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Chronic disease patients have fewer social contacts:A pilot survey with implications for transmission dynamics

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Infectious Disease modelling 2024年第3期9卷 926-930页

作者： J.Vanderlocht S.Møgelmose K.Van Kerckhove P.Beutels N.Hens Interuniversity Institute of Biostatistics and Statistical Bioinformatics Data Science InstituteHasselt UniversityHasseltBelgium centre for Health Economic Research and modelling Infectious Diseases University of AntwerpAntwerpBelgium

Non-communicable diseases(NCD)are the most important cause of death in the *** socio-economic costs associated with NCDs makes it imperative to prevent and control them in the 21st *** severe toll that the COVID-19 pandemic has taken worldwide is an unfortunate illustration of our limited insight into the infectious risk for the global ***-incidence between NCD and infection offers an underexplored opportunity to design preventive *** a pilot survey,we observed that the NCD population displays a substantial reduction in their social contacting behavior as compared to the general *** indicates that existing mathematical models based on contact surveys in the general population are not applicable to the NCD population and that the risk of acquiring an infection following a contact is probably *** demonstration of reduced social mixing in several chronic conditions,raises the question to what extent the social mixing is influenced by the burden of *** advocate the design of disease-specific contact surveys to address how the burden of disease associates with social contact behavior and the risk of *** SARS-CoV-2 pandemic offers an unprecedented opportunity to gain insight into the importance of infection in the NCD population and to find ways to improve healthcare procedures.

关键词： survey mixing insight

Digital Twins for Wastewater Treatment:A Technical Review

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Engineering 2024年第5期36卷 21-35页

作者： Ai-Jie Wang Hewen Li Zhejun He Yu Tao Hongcheng Wang Min Yang Dragan Savic Glen TDaigger Nanqi Ren School of Civil and Environmental Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China State Key Laboratory of Urban Water Resource and Environment Harbin Institute of TechnologyHarbin 150090China Department of Civil and Environmental Engineering Cornell UniversityIthacaNY 14850USA BIOMATH Department of Data Analysis and Mathematical ModellingGhent UniversityGhent 9000Belgium KWR Water Research Institute Nieuwegein 3430 BBNetherlands centre for Water Systems University of ExeterExeter EX44QFUK Department of Civil and Environmental Engineering University of MichiganAnn ArborMI 48109USA

The digital twins concept enhances modeling and simulation through the integration of real-time data and *** review elucidates the foundational elements of digital twins,covering their concept,entities,domains,and key *** specifically,we investigate the transformative potential of digital twins for the wastewater treatment engineering *** discussion highlights the application of digital twins to wastewater treatment plants(WWTPs)and sewage networks,hardware(i.e.,facilities and pipes,sensors for water quality and activated sludge,hydrodynamics,and power consumption),and software(i.e.,knowledge-based and data-driven models,mechanistic models,hybrid twins,control methods,and the Internet of Things).Furthermore,two cases are provided,followed by an assessment of current challenges in and perspectives on the application of digital twins in *** review serves as an essential primer for wastewater engineers navigating the digital paradigm shift.

关键词： Digital twins Urban water systems Wastewater treatment

Spatio-temporal clustering analysis of COVID-19 cases in Johor

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Infectious Disease modelling 2024年第2期9卷 387-396页

作者： Fong Ying Foo Nuzlinda Abdul Rahman Fauhatuz Zahroh Shaik Abdullah Nurul Syafiah Abd Naeeim School of mathematical Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia

At the end of the year 2019,a virus named SARS-CoV-2 induced the coronavirus disease,which is very contagious and quickly spread around the *** new infectious disease is called *** areas,such as the economy,social services,education,and healthcare system,have suffered grave consequences from the invasion of this deadly ***,a thorough understanding of the spread of COVID-19 is required in order to deal with this outbreak before it becomes an infectious *** this research,the daily reported COVID-19 cases in 92 sub-districts in Johor state,Malaysia,as well as the population size associated to each sub-district,are used to study the propagation of COVID-19 disease across space and time in *** time frame of this research is about 190 days,which started from August 5,2021,until February 10,*** clustering technique known as spatio-temporal clustering,which considers the spatio-temporal metric was adapted to determine the hot-spot areas of the COVID-19 disease in Johor at the sub-district *** results indicated that COVID-19 disease does spike in the dynamic populated sub-districts such as the state's economic centre(Bandar Johor Bahru),and during the festive *** findings empirically prove that the transmission rate of COVID-19 is directly proportional to human mobility and the presence of *** the other hand,the result of this study will help the authority in charge in stopping and preventing COVID-19 from spreading and become worsen at the national level.

关键词： Disease mapping COVID-19Hot-spot areas Sub-district level Spatio-temporal clustering Scan statistics

Investigating Stability Properties for Transition Metal Carbonate Precursors Using Universal Cluster Expansion Technique(UNCLE)as Cathodes for Li-Ion Batteries

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材料科学与工程（中英文A版） 2024年第1期14卷 26-33页

作者： Mogahabo Tebogo Morukuladi N.L.Lethole M.C.Masedi N.N.Ngoepe P.E.Ngoepe Materials modelling centre University of LimpopoPrivate Bag x1106Sovenga 0727South Africa Department of Physics University of Fort HareAlice 5700South Africa

The universal cluster expansion technique was used in this study to determine the binary phase diagrams for the transition metal carbonate precursors MCO3(M:Mn,Ni,Co).The use of mixed cathode materials in lithium-ion batteries such as NMC(Ni,Mn and Co)formulations,is a strategic approach to optimize performance,enhance safety and address cost and environmental considerations in the rapidly evolving field of energy *** study focuses on the cost issue related to lithium ion batteries by investigating the manganese rich NMC since manganese is more abundant and *** doped MnCO3 with nickel and doped MnCO3 with cobalt then ran cluster expansion calculations to generate binary *** binary phase diagrams generated indicated that doping MnCO3 with nickel favours the Mn-rich side,while doping MnCO3 with cobalt favours 50%Mn-rich and 50%*** further extracted the most stable structures from both binary diagrams and determined their electronic,mechanical and vibrational stabilities using DFT(density functional theory)calculations within the LDA(local gradient approximation)with Hubbard parameter(U).The electronic properties revealed that both materials are semiconductors due to their narrow energy band gap obtained while the mechanical properties showed that structures are mechanically stable since their necessary conditions for trigonal and triclinic systems were satisfied.

关键词： Binary phase diagrams mechanical properties electronic conductivity phonon dispersion curves.

Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning

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Big Data Mining and Analytics 2024年第2期7卷 294-314页

作者： Shahriar Kaisar Md Mamunur Rashid Abdullahi Chowdhury Sakib Shahriar Shafin Joarder Kamruzzaman Abebe Diro Department of Information Systems and Business Analytics RMIT UniversityMelbourne 3000Australia School of Engineering and Technology Central Queensland UniversityRockhampton 4700Australia Faculty of Engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide 5005Australia centre for Smart Analytics Federation University AustraliaBallarat 3350Australia School of Accounting Information Systems and Supply ChainRMIT UniversityMelbourne 3000Australia

Telemarketing is a well-established marketing approach to offering products and services to prospective *** effectiveness of such an approach,however,is highly dependent on the selection of the appropriate consumer base,as reaching uninterested customers will induce annoyance and consume costly enterprise resources in vain while missing interested *** introduction of business intelligence and machine learning models can positively influence the decision-making process by predicting the potential customer base,and the existing literature in this direction shows promising ***,the selection of influential features and the construction of effective learning models for improved performance remain a ***,from the modelling perspective,the class imbalance nature of the training data,where samples with unsuccessful outcomes highly outnumber successful ones,further compounds the problem by creating biased and inaccurate ***,customer preferences are likely to change over time due to various reasons,and/or a fresh group of customers may be targeted for a new product or service,necessitating model retraining which is not addressed at all in existing works.A major challenge in model retraining is maintaining a balance between stability(retaining older knowledge)and plasticity(being receptive to new information).To address the above issues,this paper proposes an ensemble machine learning model with feature selection and oversampling techniques to identify potential customers more accurately.A novel online learning method is proposed for model retraining when new samples are available over *** newly introduced method equips the proposed approach to deal with dynamic data,leading to improved readiness of the proposed model for practical adoption,and is a highly useful addition to the *** experiments with real-world data show that the proposed approach achieves excellent results in all cases(e.g.,98.6

关键词： machine learning online learning oversampling telemarketing imbalanced dataset ensemble model

Comparison of Semi-Parametric Shared Frailty Models for Bees’Survival

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Journal of Data Analysis and Information Processing 2024年第2期12卷 267-288页

作者： Patience Isiaho Daisy Salifu Samuel Mwalili Henri E. Z. Tonnang Department of Statistics and Actuarial Sciences Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya Data Management Modelling and Geo-Information Unit International Centre of Insect Physiology and Ecology (ICIPE) Nairobi Kenya

Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.

关键词： Correlated Failure Times Frailty Survival Analysis Unobserved Heterogeneity

modelling the Survival of Western Honey Bee Apis mellifera and the African Stingless Bee Meliponula ferruginea Using Semiparametric Marginal Proportional Hazards Mixture Cure Model

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Journal of Data Analysis and Information Processing 2024年第1期12卷 24-39页

Classical survival analysis assumes all subjects will experience the event of interest, but in some cases, a portion of the population may never encounter the event. These survival methods further assume independent survival times, which is not valid for honey bees, which live in nests. The study introduces a semi-parametric marginal proportional hazards mixture cure (PHMC) model with exchangeable correlation structure, using generalized estimating equations for survival data analysis. The model was tested on clustered right-censored bees survival data with a cured fraction, where two bee species were subjected to different entomopathogens to test the effect of the entomopathogens on the survival of the bee species. The Expectation-Solution algorithm is used to estimate the parameters. The study notes a weak positive association between cure statuses (ρ1=0.0007) and survival times for uncured bees (ρ2=0.0890), emphasizing their importance. The odds of being uncured for A. mellifera is higher than the odds for species M. ferruginea. The bee species, A. mellifera are more susceptible to entomopathogens icipe 7, icipe 20, and icipe 69. The Cox-Snell residuals show that the proposed semiparametric PH model generally fits the data well as compared to model that assume independent correlation structure. Thus, the semi parametric marginal proportional hazards mixture cure is parsimonious model for correlated bees survival data.

关键词： Mixture Cure Models Clustered Survival Data Correlation Structure Cox-Snell Residuals EM Algorithm Expectation-Solution Algorithm

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污水处理工程中的数字孪生技术（英文）

Engineering 2024年第5期 21-35页

作者：王爱杰李贺文贺哲君陶彧王鸿程杨敏 Dragan Savic Glen T.Daigger 任南琪 School of Civil and Environmental Engineering Harbin Institute of Technology (Shenzhen) State Key Laboratory of Urban Water Resource and Environment Harbin Institute of Technology Department of Civil and Environmental Engineering Cornell University BIOMATH Department of Data Analysis and Mathematical Modelling Ghent University KWR Water Research Institute centre for Water Systems University of Exeter Department of Civil and Environmental Engineering University of Michigan

The digital twins concept enhances modeling and simulation through the integration of real-time data and feedback. This review elucidates the foundational elements of digital twins, covering their concept,entities, domains, and key technologies. More specifically, we investigate the transformative potential of digital twins for the wastewater treatment engineering sector. Our discussion highlights the application of digital twins to wastewater treatment plants(WWTPs) and sewage networks, hardware(i.e., facilities and pipes, sensors for water quality and activated sludge, hydrodynamics, and power consumption), and software(i.e., knowledge-based and data-driven models, mechanistic models, hybrid twins, control methods, and the Internet of Things). Furthermore, two cases are provided, followed by an assessment of current challenges in and perspectives on the application of digital twins in WWTPs. This review serves as an essential primer for wastewater engineers navigating the digital paradigm shift.

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An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2873-2897页

作者： Yingui Qiu Shuai Huang Danial Jahed Armaghani Biswajeet Pradhan Annan Zhou Jian Zhou School of Resources and Safety Engineering Central South UniversityChangsha410083China School of Civil and Environmental Engineering University of Technology SydneyNew South WalesAustralia centre for Advanced modelling and Geospatial Information Systems School of Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNew SouthWalesAustralia Civil and Infrastructure Engineering Discipline School of EngineeringRoyal Melbourne Institute of Technology(RMIT)MelbourneVictoria3001Australia

As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and *** the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction *** performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine *** previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of ***,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF *** the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,*** examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM *** of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied *** newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed ***,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHA

关键词： Tunnel boring machine random forest GOGHS optimization PSO optimization GA optimization ABC optimization SHAP