Hábitos posturais domiciliares e dor lombar e cervical entre adolescentes de uma escola pública de ensino médio do Rio de Janeiro

A prevalência de dor lombar e cervical na adolescência é tão elevada quanto nos adultos e seu início, na adolescência, aumenta o risco de desenvolver dor crônica na vida adulta. Existem poucos estudos que tenham investigado como são os hábitos posturais dos adolescentes durante o tempo que estão em atividades passivas em casa e se esses hábitos estão associados à dor lombar e à dor cervical. Objetivo: Investigar a prevalência de dor lombar (DL) e de dor cervical (DC) em adolescentes e suas associações com hábitos posturais domiciliares enquanto estão assistindo a TV e/ou usando o computador. Métodos: Estudo transversal com adolescentes de uma escola pública de ensino médio do Rio de Janeiro. Os estudantes responderam questões relativas a variáveis sociodemográficas, ao estilo de vida, aos hábitos posturais (ilustrações), ao tempo assistindo a TV, ao tempo usando o computador, ao tempo usando o videogame e sobre a presença da DL e da DC. Foi utilizada regressão logística multivariada para analisar a associação entre hábitos posturais domiciliares e dor lombar e cervical. Resultados: Foram 1102 participantes. A prevalência de DL foi de 46,8% (18,2% dor lombar crônica [DLC] e 28,6% dor lombar aguda [DLA]. A prevalência de dor cervical aguda (DCA) foi de 32,9%. Posturas slump (excessivamente relaxadas) ao assistir a TV e ao usar o computador de mesa estiveram associadas com DLC (RC [razão de chances] 3,22, IC 95% 1,38 7,5 e RC 1,7, IC 95% 1,06 2,73). Participantes que assistiam a TV sentados na cama tiveram uma RC de 2,14 (IC 95% 1,06 4,32) para DLA e os que usavam o notebook em decúbito ventral na cama tiveram uma RC de 2,26 (IC 95% 1,02 5,01) para DLA. Os participantes que assistiam a TV em decúbito dorsal por 2 horas ou mais tiveram uma RC de 6,21 (IC 95% 1,45 26,52) para DCA. Aqueles que disseram que mudavam de postura com frequência, ao usar o computador de mesa por 2 horas ou mais, tiveram uma RC de 0,34 (IC 95% 0,14 0,85) para DCA. Conclusão: Os nossos achados apoiam a elevada prevalência de DL e de DC na adolescência e adicionam a associação com os hábitos posturais domiciliares.

Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation.

The human cervix is an important mechanical barrier in pregnancy which must withstand the compressive and tensile forces generated from the growing fetus. Premature cervical shortening resulting from premature cervical remodeling and alterations of cervical material properties are known to increase a woman׳s risk of preterm birth (PTB). To understand the mechanical role of the cervix during pregnancy and to potentially develop indentation techniques for in vivo diagnostics to identify women who are at risk for premature cervical remodeling and thus preterm birth, we developed a spherical indentation technique to measure the time-dependent material properties of human cervical tissue taken from patients undergoing hysterectomy. In this study we present an inverse finite element analysis (IFEA) that optimizes material parameters of a viscoelastic material model to fit the stress-relaxation response of excised tissue slices to spherical indentation. Here we detail our IFEA methodology, report compressive viscoelastic material parameters for cervical tissue slices from nonpregnant (NP) and pregnant (PG) hysterectomy patients, and report slice-by-slice data for whole cervical tissue specimens. The material parameters reported here for human cervical tissue can be used to model the compressive time-dependent behavior of the tissue within a small strain regime of 25%.

Application of ICA in on-line verification of the phase difference of the current sensor

The performance of the current sensor in power equipment may become worse affected by the environment. In this paper, based on ICA, we propose a method for on-line verification of the phase difference of the current sensor. However, not all source components are mutually independent in our application. In order to get an exact result, we have proposed a relative likelihood index to choose an optimal result from different runs. The index is based on the maximum likelihood evaluation theory and the independent subspace analysis. The feasibility of our method has been confirmed by experimental results.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

Application of ICA in on-line verification of the phase difference of the current sensor

The performance of the current sensor in power equipment may become worse affected by the environment. In this paper, based on ICA, we propose a method for on-line verification of the phase difference of the current sensor. However, not all source components are mutually independent in our application. In order to get an exact result, we have proposed a relative likelihood index to choose an optimal result from different runs. The index is based on the maximum likelihood evaluation theory and the independent subspace analysis. The feasibility of our method has been confirmed by experimental results.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

核ICA在电流传感器相位差监测中的应用

介绍了核独立分量分析（ICA）的基本原理和算法，并将其用于对电流传感器输出的混合信号进行分离，通过比较分离出的单频测试信号输入前后的相位差，来标定传感器本身的相位差对其检测对象的影响。此外，还采用最大似然法对核ICA的分离效果进行评价。实验证明

基于ICA和BP网络的电流传感器相位差测量方法

提出了一种高精度在线测定电流传感器相位差的方法.在输入端加入测试信号,在输出端采用独立分量分析(ICA)将该测试信号与传感器正常工作的输出信号分离,通过比较该测试信号输出前后相位的变化确定传感器的相位差.但因ICA算法固有的局限性,同一混合信号每次分离结果误差不同,为了提高分离精度,利用BP网络学习分离结果中相位误差与最大似然指标和负熵的关系,提出了一个指示分离结果误差的评价量,以选取多次分离结果中的最优结果.实验结果证明该评价量的有效性.

基于仿生模式识别和PCA/ICA的DOA估计方法

本文提出了一种基于仿生模式识别和PCA/ICA的DOA估计方法.这种方法的建模过程是用在实际环境下采集的训练样本构造人工神经网络模型,对环境的适应能力较强;且这种方法采用PCA/ICA进行特征提取,使数据得到有效压缩,可以实现系统实时处理.实验结果表明:在信噪比为20dB和0dB时,该方法的正确估计率可达100%;在信噪比降为-20dB时,该方法仍有83%的可识别率.

Bacterial vaginosis as a risk factor for high-grade cervical lesions and cancer in HIV-seropositive women.

OBJECTIVE: To assess the effect of bacterial vaginosis (BV) on the risk of high-grade squamous intraepithelial lesions (HSIL) among HIV-seropositive women. METHODS: A hospital-based prospective cohort study of HIV-seropositive women was conducted in Johannesburg, South Africa from January 2005 to September 2009. Multivariate log-binomial and Poisson regressions were used to estimate prevalence and rate ratios, respectively. RESULTS: Among 1954 HIV-seropositive women, the baseline prevalence of HSIL was 17%. BV prevalence was high (54%) and showed no association with prevalence of HSIL (adjusted prevalence ratio, 1.12; 95% confidence intervals (CI), 0.92-1.35) nor with cervical lesion progression at follow-up visit (n=503) (adjusted rate ratio: 1.00; 95% CI, 0.65-1.53). CONCLUSION: Among HIV-seropositive women, BV was not associated with an increased risk of HSIL or cervical lesion progression.