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Synthesis of coral-like structures of Pr-Yb co-doped YIG: Structural,optical, magnetic and antimicrobial properties

Journal of Rare Earths 2024年第3期42卷 543-554,I0004页

作者： A.Fernandez Francisca P.Araujo Y.Guerra S.Castro-Lopes J.Matilla-Arias Idglan S.de Lima Edson C.Silva-Filho Josy A.Osajima F.Guerrero R.Pena-Garcia federal university of Piau Graduate Program in Materials Science and EngineeringTeresinaPIBrazil federal Rural university of Pernambuco Academic Unit of Cabo de Santo AgostinhoCabo de Santo AgostinhoPEBrazil federal university of Piaui Department of PhysicTeresinaPBrazil federal university of Pernambuco Graduate Program in Materials ScienceRecifePEBrazil university of Granma Departmentof Basic Sciences and Applied InformaticsFaculty of Technical SciencesBayamoCuba federal university of Amazonas Department of PhysicManausAMBrazil federal university of Pernambuco Department of PhysicRecifePEBrazil

Coral-like structures of the Y_(3-x)Pr_(x)Fe_(5-y)Yb_(y)O_(12),(0.00 ≤ x ≤ 0.04, 0.00 ≤ y ≤ 0.02) compound were synthesized using the sol-gel method. Structural investigation certified the YIG cubic crystal structure formation, without any secondary phase. It is shown that, the relatively large ionic radius of the dopant cations results in an expansion of the lattice parameter, variations in the Iona-O-Iondangle, Iona-O,Iond-O and Ionc-O bond distances and decrease in the average crystallite size. Fourier transform infrared(FTIR) and Raman measurements are essential to testify the single-phase formation of YIG crystal structure and are observed changes in the stretching and vibrational modes, respectively. The morphological study, energy dispersive spectroscopy(EDS) spectra and textural properties show corallike structures, peaks associated with Pr^(3+) and Yb^(3+) atoms and the effect of dopants on surface area,diameter, and pore volume, respectively. The optical analysis from diffuse reflectance spectra witnessed an increase in the optical gap band, a decrease in Urbach energy and blue shift in the charge transfer,correlated with the expansion of the unit cell due to the dopant's insertion in the YIG structure. A typical ferrimagnetic behavior is exhibited by the Y_(3-x)Pr_(x)Fe_(5-y)Yb_(y)O_(12)compound. The saturation magnetization(M_(s)), cubic anisotropy constant(K_(1)) and coercive field(H_(c)) increase with the Pr^(3+)cations content, as consequence of their magnetic nature and distribution around of Fe^(3+)ions due to the coexistence with the Yb^(3+). Finally, for the first time, antibacterial tests by mean of the direct contact method were performed for YIG co-doped with Pr^(3+)and Yb^(3+)and it is shown that, relatively high dosages of Pr^(3+) cations favored the activity against S. aureus, therefore, a new biological property for YIG doped with rare earths is presented.

关键词： Yttrium iron garnet(YIG) Coral-like structures Rare earths Band gap energy Magnetic properties Antimicrobial properties

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Designing for well-Being: Using facial micro-expression analysis and EEG biosensor to evaluate human responses to 2D biophilically-driven geometries

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Frontiers of Architectural Research 2024年第2期13卷 219-234页

作者： Andrea Macruz Ernesto Bueno Gustavo Sol Jaime Vega Ricardo Palmieri Bing Zhao College of Architecture and Urban Planning Tongji UniversityShanghaiChina Universidade Presbiteriana Mackenzie Sao PauloBrazil Centro Universitario Belas Artes Sao PauloBrazil Universidade Anhembi Morumbi Sao PauloBrazil Universidade federal do ABC Santo AndreBrazil

This research explores the capacity of emerging technologies to enhance well-being. It involves the generation of 2D biophilically-driven geometries to represent human-response-oriented built environments and conducts inter and intra-individual analyses to assess human responses using a range of technologies within the realms of facial micro-expression analysis and EEG biosensor use. The outcomes of this analysis allow for the grading of these geometries in terms of emotional valences, meditation levels, and subjective preferences. These graded geometries can subsequently be employed in specific architectural contexts, such as interior decor, wallpapers, furniture surfaces, or other architectural and interior components. It is an interdisciplinary effort that underscores the importance of incorporating emerging technological means with human-response-oriented design approaches to foster built environments that promote well-being.

关键词： Biophilic design Geometrical algorithmicmodeling Facial micro-expressionanalysis EEG biosensor Neuroscience

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Importance of complementary data to histopathological image analysis of oral leukoplakia and carcinoma using deep neural networks

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Intelligent Medicine 2023年第4期3卷 258-266页

作者： Leandro Muniz de Lima Maria Clara Falcão Ribeiro de Assis Júlia Pessini Soares Tânia Regina Grão-Velloso Liliana Aparecida Pimenta de Barros Danielle Resende Camisasca Renato Antonio Krohling Nature-inspired Computing Lab Federal University of Espirito SantoVitoriaBrazil Graduate Program in Computer Science Federal University of Espirito SantoVitoriaBrazil School of Dentistry Departamento de Clinica OdontologicaFederal University of Espirito SantoVitoriaBrazil Graduate Program in Clinical Dentistry Federal University of Espirito SantoVitoriaBrazil

Background Oral cancer is one of the most common types of cancer in men causing mortality if not diagnosedearly.In recent years,computer-aided diagnosis(CAD)using artificial intelligence techniques,in particular,deepneural networks have been investigated and several approaches have been proposed to deal with the automateddetection of various pathologies using digital images.Recent studies indicate that the fusion of images with thepatient’s clinical information is important for the final clinical diagnosis.As such dataset does not yet exist fororal cancer,as far as the authors are aware,a new dataset was collected consisting of histopathological images,demographic and clinical data.This study evaluated the importance of complementary data to histopathologicalimage analysis of oral leukoplakia and carcinoma for CAD.Methods A new dataset(NDB-UFES)was collected from 2011 to 2021 consisting of histopathological imagesand information.The 237 samples were curated and analyzed by oral pathologists generating the gold standardfor classification.State-of-the-art image fusion architectures and complementary data(Concatenation,MutualAttention,MetaBlock and MetaNet)using the latest deep learning backbones were investigated for 4 distincttasks to identify oral squamous cell carcinoma,leukoplakia with dysplasia and leukoplakia without dysplasia.We evaluate them using balanced accuracy,precision,recall and area under the ROC curve metrics.Results Experimental results indicate that the best models present balanced accuracy of 83.24%using images,demographic and clinical information with MetaBlock fusion and ResNetV2 backbone.It represents an improvement in performance of 30.68%(19.54 pp)in the task to differentiate samples diagnosed with oral squamous cellcarcinoma and leukoplakia with or without dysplasia.Conclusion This study indicates that cured demographic and clinical data may positively influence the performance of artificial intelligence models in automated classification of oral cancer.

关键词： Leukoplakia Squamous carcinoma Pathology Deep learning Transfer learning

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Molecular mechanisms underlying the neuroprotection of environmental enrichment in Parkinson’s disease

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Neural Regeneration Research 2023年第7期18卷 1450-1456页

作者： Tamara Andrea Alarcón Sarah Martins Presti-Silva Ana Paula Toniato Simões Fabiola Mara Ribeiro Rita Gomes Wanderley Pires Department of Physiological Sciences Health Science CenterUniversidade Federal do Espirito SantoVitoriaBrazil Laboratory of Molecular and Behavioral Neurobiology Health Science CenterUniversidade Federal do Espirito SantoVitoriaBrazil Department of Biochemistry and Immunology Institute o Biological SciencesUniversidade Federal de Minas GeraisAvenida Antônio CarlosBelo HorizonteBrazil

Parkinson’s disease is the most common movement disorder,affecting about 1%of the population over the age of 60 years.Parkinson’s disease is characterized clinically by resting tremor,bradykinesia,rigidity and postural instability,as a result of the progressive loss of nigrostriatal dopaminergic neurons.In addition to this neuronal cell loss,Parkinson’s disease is characterized by the accumulation of intracellular protein aggregates,Lewy bodies and Lewy neurites,composed primarily of the proteinα-synuclein.Although it was first described almost 200 years ago,there are no disease-modifying drugs to treat patients with Parkinson’s disease.In addition to conventional therapies,non-pharmacological treatment strategies are under investigation in patients and animal models of neurodegenerative disorders.Among such strategies,environmental enrichment,comprising physical exercise,cognitive stimulus,and social interactions,has been assessed in preclinical models of Parkinson’s disease.Environmental enrichment can cause structural and functional changes in the brain and promote neurogenesis and dendritic growth by modifying gene expression,enhancing the expression of neurotrophic factors and modulating neurotransmission.In this review article,we focus on the current knowledge about the molecular mechanisms underlying environmental enrichment neuroprotection in Parkinson’s disease,highlighting its influence on the dopaminergic,cholinergic,glutamatergic and GABAergic systems,as well as the involvement of neurotrophic factors.We describe experimental pre-clinical data showing how environmental enrichment can act as a modulator in a neurochemical and behavioral context in different animal models of Parkinson’s disease,highlighting the potential of environmental enrichment as an additional strategy in the management and prevention of this complex disease.

关键词： acetylcholine brain-derived neurotrophic factor dopamine environment enrichment gamma-aminobutyric acid glial cell line-derived neurotrophic factor glutamate molecular mechanisms Parkinson’s disease

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Few-shot learning for biotic stress classification of coffee leaves

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Artificial Intelligence in Agriculture 2022年第1期6卷 55-67页

作者： Lucas M.Tassis Renato A.Krohling LABCIN-Nature Inspired Computing Lab Federal University of Espirito SantoAv.Fernando Ferrari514CEP29075-910 VitóriaEspırito SantoESBrazil PPGI-Graduate Program in Computer Science Federal University of Espirito SantoAv.Fernando Ferrari514CEP 29075-910VitóriaEspírito SantoESBrazil

In the last few years,deep neural networks have achieved promising results in several fields.However,one of the main limitations of these methods is the need for large-scale datasets to properly generalize.Few-shot learning methods emerged as an attempt to solve this shortcoming.Among the few-shot learning methods,there is a class of methods known as embedding learning or metric learning.These methods tackle the classification problem by learning to compare,needing fewer training data.One of the main problems in plant diseases and pests recognition is the lack of large public datasets available.Due to this difficulty,the field emerges as an intriguing application to evaluate the few-shot learning methods.The field is also relevant due to the social and economic importance of agriculture in several countries.In this work,datasets consisting of biotic stresses in coffee leaves are used as a case study to evaluate the performance of few-shot learning in classification and severity estimation tasks.We achieved competitive results compared with the ones reported in the literature in the classification task,with accuracy values close to 96%.Furthermore,we achieved superior results in the severity estimation task,obtaining 6.74%greater accuracy than the baseline.

关键词： Plant diseases and pests classification Image classification Few-shot learning Meta-learning Convolutional neural networks

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Apparent soil electrical conductivity in the delineation of management zones for cocoa cultivation

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Information Processing in Agriculture 2022年第3期9卷 443-455页

作者： Samuel de Assis Silva Railton Oliveira dos santos Daniel Marcal de Queiroz Juliao Soares de Souza Lima Levi Fraga Pajehua Caique Carvalho Medauar Center for Agricultural Sciences and Engineering Federal University of Espirito SantoAlegre CampusEspirito Santo 29500-000Brazil Department of Agricultural Sciences Santa Cruz State UniversityIlheusBahia 45662-900Brazil Department of Agricultural Engineering Federal University of Vic¸osaVic¸osaMinas Gerais 36570-900Brazil

Apparent electrical conductivity is an important parameter for describing the spatial vari-ability of physical and chemical attributes of the soil and for the delineation of manage-ment zones.The objective of this work is to outline management zones for the cocoa cultivation based on the spatial variability of the productivity and the apparent electrical conductivity(ECa)of the soil.Data collection was performed in a regular sample grid con-taining 120 points in an area cultivated with cocoa trees,located in the municipality of Ilhe´us,state of Bahia,Brazil.At each sampling point(cocoa tree),soil samples were col-lected to determine chemical attributes.Productivity was measured for one year,counting,monthly,the number of fruits,which were classified into off-season cocoa,harvest and annual production.Measurements of the apparent electrical conductivity of the soil were performed at different times of the year using a portable conductivity meter.The data were analyzed using classical statistics and geostatistics.The management zones were delin-eated using the fuzzy k-means algorithm.The ideal number of class was defined using the fuzziness performance index(FPI)and the entropy of the modified partition(MPE)indexes.The Kappa coefficient was used to validate the management zones,assessing their agreement with the chemical attributes of the soil.The ECa of the soil values pre-sented moderate temporal variation,with maximum amplitude of 19.37 mS m1 and min-imum of 0.82 mS m1 between measurement periods;higher averages of the ECa coincided with the highest levels of water in the soil.The measurements of the ECa of the soil carried out in April and October showed greater correlation with the chemical attributes of the soil,with significant values for 11 and 8 of the 17 attributes evaluated,respectively.The man-agement zones from the ECa measured in April showed:a)reduced number of classes;b)spatial continuity between classes,and;c)agreement from reasonable(kappa between 0.20 and 0.40)to good(kappa>0.41)with most of th

关键词： Theobroma cacao Precision agriculture Spatial variability Fuzzy k-means

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An app to assist farmers in the identification of diseases and pests of coffee leaves using deep learning

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Information Processing in Agriculture 2022年第1期9卷 38-47页

作者： Jose G.M.Esgario Pedro B.C.de Castro Lucas M.Tassis Renato A.Krohling LABCIN-Nature Inspired Computing Federal University of Espirito SantoAv.Fernando Ferrari514CEP 29075-910 VitoriaEspırito SantoESBrazil LABCIN-Nature Inspired Computing and PPGI-Graduate Program in Computer Scienceand Production Engineering DepartmentFederal University of Espirito SantoAv.Fernando Ferrari514CEP 29075-910 VitoriaEspırito SantoESBrazil

In recent years,deep learning methods have been introduced for segmentation and classi-fication of leaf lesions caused by pests and pathogens.Among the commonly used approaches,convolutional neural networks have provided results with high accuracy.The purpose of this work is to present an effective and practical system capable of seg-menting and classifying different types of leaf lesions and estimating the severity of stress caused by biotic agents in coffee leaves using convolutional neural networks.The proposed approach consists of two stages:a semantic segmentation stage with severity calculation and a symptom lesion classification stage.Each stage was tested separately,highlighting the positive and negative points of each one.We obtained very good results for the severity estimation,suggesting that the model can estimate severity values very close to the real values.For the biotic stress classification,the accuracy rates were greater than 97%.Due to the promising results obtained,an App for Android platform was developed and imple-mented,consisting of semantic segmentation and severity calculation,as well as symptom classification to assist both specialists and farmers to identify and quantify biotic stresses using images of coffee leaves acquired by smartphone.

关键词： Convolutional neural networks Semantic segmentation Coffee leaf Pests and diseases App.development

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TODIM and TOPSIS with Z-numbers

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Frontiers of Information Technology & Electronic Engineering 2019年第2期20卷 283-291页

作者： Renato A.KROHLING André G.C.PACHECO Guilherme A.dos santoS Department of Production Engineering Federal University of Espirito Santo Graduate Program in Computer Science Federal University of Espirito Santo

In this paper, we present an approach that can handle Z-numbers in the context of multi-criteria decision-making problems. The concept of Z-number as an ordered pair Z=(A, B) of fuzzy numbers A and B is used, where A is a linguistic value of a variable of interest and B is a linguistic value of the probability measure of A. As human beings, we communicate with each other by means of natural language using sentences like "the journey from home to university most likely takes about half an hour." The Z-numbers are converted to fuzzy numbers. Then the Z-TODIM and Z-TOPSIS are presented as a direct extension of the fuzzy TODIM and fuzzy TOPSIS, respectively. The proposed methods are applied to two case studies and compared with the standard approach using crisp values. The results obtained show the feasibility of the approach.

关键词： Multi-criteria decision-making TODIM TOPSIS Fuzzy number Z-number

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Arlenea delicata gen.et sp.nov.,a new ephedroid plant from the Early Cretaceous Crato Formation,Araripe Basin,Northeast Brazil

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Plant Diversity 2024年第3期46卷 362-371页

作者： Alita Maria Neves Ribeiro Yong Yang Antonio Alamo Feitosa Saraiva Renan Alfredo Machado Bantim Joao Tavares Calixto Junior Flaviana Jorge de Lima Programa de Pos-Graduaçao em Diversidade Biologica e Recursos Naturais Universidade Regional do CaririRua Carolino SucupiraPimenta63105-160CratoCearaBrazil Co-Innovation Center for Sustainable Forestry in Southern China College of Biology and the Environment159 Longpan RoadNanjing Forestry UniversityNanjing210037China Laboratorio de Paleontologia Universidade Regional do CaririRua Carolino SucupiraPimenta63105-160CratoCearaBrazil Laboratorio de Estudos da Flora Regional Universidade Regional do CaririRua Carolino SucupiraPimenta63105-160CratoCearaBrazil Gondwanan Plants Lab Universidade Federal de PernambucoCentro Academico de VitoriaRua Do Alto Reservatorio S/nBela Vista55608-680Vitoria de Santo AntaoPernambucoBrazil Programa de Pos-Graduaçao em Geociencias(PPGEOC) Universidade Federal de Pernambuco(UFPE)Rua Av.da ArquiteturaS/n°CEP-50740-550Cidade UniversitariaRecifePernambucoBrazil

Ephedroid macrofossils have been widely documented in Cretaceous deposits,including numerous from the Lower Cretaceous Yixian Formation of NE China.However,few ephedroid macrofossils have been reported from South America.Herein,we describe a new plant of the family Ephedraceae,Arlenea delicata gen.et sp.nov.,from the Lower Cretaceous Crato Formation of the Araripe Basin,Northeast Brazil,based on the vegetative and reproductive structures.It has the typical morphological characteristics of ephedroid plants,including fertile reproductive branches,opposite phyllotaxy,terminal female cones,a sympodial branching system,longitudinally striated internodes,and swollen nodes.Our new finding is unusual in having inner chlamydosperms subtended by two pairs of bracts,reproductive units connected to branches through swollen receptacles and a smooth seed surface.This new ephedroid taxon from the Crato Formation increases our understanding of plant diversity of this group during the Early Cretaceous.Furthermore,the general morphology(fleshy bracts and enlarged receptacles)of this new fossil discovery indicates that seeds of this plant may have been dispersed by animals such as pterosaurs(mainly the Tapejaridae)and birds(Enantiornithes and Ornituromorpha).If true,this would explain the cosmopolitan distribution of Ephedraceae in the Lower Cretaceous.

关键词： Early Cretaceous Gnetophytes Arlenea delicata Ephedrales Crato Formation

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Settlement predictions of footings on sands using probabilisticanalysis

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Journal of Rock Mechanics and Geotechnical Engineering 2016年第2期8卷 198-203页

作者： felipe carvalho bungenstab kátia vanessa bicalho federal university of espirito santo VitóriaBrazil

The design of footings on sands is often controlled by settlement rather than bearing capacity.Therefore,settlement predictions are essential in the design of shallow foundations.However,predicted settlements of footings are highly dependent on the chosen elastic modulus and the used method.This paper presents the use of probabilistic analysis to evaluate the variability of predicted settlements of footings on sands,focusing on the load curve(predicted settlements)characterization.Three methodologies,the first-and second-order second-moment(FOSM and SOSM),and Monte Carlo simulation(MCS),for calculating the mean and variance of the estimated settlements through Schmertmann(1970)’s equation,are presented and discussed.The soil beneath the footing is treated as an uncorrelated layered material,so the total settlement and variance are found by adding up the increments of the layers.The deformability modulus(ESi)is considered as the only independent random variable.As an example of application,a hypothetical case of a typical subsoil in the state of espirito santo,southeast of Brazil,is evaluated.The results indicate that there is a significant similarity between the SOSM and MCS methods,while the FOSM method underestimates the results due to the non-consideration of the high-order terms in Taylor’s series.The contribution of the knowledge of the uncertainties in settlement prediction can provide a safer design.

关键词： Footings Settlements Probabilities Deformability modulus

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