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Performance of statistical and machine learning-based methods for predicting biogeographical patterns of fungal productivity in forest ecosystems

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Forest Ecosystems 2021年第2期8卷 278-291页

作者： Albert Morera juan martínez de Aragón josé Antonio Bonet jingjing Liang Sergio de-Miguel Department of Crop and Forest Sciences University of LleidaAv.Alcalde Rovira Roure 191E-25198 LleidaSpain joint Research Unit CTFC-AGROTECnIO-CERCA Center Av.Rovira Roure 19125198 LleidaSpain Forest Science and Technology Centre of Catalonia Ctra.Sant Llorençde Morunys km 225280 SolsonaSpain Forest Advanced Computing and Artificial Intelligence Laboratory Department of Forestry and Natural ResourcesPurdue UniversityWest LafayetteIN 47907USA

Background:The prediction of biogeographical patterns from a large number of driving factors with complex interactions,correlations and non-linear dependences require advanced analytical methods and modeling tools.This study compares different statistical and machine learning-based models for predicting fungal productivity biogeographical patterns as a case study for the thorough assessment of the performance of alternative modeling approaches to provide accurate and ecologically-consistent predictions.Methods:We evaluated and compared the performance of two statistical modeling techniques,namely,generalized linear mixed models and geographically weighted regression,and four techniques based on different machine learning algorithms,namely,random forest,extreme gradient boosting,support vector machine and artificial neural network to predict fungal productivity.Model evaluation was conducted using a systematic methodology combining random,spatial and environmental blocking together with the assessment of the ecological consistency of spatially-explicit model predictions according to scientific knowledge.Results:Fungal productivity predictions were sensitive to the modeling approach and the number of predictors used.Moreover,the importance assigned to different predictors varied between machine learning modeling approaches.Decision tree-based models increased prediction accuracy by more than 10%compared to other machine learning approaches,and by more than 20%compared to statistical models,and resulted in higher ecological consistence of the predicted biogeographical patterns of fungal productivity.Conclusions:Decision tree-based models were the best approach for prediction both in sampling-like environments as well as in extrapolation beyond the spatial and climatic range of the modeling data.In this study,we show that proper variable selection is crucial to create robust models for extrapolation in biophysically differentiated areas.This allows for reducing the dimensions of the ecosystem space described by the p

关键词： Modeling Regression Biogeography Climate Forest Fungi Mushrooms

Magnetic resonance imaging findings of spontaneous pyomyoma in a premenopausal woman managed with myomectomy:A case report

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World journal of Radiology 2023年第3期15卷 83-88页

作者： David martínez Gustavo E Sanchez jhonatan Gómez Luis j Sonda Luis D Suárez Carlos S López juan j Vega Daniel A Cepeda Department of Radiology Hospital Christus MuguerzaPuebla 72501PueblaMexico Department of Radiology Hospital Regional Dr.Juan Graham CasasùsVillahermosa 86126TabascoMexico Department of Radiology Hospital de Especialidades 5 de MayoPuebla 72550PueblaMexico

BACKGROUnD Acute fibroid complications are rare.However,failure to recognize and treat acute complications expeditiously when they occur can lead to catastrophic,even deadly,complications.Pyomyoma is a rare but potentially fatal condition resulting from infarction and infection of a fibroid through bacterial seeding and direct,hematogenous,or lymphatic dissemination.Even though the diagnosis is established through clinical and laboratory findings,imaging is an important complementary method to support the suspected diagnosis.CASE SUMMARY Herein,we report a case of a pyomyoma in a nulliparous woman previously diagnosed with uterine leiomyomatosis according to ultrasound findings.The patient had previously attended the emergency room due to hypogastric pain unresponsive to analgesics.After a week of persistent pain,she developed sepsis without any identifiable foci.Magnetic resonance imaging revealed findings compatible with uterine myomatosis with red degeneration,and a possible diagnosis of a pyomyoma was made according to the imaging findings along with the patient’s clinical features.We decided to perform myomectomy(which is an infrequently performed surgical treatment due to the procedure’s intrinsic implic-ations)due to the patient’s desire to preserve fertility.Histopathologic results revealed a uterine leiomyoma with coagulative and liquefactive necrosis,while the tissue culture showed gram-negative cocci bacteria,which were successfully treated using antibiotic therapy.The patient’s health status improved after several days.COnCLUSIOn The main diagnostic tools to evaluate pyomyomas are the clinical and laboratory findings as well as tissue cultures.nonetheless,magnetic resonance imaging can help to corroborate these findings as well as to better characterize myomas with its different complications.

关键词： Diffusion-weighted images Apparent diffusion coefficient Leiomyoma Sepsis Magnetic resonance imaging Case report

Energy storage and relaxor behavior in(Pb_(0.8)Ba_(0.2))[(Zn_(1/3)nb_(2/3))_(0.7)Ti_(0.3)]O_(3)ferroelectric ceramic

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journal of Advanced Dielectrics 2023年第6期13卷 45-48页

作者： A.Pelaiz-Barranco Y.Perez-martín O.García-Zaldívar Y.Gagou Grupo de Materiales Ferroicos Facultad de Física-IMRE Universidad de la Habana.San Lazaroy LVedado.La Habana 10400Cuba LPMC Universite de Picardie Jules Verne 33 rue Saint-Leu80039 Amiens CedexFrance

(Pb_(0.8)Ba_(0.2))[(Zn_(1/3)nb_(2/3))_(0.7)Ti_(0.3)]O_(3)relaxor-type ferroelectric ceramics was obtained via classical solid-state reaction.The hysteresis loop results were discussed in the frame of ergodicity criterium around the characteristic ferroelectric relaxor freezing temperature.Slimer hysteresis loops were observed below the freezing temperature reflecting an ergodic relaxor behavior.Above this temperature,estimated around 223K for the studied system,larger and unsaturated like ferroelectric hysteresis loops were observed.This temperature also coincides with the slope change on maximum polarization and inflection point of remnant polarization curves.Energy storage,energy loss and efficiency values were determined in a wide temperature range.While the recoverable energy density shows relatively low values(0.23 j/cm^(3)),there are interesting behaviors for this parameter and for the efficiency,since the two physical quantities increase versus temperature and the efficiency even reaches the value of 97%.

关键词： Relaxors ferroelectrics energy storage freezing temperature

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

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Financial Innovation 2023年第1期9卷 2939-2991页

作者： Zhen‑Song Chen jia Zhou Chen‑Ye Zhu Zhu‑jun Wang Sheng‑Hua Xiong Rosa M.Rodríguez Luis martínez Mirosław j.Skibniewski School of Civil Engineering Wuhan UniversityWuhan 430072China College of Civil Aviation Safety Engineering Civil Aviation Flight University of ChinaGuanghan 618307China School of Management Xi’an Jiaotong UniversityXi’an 710049China Department of Computer Science University of Jaén23071 JaénSpain Department of Civil and Environmental Engineering University of MarylandCollege ParkMD 20742‑3021USA Institute for Theoretical and Applied Informatics Polish Academy of SciencesGliwicePoland Chaoyang University of Technology TaizhongTaiwan

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

关键词： Real estate enterprise Credit risk assessment PROMETHEE II Best–worst method Proportional hesitant fuzzy linguistic term sets

Hybrid heuristic and mathematical programming in oil pipelines networks: Use of immigrants

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journal of Zhejiang University-Science A(Applied Physics & Engineering) 2005年第1期6卷 9-19页

作者： DE LA CRUZ j.M HERRán-GOnZáLEZ A RISCO-martín j.L AnDRéS-TORO B Department of Computer Architecture and Automatic Control Complutense University of Madrid 28040 Madrid SpainDepartment of Computer Architecture and Automatic Control Complutense University of Madrid 28040 Madrid SpainDepartment of Computer Science Engineering C.E.S. Felipe II (U.C.M.) 28300 Aranjuez SpainDepartment of Computer Architecture and Automatic Control Complutense University of Madrid 28040 Madrid Spain

We solve the problem of petroleum products distribution through oil pipelines networks. This problem is modelled and solved using two techniques: A heuristic method like a multiobjective evolutionary algorithm and Mathematical Programming. In the multiobjective evolutionary algorithm, several objective functions are defined to express the goals of the solutions as well as the preferences among them. Some constraints are included as hard objective functions and some are evaluated through a repairing function to avoid infeasible solutions. In the Mathematical Programming approach the multiobjective optimization is solved using the Constraint Method in Mixed Integer Linear Programming. Some constraints of the mathematical model are nonlinear, so they are linearized. The results obtained with both methods for one concrete network are presented. They are compared with a hybrid solution, where we use the results obtained by Mathematical Programming as the seed of the evolutionary algorithm.

关键词：石油输送石油管道数学模型程序设计

Analysis of the factors affecting LiDAR DTM accuracy in a steep shrub area

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International journal of Digital Earth 2011年第6期4卷 521-538页

作者： j.Estornell L.A.Ruiz B.Vela´zquez-martı´ T.Hermosilla Departamento de Ingenierı´a Cartogra´fica Geodesia y Fotogrametrı´aUniversidad Polite´cnica de ValenciaCamino de Vera s/nValencia 46022Spain Departamento de Ingenierı´a Rural y Agroalimentaria Universidad Polite´cnica de ValenciaValenciaSpain

The creation of a quality Digital Terrain Model(DTM)is essential for representing and analyzing the Earth in a digital form.The continuous improvements in the acquisition and the potential of airborne Light Detection and Ranging(LiDAR)data are increasing the range of applications of this technique to the study of the Earth surface.The aim of this study was to determine the optimal parameters for calculating a DTM by using an iterative algorithm to select minimum elevations from LiDAR data in a steep mountain area with shrub vegetation.The parameters were:input data type,analysis window size,and height thresholds.The effects of slope,point density,and vegetation on DTM accuracy were also analyzed.The results showed that the lowest root mean square error(RMSE)was obtained with an analysis window size of 10 m,5 m,and 2.5 m,rasterized data as input data,and height thresholds equal to or greater than 1.5 m.These parameters showed a RMSE of 0.19 m.When terrain slope varied from 010%to 5060%,the RMSE increased by 0.11 m.The RMSE decreased by 0.06 m when point density was increased from 4 to 8 points/m2,and increased by 0.05 m in dense vegetation areas.

关键词： LiDAR digital earth Digital Terrain Model(DTM) filtering 3-D representation

Stochastic simulation of successive waves of COVID-19 in the province of Barcelona

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Infectious Disease Modelling 2023年第1期8卷 145-158页

作者： M.Bosman A.Esteve L.Gabbanelli X.jordan A.Lòpez-Gay M.Manera M.martínez P.Masjuan Ll.M.Mir j.Paradells A.Pignatelli I.Riu V.Vitagliano Institut de Física d’Altes Energies(IFAE) The Barcelona Institute of Science and TechnologyBarcelonaSpain Centre d’Estudis Demogrèfics(CED-CERCA) BarcelonaSpain Serra Húnter Fellow Departament de Ciències Polítiques i SocialsUniversitat Pompeu FabraBarcelonaSpain i2CAT Foundation Edifici Nexus(Campus Nord UPC)BarcelonaSpain Departament de Geografia Universitat Autónoma de BarcelonaBellaterraSpain Serra Húnter Fellow Departament de FísicaUniversitat Autònoma de BarcelonaBellaterraSpain InstitucióCatalana de Recerca i Estudis Avançats(ICREA) BarcelonaSpain Departament de Física Universitat Autónoma de BarcelonaBellaterraSpain Departament d’Enginyeria Telemàtica Universitat Politècnica de CatalunyaBarcelonaSpain DIME University of GenovaVia all’Opera Pia 1516145GenovaItaly InFn Sezione di Genovavia Dodecaneso 3316146GenoaItaly Department of Mathematics and Physics University of HullKingston upon HullHU67RXUK

Analytic compartmental models are currently used in mathematical epidemiology to forecast the COVID-19 pandemic evolution and explore the impact of mitigation strategies.In general,such models treat the population as a single entity,losing the social,cultural and economical specificities.We present a network model that uses socio-demographic datasets with the highest available granularity to predict the spread of COVID-19 in the province of Barcelona.The model is flexible enough to incorporate the effect of containment policies,such as lockdowns or the use of protective masks,and can be easily adapted to future epidemics.We follow a stochastic approach that combines a compartmental model with detailed individual microdata from the population census,including social determinants and age-dependent strata,and time-dependent mobility information.We show that our model reproduces the dynamical features of the disease across two waves and demonstrates its capability to become a powerful tool for simulating epidemic events.

关键词： COVID-19 modelling Parameter estimation Socio-demographic data Intervention

Application of a new reagent for analysis of oxygen presence in a lowcarbon steel wire rod

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journal of Iron and Steel Research(International) 2021年第6期28卷 729-738页

作者： M.I.Dávila-Pérez H.j.Vergara-Hernández O.Vázquez-Gómez F.Reyes-Calderón E.López-martínez j.M.Salgado-López national Technology of Mexico/T.I.of Morelia Morelia 58120MichoacanMexico national Council for Science and Technology COnACYT Mexico City 03940Mexico Isthmus University Santo Domingo TehuantepecOaxaca 70760Mexico Engineering and Industrial Development Center CIDESI Santiago de Queretaro 76125QueretaroMexico

A microstructural analysis was performed to determine the presence of oxygen in a wire rod section of AISI 1008 steel with a surface mechanical failure produced during wire drawing.The failure zone was analyzed by comparison using three different attack reagents:alkaline sodium chromate(ASC),ASC with hydrogen peroxide and amyl alcohol,and a solution of nitric acid in ethyl alcohol.The reagents were applied in samples in the failure zone,showing different types of zones in regions with internal and superficial defects such as carbides,pores,cracks,deformation,and detachment zones,indicating the possible presence of oxygen.The areas identified were observed by means of an optical microscope and were correlated with the content of elements that were present in the region using a scanning electron microscope and a scattered X-ray energy spectrometer,which determined that the areas identified by chromate sodium correspond to regions with a high concentration of oxygen and slag-forming elements such as silicon,aluminum,and iron;this is associated with the presence of oxygen in the oxide form.It was also observed that the ASC and the modified ASC solution with hydrogen peroxide and amyl alcohol could identify areas with a high presence of oxides,while the nitric acid solution only identified the steel microstructure.The modified ASC solution is an alternative to identify the presence of chemical variants of oxygen because the conventional formulation is unstable and has a too short shelf life,and therefore,its application must be carried out at the time of preparation.

关键词： Etching Alkaline sodium chromate Oxide presence Internal defect

Dissecting the molecular pathophysiology of drug-induced liver injury

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World journal of Gastroenterology 2018年第13期24卷 1373-1385页

作者： Hui Ye Leonard j nelson Manuel Gómez del Moral Eduardo martínez-naves Francisco javier Cubero Department of Immunology Ophtalmology and ORLComplutense University School of MedicineMadrid 28040Spain 12 de Octubre Health Research Institute(imas12) Madrid 28041Spain Institute for BioEngineering(Human Liver Tissue Engineering Faraday BuildingThe University of EdinburghThe King BuildingsMayfield RoadEdinburgh EH9 3 JLScotlandUnited Kingdom Department of Cell Biology Complutense University School of MedicineMadrid 28040Spain

Drug-induced liver injury(DILI) has become a major topic in the field of Hepatology and Gastroenterology. DILI can be clinically divided into three phenotypes: hepatocytic, cholestatic and mixed. Although the clinical manifestations of DILI are variable and the pathogenesis complicated, recent insights using improved preclinical models, have allowed a better understanding of the mechanisms that trigger liver damage. In this review, we will discuss the pathophysiological mechanisms underlying DILI. The toxicity of the drug eventually induces hepatocellular damage through multiple molecular pathways, including direct hepatic toxicity and innate and adaptive immune responses. Drugs or their metabolites, such as the common analgesic, acetaminophen, can cause direct hepatic toxicity through accumulation of reactive oxygen species and mitochondrial dysfunction. The innate and adaptive immune responses play also a very important role in the occurrence of idiosyncratic DILI. Furthermore, we examine common forms of hepatocyte death and their association with the activation of specific signaling pathways.

关键词： signaling pathways acetaminophen Drug-induced liver injury cell death reactive oxygen species