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1.
Comput Math Methods Med ; 2019: 9163547, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30774706

RESUMO

Sex determination from skeletons is a significant step in the analysis of forensic anthropology. Previous skeletal sex assessments were analyzed by anthropologists' subjective vision and sexually dimorphic features. In this paper, we proposed an improved backpropagation neural network (BPNN) to determine gender from skull. It adds the momentum term to improve the convergence speed and avoids falling into local minimum. The regularization operator is used to ensure the stability of the algorithm, and the Adaboost integration algorithm is used to improve the generalization ability of the model. 267 skulls were used in the experiment, of which 153 were females and 114 were males. Six characteristics of the skull measured by computer-aided measurement are used as the network inputs. There are two structures of BPNN for experiment, namely, [6; 6; 2] and [6; 12; 2], of which the [6; 12; 2] model has better average accuracy. While η = 0.5 and α = 0.9, the classification accuracy is the best. The accuracy rate of the training stage is 97.232%, and the mean squared error (MSE) is 0.01; the accuracy rate of the testing stage is 96.764%, and the MSE is 1.016. Compared with traditional methods, it has stronger learning ability, faster convergence speed, and higher classification accuracy.


Assuntos
Determinação do Sexo pelo Esqueleto/métodos , Crânio/anatomia & histologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Cefalometria/métodos , Cefalometria/estatística & dados numéricos , Análise Discriminante , Feminino , Antropologia Forense/métodos , Antropologia Forense/estatística & dados numéricos , Humanos , Imageamento Tridimensional , Masculino , Pessoa de Meia-Idade , Modelos Anatômicos , Redes Neurais de Computação , Caracteres Sexuais , Determinação do Sexo pelo Esqueleto/estatística & dados numéricos , Crânio/diagnóstico por imagem , Tomografia Computadorizada por Raios X , Adulto Jovem
2.
Sensors (Basel) ; 8(9): 5649-5660, 2008 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-27873834

RESUMO

An electrochemical DNA biosensor for the detection of NOS gene sequences from genetically modified organisms (GMOs) is presented in this paper. Single-stranded DNA (ssDNA) was covalently attached through the carboxylate ester formed by the 3'- hydroxy end of the DNA with the carboxyl of a mercaptoacetic acid self-assembled monolayer-modified gold electrode using N-hydroxysuccinimide (NHS) and N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC) as linkers. The electrochemical behavior of methylene blue (MB) on the ssDNA and dsDNA modified gold electrode were carefully studied. Compared with ssDNA/Au electrode, an increase of redox peak current of MB on dsDNA/Au electrode was found, which could be further used for monitoring the recognition of DNA hybridization. Based on this result, the polymerase chain reaction (PCR) product of the common inserts NOS terminator from real GMOs samples was detected successfully.

3.
Chinese Journal of School Health ; (12): 1863-1866, 2021.
Artigo em Chinês | WPRIM | ID: wpr-907079

RESUMO

Objective@#To monitor and analyze the epidemiological characteristics of influenza in schools and understand the disease burden of students, and to provide a scientific reference for instructing the prevention of influenza in schools.@*Methods@#A school influenza surveillance sentinel to conduct influenza like case (ILI) surveillance and outbreak surveillance. Through network, we understood the burden of flu disease among students. Descriptive epidemiology was used to analyze influenza like case surveillance and questionnaire survey data.@*Results@#Surveillance confirmed that from the 42th week of 2019 to the 1st week of 2020, the cumulative reported ILI of 3 school influenza surveillance sites in Jinan accounted for 7.91% (ILI%) of the total number of surveillance personnel during the same period, with the highest ILI% (24.19%) of kindergarten children, ILI% gradually decreased with the increase of grade, and teachers were the lowest. The reporting of ILI was concentrated in the 49th to 52nd week of 2019, during which the reported influenza like cases accounted for 84.81% of the total number of ILI reported during the surveillance period. Two influenza outbreaks were monitored. The pathogens were H3N2 and B (Victoria). The epidemics mainly occurred in the lower grades of elementary school. A survey of 2 297 students found that 577 people had fever and respiratory symptoms since October 2019. Among them, 85.26% of them went to the hospital, 32.75% of those who used anti influenza drugs such as oseltamivir, and 64.81% of those who used antibiotics. 42.63% received infusion therapy, 3.99% were hospitalized, and the average cost of inpatients was 6 686 yuan. The sick students were absent from school for an average of 3.77 days, and the parents of the sick children missed work for an average of 4.26 days.@*Conclusion@#Surveillance of influenza like cases in schools is an important way to proactively discover influenza epidemic trends and outbreaks, and to accurately grasp the characteristics of influenza epidemics in schools. The key populations affected by influenza are kindergarten children and lower grades of primary school students. Suffering from influenza has caused a heavy disease burden on students and children in kindergartens, and is also an important factor that causes student absenteeism and parents to miss work.

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