Determinants of blood pressure in preschool children: the role of parental smoking

Hypertension is the leading risk factor for cardiovascular disease. Although accumulating evidence suggests tracking of blood pressure from childhood into adult life, there is little information regarding the relative contributions of genetic, prenatal, biological, behavioral, environmental, and social determinants to childhood blood pressure.

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

The Impact of Parental Psychological Control on College Students’ Relational Aggression and Friendship Quality

The present study investigated the relationships between parental psychological control and college students’ relational aggression and friendship quality. Based on previous research, it was expected that parents’ use of psychological control would be associated with students’ increased use of relational aggression with peers and lower friendship quality. Students completed a series of survey measures assessing their mothers’ and fathers’ use of psychological control, behavioral control, and warmth/acceptance. Students also completed a series of survey measures assessing their friendship quality, social skills, relational aggression, self-esteem, and social desirability. The study’s findings revealed that parental psychological control was associated with and predicted students’ increased use of relational aggression with peers. Parental psychological control was also associated with students’ lower friendship quality. However, parents’ use of psychological control did not predict students’ friendship quality after accounting for the influence of students’ personal and peer relationship variables. This finding suggests that characteristics of peer relationships may play a larger role than parenting behaviors in shaping college students’ friendships. The study also found that students who displayed higher levels of relational aggression had lower quality friendships. Other findings revealed that the relationship between parental psychological control and students’ friendship quality can be partially explained by students’ use of relational aggression with peers. Students’ friendship quality can also help to explain the influence of parental psychological control on students’ relational aggression. In addition, the study found that combinations of parenting behaviors were more informative predictors of students’ relational aggression and friendship quality than psychological control alone. Finally, this study revealed the importance of assessing participants’ social desirability when measuring sensitive personal qualities such as relational aggression, friendship quality, and self-esteem. Overall, this study contributes to the field of research on parental psychological control by revealing its effects on college students’ relational aggression and friendship quality.

Follicle flushing in monofollicular in vitro fertilization almost doubles the number of transferable embryos

Follicle flushing has been proved to be ineffective in polyfollicular in vitro fertilization. To analyze the effect of flushing in monofollicular in vitro fertilization we aspirated and then flushed the follicles in 164 cycles. Total oocyte yield/aspiration was 44.5% in the aspirate, 20.7% in the 1(st) flush, 10.4% in the 2(nd) flush and 4.3% in the 3(rd) flush. By flushing, the total oocyte yield increased (p < 0.01) by 80.9%, from 44.5 to 80.5%. The total transfer rate increased (p < 0.01) by 91.0%, from 20.1 to 38.4%. The results indicate that the oocyte yield and the number of transferable embryos can be increased significantly by flushing.

17β-estradiol protects 7-day old rats from acute brain injury and reduces the number of apoptotic cells

To test a possible neuroprotective activity of 17β-estradiol in the neonatal rat brain exposed to hypoxic-ischemia (controlled hypoxia after unilateral carotid artery ligation).

Estimating the number of motor units using random sums with independently thinned terms

The problem of estimating the numbers of motor units N in a muscle is embedded in a general stochastic model using the notion of thinning from point process theory. In the paper a new moment type estimator for the numbers of motor units in a muscle is denned, which is derived using random sums with independently thinned terms. Asymptotic normality of the estimator is shown and its practical value is demonstrated with bootstrap and approximative confidence intervals for a data set from a 31-year-old healthy right-handed, female volunteer. Moreover simulation results are presented and Monte-Carlo based quantiles, means, and variances are calculated for N in{300,600,1000}.

Estimating the Number of Essential Genes in a Genome by Random Transposon Mutagenesis

We describe a Bayesian method for estimating the number of essential genes in a genome, on the basis of data on viable mutants for which a single transposon was inserted after a random TA site in a genome,potentially disrupting a gene. The prior distribution for the number of essential genes was taken to be uniform. A Gibbs sampler was used to estimate the posterior distribution. The method is illustrated with simulated data. Further simulations were used to study the performance of the procedure.

EFFICIENT EVALUATION OF RANKING PROCEDURES WHEN THE NUMBER OF UNITS IS LARGE WITH APPLICATION TO SNP IDENTIFICATION

Simulation-based assessment is a popular and frequently necessary approach to evaluation of statistical procedures. Sometimes overlooked is the ability to take advantage of underlying mathematical relations and we focus on this aspect. We show how to take advantage of large-sample theory when conducting a simulation using the analysis of genomic data as a motivating example. The approach uses convergence results to provide an approximation to smaller-sample results, results that are available only by simulation. We consider evaluating and comparing a variety of ranking-based methods for identifying the most highly associated SNPs in a genome-wide association study, derive integral equation representations of the pre-posterior distribution of percentiles produced by three ranking methods, and provide examples comparing performance. These results are of interest in their own right and set the framework for a more extensive set of comparisons.

The role of the number of uninvolved lymph nodes in predicting locoregional recurrence in breast cancer

PURPOSE: To identify groups of early breast cancer patients with substantial risk (10-year risk > 20%) for locoregional failure (LRF) who might benefit from postmastectomy radiotherapy (RT). PATIENTS AND METHODS: Prognostic factors for LRF were evaluated among 6,660 patients (2,588 node-negative patients, 4,072 node-positive patients) in International Breast Cancer Study Group Trials I to IX treated with chemotherapy and/or endocrine therapy, and observed for a median of 14 years. In total, 1,251 LRFs were detected. All patients were treated with mastectomy without RT. RESULTS: No group with 10-year LRF risk exceeding 20% was found among patients with node-negative disease. Among patients with node-positive breast cancer, increasing numbers of uninvolved nodes were significantly associated with decreased risk of LRF, even after adjustment for other prognostic factors. The highest quartile of uninvolved nodes was compared with the lowest quartile. Among premenopausal patients, LRF risk was decreased by 35% (P = .0010); among postmenopausal patients, LRF risk was decreased by 46% (P < .0001). The 10-year cumulative incidence of LRF was 20% among patients with one to three involved lymph nodes and fewer than 10 uninvolved nodes. Age younger than 40 years and vessel invasion were also associated significantly with increased risk. Among patients with node-positive disease, overall survival was significantly greater in those with higher numbers of uninvolved nodes examined (P < .0001). CONCLUSION: Patients with one to three involved nodes and a low number of uninvolved nodes, vessel invasion, or young age have an increased risk of LRF and may be candidates for a similar treatment as those with at least four lymph node metastases.

Data-driven estimates of the number of clusters in multivariate time series

An important problem in unsupervised data clustering is how to determine the number of clusters. Here we investigate how this can be achieved in an automated way by using interrelation matrices of multivariate time series. Two nonparametric and purely data driven algorithms are expounded and compared. The first exploits the eigenvalue spectra of surrogate data, while the second employs the eigenvector components of the interrelation matrix. Compared to the first algorithm, the second approach is computationally faster and not limited to linear interrelation measures.