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Machine Learning and Deep Learning for Smart Urban Transportation Systems with GPS， GIS， and advanced analytics: A Comprehensive Analysis

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Journal of Harbin institute of Technology(New series) 2024年

作者： E. Kalaivanan S.Brindha Department of Computer Science and Applications St.Peters institute of Higher Education And Research

As urbanization continues to accelerate， the challenges associated with managing transportation in metropolitan areas become increasingly complex. The surge in population density contributes to traffic congestion， impacting travel experiences and posing safety risks. Smart urban transportation management emerges as a strategic solution， conceptualized here as a multidimensional big data problem. The success of this strategy hinges on the effective collection of information from diverse， extensive， and heterogeneous data sources， necessitating the implementation of full-stack Information and Communication Technology (ICT) solutions. The main idea of the work is to investigate the current technologies of ITS and enhance the safety of urban transportation systems. Machine learning models， trained on historical data， can predict traffic congestion， allowing for the implementation of preventive measures. Deep learning architectures， with their ability to handle complex data representations， further refine traffic predictions， contributing to more accurate and dynamic transportation management. The background of this research underscores the challenges posed by traffic congestion in metropolitan areas and emphasizes the need for advanced technological solutions. By integrating GPS and GIS technologies with machine learning algorithms， this work aims to pay attention to the development of intelligent transportation systems that not only address current challenges but also pave the way for future advancements in urban transportation management.

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Inequity in the global distribution of monkeypox vaccines

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World Journal of Clinical Cases 2023年第19期11卷 4498-4503页

作者： Marcos Roberto Tovani-Palone Neel Doshi Paolo Pedersini Department of Research analytics Saveetha Dental College and HospitalsSaveetha Institute of Medical and Technical SciencesChennai 600077India Department of Medicine Pravara Institute of Medical SciencesAhmednagar 413736India IRCCS Fondazione Don Carlo Gnocchi Milan 20148Italy

Monkeypox(mpox)has been a public health emergency of international concern that emerged in mid-2022 and has spread to 110 *** clinical findings of the disease vary according to the seriousness of the *** its case fatality risk has not been high,a significant percentage of patients require *** this context,local initiatives were taken to extend the limited supply of vaccines against the disease;however,such measures have not been sufficient to contain the spread of cases and ensure an equitable distribution of health *** a result,endemic regions of low-income countries continue to have insufficient access to mpox *** this and considering the global scope of the disease,there is still little discussion in the literature about the difficulties in achieving adequate vaccination coverage rates for the target population of *** this article,we briefly discussed general aspects of the disease,including its surveillance,the current global context of challenges for mpox vaccination,and issues on global allocation of health resources as well as proposed related recommendations.

关键词： Monkeypox Smallpox vaccine Health inequities Vaccination coverage Vaccination hesitancy Healthcare financing

Nanoscale chemical imaging of individual chemotherapeutic cytarabineloaded liposomal nanocarriers

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Nano Research 2019年第1期12卷 197-203页

作者： Karin Wieland Georg Ramer Victor U. Weiss Guenter Allmaier Bemhard Lendl Andrea Centrone institute of Chemical Technologies and analytics Research Division EnvironmentalProcess Analytics and SensorsTU WienVienna 1060Austria Center for Nanoscale Science and Technology National Institute of Standards and TechnologyGaithersburgMD 20899USA institute for Research in Electronics and Applied Physics University of MarylandCollege ParkMD 20742USA institute of Chemical Technologies and analytics Research Division Instrumental and Imaging Analytical ChemistryTU WienVienna 1060Austria

Dosage of chemotherapeutic drugs is a tradeoff between efficacy and *** are nanocarriers that increase therapy efficacy and minimize side-effects by delivering otherwise difficult to administer therapeutics with improved efficiency and ***,variabilities in liposome preparation require assessing drug encapsulation efficiency at the single liposome level,an information that,for non-fluorescent therapeutic cargos,is inaccessible due to the minute drug load per *** induced resonance (PTIR) provides nanoscale compositional specificity,up to now,by leveraging an atomic force microscope (AFM) tip contacting the sample to transduce the sample's photothermal ***,on soft samples (e.g.,liposomes) PTIR effectiveness is reduced due to the likelihood of tip-induced sample damage and inefficient AFM ***,individual liposomes loaded with the chemotherapeutic drug cytarabine are deposited intact from suspension via nano-electrospray gas-phase electrophoretic mobility molecular analysis (nES-GEMMA) collection and characterized at the nanoscale with the chemically-sensitive PTIR method.A new tapping-mode PTIR imaging paradigm based on heterodyne detection is shown to be better adapted to measure soft samples,yielding cytarabine distribution in individual liposomes and enabling classification of empty and drug-loaded *** measurements highlight PTIR capability to detect ~ 103 cytarabine molecules (~ 1.7 zmol) label-free and non-destructively.

关键词： tapping photothermal induced resonance (PTIR) nanoscale chemical imaging liposomes cytarabine drug delivery nanocarriers

Secretive derived from hypoxia preconditioned mesenchymal stem cells promote cartilage regeneration and mitigate joint inflammation via extracellular vesicles

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Bioactive Materials 2023年第9期27卷 98-112页

作者： Yanmeng Yang Yingnan Wu Dahou Yang Shu Hui Neo Nurul Dinah Kadir Doreen Goh Jian Xiong Tan Vinitha Denslin Eng Hin Lee Zheng Yang Department of Orthopaedic Surgery Yong Loo Lin School of MedicineNational University of SingaporeSingapore NUS Tissue Engineering Program Life Sciences InstituteNational University of SingaporeSingapore Critical analytics for Manufacturing Personalised-Medicine Singapore-MIT Alliance for Research and TechnologySingapore

Secretome derived from mesenchymal stem cells (MSCs) have profound effects on tissue regeneration, which could become the basis of future MSCs therapies. Hypoxia, as the physiologic environment of MSCs, has great potential to enhance MSCs paracrine therapeutic effect. In our study, the paracrine effects of secretome derived from MSCs preconditioned in normoxia and hypoxia was compared through both in vitro functional assays and an in vivo rat osteochondral defect model. Specifically, the paracrine effect of total EVs were compared to that of soluble factors to characterize the predominant active components in the hypoxic secretome. We demonstrated that hypoxia conditioned medium, as well as the corresponding EVs, at a relatively low dosage, were efficient in promoting the repair of critical-sized osteochondral defects and mitigated the joint inflammation in a rat osteochondral defect model, relative to their normoxia counterpart. In vitro functional test shows enhancement through chondrocyte proliferation, migration, and matrix deposition, while inhibit IL-1β-induced chondrocytes senescence, inflammation, matrix degradation, and pro-inflammatory macrophage activity. Multiple functional proteins, as well as a change in EVs’ size profile, with enrichment of specific EV-miRNAs were detected with hypoxia preconditioning, implicating complex molecular pathways involved in hypoxia pre-conditioned MSCs secretome generated cartilage regeneration.

关键词： Hypoxia preconditioned MSCs Secretome Extracellular vesicles Cartilage regeneration Joint inflammation

Modern internet search analytics and thyroidectomy:What are patients asking?

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World Journal of Otorhinolaryngology-Head and Neck Surgery 2024年第1期10卷 49-58页

作者： Neeraj Suresh Christian Fritz Emma De Ravin Karthik Rajasekaran Department of Otorhinolaryngology–Head&Neck Surgery University of PennsylvaniaPhiladelphiaPennsylvaniaUSA Perelman School of Medicine at the University of Pennsylvania PhiladelphiaPennsylvaniaUSA Leonard Davis institute of Health Economics University of PennsylvaniaPhiladelphiaPennsylvaniaUSA

Objectives:Thyroidectomy is among the most commonly performed head and neck surgeries,however,limited existing information is available on topics of interest and concern to *** Design:***:***:A search engine optimization tool was utilized to extract metadata on Google‐suggested questions that“People Also Ask”(PAA)pertaining to“thyroidectomy”and“thyroid surgery.”These questions were categorized by Rothwell criteria and topics of *** Journal of the American Medical Association(JAMA)benchmark criteria enabled quality ***:A total of 250 PAA questions were ***‐oriented PAA questions describing what to expect during and after the surgery on topics such as postoperative management,risks or complications of surgery,and technical details were significantly less popular among the“thyroid surgery”group(P<0.001,P=0.005,and P<0.001,respectively).PAA questions about scarring and hypocalcemia were nearly threefold more popular than those related to pain(335 and 319 vs.113 combined search engine response page count,respectively).The overall JAMA quality score remained low(2.50±1.07),despite an increasing number of patients searching for“thyroidectomy”(r(77)=0.30,P=0.007).Conclusions:Patients searching for the nonspecific term“thyroid surgery”received a curated collection of PAA questions that were significantly less likely to educate them on what to expect during and after surgery,as compared to patients with higher health literacy who search with the term“thyroidectomy.”This suggests that the content of PAA questions differs based on the presumed health literacy of the internet user.

关键词： information quality online health education search analytics thyroid surgery thyroidectomy

Item-level Forecasting for E-commerce Demand with High-dimensional Data Using a Two-stage Feature Selection Algorithm

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Journal of Systems Science and Systems Engineering 2022年第2期31卷 247-264页

作者： Hongyan Dai Qin Xiao Nina Yan Xun Xu Tingting Tong Business School Central University of Finance and EconomicsBeijing 100081China Department of Management Operationsand MarketingCollege of Business AdministrationCalifornia State UniversityStanislausTurlockCA95382United States institute of Supply Chain analytics&International Business College Dongbei University of Finance and EconomicsDalian 116025China

With the rapid development of information technology and fast growth of Internet users,e-commerce nowadays is facing complex business environment and accumulating large-volume and highdimensional *** brings two challenges for demand ***,e-merchants need to find appropriate approaches to leverage the large amount of data and extract forecast features to capture various factors affecting the ***,they need to efficiently identify the most important features to improve the forecast accuracy and better understand the key drivers for demand *** solve these challenges,this study conducts a multi-dimensional feature engineering by constructing five feature categories including historical demand,price,page view,reviews,and competition for e-commerce demand forecasting on *** then propose a two-stage random forest-based feature selection algorithm to effectively identify the important features from the high-dimensional feature set and avoid *** test our proposed algorithm with a large-scale dataset from the largest e-commerce platform in *** numerical results from 21,111 items and 109 million sales observations show that our proposed random forest-based forecasting framework with a two-stage feature selection algorithm delivers 11.58%,5.81%and 3.68%forecast accuracy improvement,compared with the Autoregressive Integrated Moving Average(ARIMA),Random Forecast,and Random Forecast with one-stage feature selection approach,respectively,which are widely used in literature and *** study provides a useful tool for the practitioners to forecast demands and sheds lights on the B2C e-commerce operations management.

关键词： Forecasting e-commerce high-dimensional feature feature selection

LexDeep:Hybrid Lexicon and Deep Learning Sentiment Analysis Using Twitter for Unemployment-Related Discussions During COVID-19

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计算机、材料和连续体（英文） 2023年第4期75卷 1577-1601页

作者： Azlinah Mohamed Zuhaira Muhammad Zain Hadil Shaiba Nazik Alturki Ghadah Aldehim Sapiah Sakri Saiful Farik Mat Yatin Jasni Mohamad Zain institute for Big Data analytics and Artificial Intelligence Universiti Teknologi MARA(UiTM)Shah AlamMalaysia College of Computer and Information Sciences Princess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA(UiTM)Shah AlamMalaysia

The COVID-19 pandemic has spread globally,resulting in financialinstability in many countries and reductions in the per capita grossdomestic *** analysis is a cost-effective method for acquiringsentiments based on household income loss,as expressed on social ***,limited research has been conducted in this domain using theLexDeep *** study aimed to explore social trend analytics usingLexDeep,which is a hybrid sentiment analysis technique,on Twitter to capturethe risk of household income loss during the COVID-19 ***,tweet data were collected using Twint with relevant keywords before(9 March2019 to 17 March 2020)and during(18 March 2020 to 21 August 2021)***,the tweets were annotated using VADER(lexiconbased)and fed into deep learning classifiers,and experiments were conductedusing several embeddings,namely simple embedding,Global Vectors,andWord2Vec,to classify the sentiments expressed in the *** performanceof each LexDeep model was evaluated and compared with that of a supportvector machine(SVM).Finally,the unemployment rates before and duringCOVID-19 were analysed to gain insights into the differences in unemploymentpercentages through social media input and *** resultsdemonstrated that all LexDeep models with simple embedding outperformedthe *** confirmed the superiority of the proposed LexDeep modelover a classical machine learning classifier in performing sentiment analysistasks for domain-specific *** terms of the risk of income loss,the unemployment issue is highly politicised on both the regional and globalscales;thus,if a country cannot combat this issue,the global economy will alsobe *** research should develop a utility maximisation algorithmfor household welfare evaluation,given the percentage risk of income lossowing to COVID-19.

关键词： Sentiment analysis sentiment lexicon machine learning imbalanced data deep learning method unemployment rate

EPQ model with the effect of inflation and reliability for partial trade credit under fuzzy and cloudy fuzzy environment

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Journal of Management analytics 2024年第1期11卷 110-134页

作者： Supriya Tiwari Kunal Shah Kajal Bhimani Department of Science and Humanities Apollo Institute of Engineering&TechnologyGTUAhmedabadIndia Department of Mathematics SMMPISRKadi Sarva VishwavidyalayaGandhinagarIndia AVAerials 401 Swarnim Business Hub-1 New Chamunda SocietyGodrej Garden CityGotaAhmedabadIndia

The proposed study offers the first-of-its-kind economic production quantity model for deteriorating items having a demand rate to be price dependent under the effect of inflation and reliability with partial trade *** model is extended under an uncertain environment by assuming inventory parameters to be triangular fuzzy numbers and cloudy triangular fuzzy *** objective of the study is to maximize the profit of the inventory system and to identify the most suitable environment for the proposed *** are verified using the numerical ***,the comparative study is presented to justify the nature of fuzzy and cloudy fuzzy *** analysis under all environments is conducted to identify the most sensitive parameters of all.

关键词： EPQ partial trade credit inflation reliability triangular fuzzy number cloudy triangular fuzzy number

Extending OpenStack Monasca for Predictive Elasticity Control

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Big Data Mining and analytics 2024年第2期7卷 315-339页

作者： Giacomo Lanciano Filippo Galli Tommaso Cucinotta Davide Bacciu Andrea Passarella Scuola Normale Superiore Pisa 56126Italy the Real-Time Systems Laboratory(RETIS) TelecommunicationsComputer Engineeringand Photonics Institute(TeCIP)Scuola Superiore Sant’AnnaPisa 56127Italy Department of Computer Science University of PisaPisa 56127Italy National Research Council Pisa56127Italy

Traditional auto-scaling approaches are conceived as reactive automations,typically triggered when predefined thresholds are breached by resource consumption *** such rules at scale is cumbersome,especially when resources require non-negligible time to be *** paper introduces an architecture for predictive cloud operations,which enables orchestrators to apply time-series forecasting techniques to estimate the evolution of relevant metrics and take decisions based on the predicted state of the *** this way,they can anticipate load peaks and trigger appropriate scaling actions in advance,such that new resources are available when *** proposed architecture is implemented in OpenStack,extending the monitoring capabilities of Monasca by injecting short-term forecasts of standard *** use our architecture to implement predictive scaling policies leveraging on linear regression,autoregressive integrated moving average,feed-forward,and recurrent neural networks(RNN).Then,we evaluate their performance on a synthetic workload,comparing them to those of a traditional *** assess the ability of the different models to generalize to unseen patterns,we also evaluate them on traces from a real content delivery network(CDN)*** particular,the RNN model exhibites the best overall performance in terms of prediction error,observed client-side response latency,and forecasting *** implementation of our architecture is open-source.

关键词： OpenStack monitoring elasticity control auto-scaling predictive operations Monasca