction with known alkaloids and sesquiterpenes targeted screening of 209 demethylation, methylation, and oxidation products in phase I metabolism, and 146 glucuronidation and glutathione conjugation products in phase II metabolism. This study provides valuable insights for the rapid and accurate annotation of chemical components and their metabolites in vivo within natural products.

关键词： Polygonal mass defect Kendrick mass defect r programming Dendrobium nobile Metabolite identification

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Harnessing open science practices to teach ecology and evolutionary biology using interactive tutorials

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ECOLOGY AND EVOLUTION 2024年第6期14卷 e11179页

作者： Griffith, Jory E. Houghton, Elizabeth Slein, Margaret A. Fraser Franco, Maxime Chavez, Jhoan Forsythe, Amy B. Glynn, Victoria M. Katkov, Egor Palmier, Kirsten M. Sang, Zihaohan Trejo-Perez, rolando Wiley, Bryn Sunday, Jennifer M. Bernhardt, Joey r. McGill Univ Dept Biol Montreal PQ Canada Univ British Columbia Okanagan Dept Biol Kelowna BC Canada Univ British Columbia Dept Zool Vancouver BC Canada Univ Quebec Montreal Dept Sci Biol Montreal PQ Canada Univ Northern British Columbia Dept Geog Earth & Environm Sci Prince George BC Canada McGill Univ Redpath Museum Montreal PQ Canada Smithsonian Trop Res Inst Balboa Panama Univ Regina Dept Biol Regina SK Canada Univ Toronto St George Dept Comp Sci Toronto ON Canada Univ Montreal Inst Rech Biol Vegetale Montreal PQ Canada Univ Guelph Dept Integrat Biol Guelph ON Canada

Open science skills are increasingly important for a career in ecology and evolutionary biology (EEB) as efforts to make data and analyses publicly available continue to become more commonplace. While learning core concepts in EEB, students are also expected to gain skills in conducting open science to prepare for future careers. Core open science skills like programming, data sharing, and practices that promote reproducibility can be taught to undergraduate students alongside core concepts in EEB. Yet, these skills are not always taught in biology undergraduate programs, and a major challenge in developing open science skills and learning EEB concepts simultaneously is the high cognitive load associated with learning multiple disparate concepts at the same time. One solution is to provide students with easily digestible, scaffolded, pre-formatted code in the form of vignettes and interactive tutorials. Here, we present six open source teaching tutorials for undergraduate students in EEB. These tutorials teach fundamental ecological concepts, data literacy, programming (using r software), and analysis skills using publicly available datasets while introducing students to open science concepts and tools. Spanning a variety of EEB topics and skill levels, these tutorials serve as examples and resources for educators to integrate open science tools, programming, and data literacy into teaching EEB at the undergraduate level. Open science skills are becoming increasingly important in academic and industry working environments in the fields of ecology and evolutionary biology (EEB). Yet, learning EEB concepts alongside open science skills such as programming is challenging for undergraduate students. To address this issue, we developed six open-access interactive tutorials integrating open science tools, programming, and data literacy into undergraduate teaching on topics of ecology and ***

关键词： cognitive load theory educational resources online tutorials open science r programming student-centered learning teaching undergraduate education

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SMEs in Covid-19 Crisis and Combating Strategies: A Systematic Literature review (SLr) and A Case from Emerging Economy

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OPErATIONS rESEArCH PErSPECTIVES 2022年 9卷

作者： Hossain, Mohammad rokibul Akhter, Fahmida Sultana, Mir Misnad Premier Univ Fac Business Studies Dept Business Adm Chittagong Bangladesh East Delta Univ Sch Business Adm Chittagong Bangladesh BGC Trust Univ Fac Business Adm Chittagong Bangladesh

The paper intends to understand the research trends in "Covid-19 and SME" through a Systematic Literature review (SLr) and extract themes to explore the most affected areas of SMEs during the Covid-19 pandemic. Subsequently, the study attempts to know the struggles of SME during Covid-19 crisis in a developing country . Furthermore, the study provides a critical dynamic resilience strategy framework to manage the SMEs in the crisis period. The authors extracted data from Scopus and Web of science to conduct a Systematic Literature review (SLr), Extracted data from both databases were merged using r programming get the same tag in r programming. The study adopts a bibliometric analysis to present the research corpus in the domain of "Covid-19 and SMEs". The cluster method of r programming has been used to usher the significantly affected areas of SMEs. Based on the cluster theme, an open-ended questionnaire was developed and used to interview 23 SMEs in Bangladesh for the case study. NVIVO-13.00 was used to extract the topic from the transcriptions of the interviews. The study reveals that Cash flow shortages and Supply Chain Disruptions are the critical constraints of SMEs. On the contrary, Digital transformation has gained momentum during this crisis. Enterprises that made the best use of digital platforms through technology, digital marketing, and innovations secured the peak of success and profitability. The study also recommends a critical dynamic, resilient strategy model to adopt in the "new normal" for successful navigation of SME business in the future. The study is the first of its kind that integrates SLr and a case study on the hurdles of SME owners during the Covid 19 crisis. Thus, it helps advance the understanding of the subject matter and enables the formulation of resilient strategies by policymakers and SME owners to navigate the business in any potential crisis in the future. The study has significant methodological contribution as it presents how

关键词： Small and Medium Enterprise (SME) Systematic Literature review (SLr) Co-word Analysis Supply Chain Disruption Cash Flow shortages r programming

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Indicators of wind-driven forest disturbances-pit-mound topography, its automatic detection and significance

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CATENA 2023年 221卷

作者： Godziek, Janusz Pawlik, Lukasz Univ Silesiaia Inst Earth Sci Fac Nat Sci Ul Bedzinska 60 PL-41200 Sosnowiec Poland Univ Silesiaia Int Environm Doctoral Sch Ul Bedzinska 60 PL-41200 Sosnowiec Poland

Pit-and-mound topography is a result of tree uprooting caused by hurricane-force wind events and hence can act as a bioindicator of forest disturbance. The occurrence and evolution of pit-mound topography can be analyzed using detailed elevation data, such as point clouds from Light Detection and ranging (LiDAr) surveys. The objective of this study was to develop an automatic method of pit-mound topography detection. We propose the usage of closed contour lines to extract the locations of pits and mounds. We performed analyses in two study areas (Markowa and Ston ' ow) located on the Babia G ' ora Massif (southern Poland). We computed the digital elevation model (DEM), extracted contour lines, calculated the length of each contour line and selected only closed contours belonging to a specified length interval. Then, we created polygons from the outermost closed contour lines. We classified polygons into "pits" and "mounds" by investigating the location of the highest and lowest altitudes within the polygon. We tested 27 variants of our method using different DEM spatial resolutions, contour intervals and contour length intervals. To estimate the accuracy of our method, we created a validation dataset by performing manual recognition of pit-mound pairs based on the topographic position index (TPI). One of the highest accuracies, obtained for the 1st variant of our method, reached 96.9 % for pits, 93.8 % for mounds and 90.6 % for pit-mound pairs in the Ston ' ow area. In the Markowa area, this variant achieved an accuracy of 95.2 % for pits, 90.5 % for mounds and 85.7 % for pit-mound pairs. Our method can be used as an important step in analyses conducted in forest ecology, geomorphology or soil science.

关键词： pit-mound topography LiDAr digital elevation model geomorphometry r programming Polish Carpathians

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A data science and open source software approach to analytics for strategic sourcing

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INTErNATIONAL JOUrNAL OF INFOrMATION MANAGEMENT 2020年 54卷 102167-102167页

作者： Boehmke, Brad Hazen, Benjamin Boone, Christopher A. robinson, Jessica L. Data Sci Chicago IL USA Univ Appl Sci Upper Austria Logistikum Wels Austria Mississippi State Univ Mississippi State MS 39762 USA Calif State Univ Long Beach Long Beach CA 90840 USA

Data science has emerged as a significant capability upon which firms compete. Although many data scientists and the high-performing companies that employ them seem to have developed robust methods to employ data sciences practices to achieve competitive advantages, there have been few attempts at defining and explaining how and why data science helps firms to achieve desired outcomes. In this paper, we describe how data science, which combines computer programming, domain knowledge, and analytic skillsets to scientifically extract insights from data, can be used to help meet the growing demand of analytic needs across an organization's value chain. This is done through the illustration of an applied data science initiative to a strategic sourcing problem via the use of open-source technology. In doing so, we contribute to the growing data science literature by demonstrating the application of unique data science capabilities. Moreover, the paper provides a tutorial on how to use a specific r package along with an actual case in which that package use used.

关键词： Data science Strategic sourcing Purchasing portfolio Supply chain management Open source r programming Decision support

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