Does Senior High School Strand Matter in Nursing Students’ Academic Self-Regulated Learning and Academic Performance?

The Philippines recently adopted the K to 12 program in basic education. Under this program, students can choose their track and strand relative to their interests or career choices when they reach senior high school. However, issues surfaced when the K to 12 graduates were admitted to the college courses not aligned with the strand they have completed. This cross-sectional study was conducted to determine the difference in the academic self-regulated learning and performance of the STEM (Science and Technology, Engineering, and Mathematics) and non-STEM graduates in senior high school among freshmen nursing students in a city-subsidized college in the Philippines. The Academic Self-Regulation Learning Scale and grades of students in the first semester were used and analyzed in this study. Results showed that there was a significant difference in the academic self-regulated learning (p=0.045) and academic performance (p=0.000) of freshmen nursing students when grouped according to their senior high school strand.  The STEM graduates had significantly higher academic self-regulated learning and academic performance than the non-STEM completers. Unfortunately, no significant relationship was established between academic self-regulated learning and academic performance (p=0.559). Students who are graduates of the STEM strand from senior high school appear to be better prepared to take up the nursing course. Colleges of nursing may consider the academic strand of students in senior high school when admitting students in the nursing program

AI-aided exploration of lunar arch forms under in-plane seismic loading

Increasing computational power has led to the expansion of civil engi- neering research into using machine learning concepts for developing improved design strategies. These strategies are particularly useful for the design of extra-terrestrial habitats under uncertain environmental conditions. This paper focuses on building an unsupervised machine learning model (convolutional autoencoder) capable of detecting patterns in arch shapes and differentiating between their stress and displacement contours. Foremost, detailed discussions of the model’s architecture and input data are presented. The variation of arch shapes and con- tours between cluster centroids in the latent space is determined, proving the capability of optimisation by moving towards clusters with optimal contours. Finally, a regression model is built to investigate the rela- tionship between the input geometric variables and the latent space representation. We prove that the autoencoder and regression mod- els produce arch shapes with logical structural contours given a set of input geometric variables. The results presented in this paper provide essential tools for the development of an automated design strategy capable of finding optimal arch shapes for extra-terrestrial habitats

A chemotactic model for interaction of antagonistic microflora colonies: front asymptotics and numerical simulations

This paper studies a two-dimensional chemotactic model for two species in which one of them produces a chemo-repellent for the other. It is shown asymptotically and numerically how the chemical inhibits the invasion of a moving front for the second species and how stable steady states, which depend on the chemical concentration, can be reached. The results qualitatively explain experimental observations by Swain and Ray (Microbiol. Res. 164(2), 2009), where colonies of bacteria produce metabolite agents which prevent the invasion of fungi.Comment: New updated version: 24.04.2012. Substitutes previous version of 25.10.2011. New references added. Note a change in titl

Effect of Anisotropic Brain Conductivity on Patient-specific Volume of Tissue Activation in Deep Brain Stimulation for Parkinson Disease

Objective: Deep brain stimulation (DBS) modeling can improve surgical targeting by quantifying the spatial extent of stimulation relative to subcortical structures of interest. A certain degree of model complexity is required to obtain accurate predictions, particularly complexity regarding electrical properties of the tissue around DBS electrodes. In this study, the effect of anisotropy on the volume of tissue activation (VTA) was evaluated in an individualized manner. Methods: Tissue activation models incorporating patient-specific tissue conductivity were built for 40 Parkinson disease patients who had received bilateral subthalamic nucleus (STN) DBS. To assess the impact of local changes in tissue anisotropy, one VTA was computed at each electrode contact using identical stimulation parameters. For comparison, VTAs were also computed assuming isotropic tissue conductivity. Stimulation location was considered by classifying the anisotropic VTAs relative to the STN. VTAs were characterized based on volume, spread in three directions, sphericity, and Dice coefficient. Results: Incorporating anisotropy generated significantly larger and less spherical VTAs overall. However, its effect on VTA size and shape was variable and more nuanced at the individual patient and implantation levels. Dorsal VTAs had significantly higher sphericity than ventral VTAs, suggesting more isotropic behavior. Contrastingly, lateral and posterior VTAs had significantly larger and smaller lateral-medial spreads, respectively. Volume and spread correlated negatively with sphericity. Conclusion: The influence of anisotropy on VTA predictions is important to consider, and varies across patients and stimulation location. Significance: This study highlights the importance of considering individualized factors in DBS modeling to accurately characterize the VT

Dimensionless fragility analysis of seismic acceleration demands through low-order building models

This paper deals with the estimation of fragility functions for acceleration-sensitive components of buildings subjected to earthquake action. It considers ideally coherent pulses as well as real non-pulselike ground-motion records applied to continuous building models formed by a flexural beam and a shear beam in tandem. The study advances the idea of acceleration-based dimensionless fragility functions and describes the process of their formulation. It demonstrates that the mean period of the Fourier Spectrum, Tm , is associated with the least dispersion in the predicted dimensionless mean demand. Likewise, peak ground acceleration, PGA-, and peak ground velocity, PGV-based length scales are found to be almost equally appropriate for obtaining efficient ‘universal’ descriptions of maximum floor accelerations. Finally, this work also shows that fragility functions formulated in terms of dimensionless Π-terms have a superior performance in comparison with those based on conventional non-dimensionless terms (like peak or spectral acceleration values). This improved efficiency is more evident for buildings dominated by global flexural type lateral deformation over the whole intensity range and for large peak floor acceleration levels in structures with shear-governed behaviour. The suggested dimensionless fragility functions can offer a ‘universal’ description of the fragility of acceleration-sensitive components and constitute an efficient tool for a rapid seismic assessment of building contents in structures behaving at, or close to, yielding which form the biggest share in large (regional) building stock evaluations

Do Interventions Designed to Support Shared Decision-Making Reduce Health Inequalities? : A Systematic Review and Meta-Analysis

Copyright: © 2014 Durand et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Increasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities. Objective: To evaluate the impact of SDM interventions on disadvantaged groups and health inequalities. Design: Systematic review and meta-analysis of randomised controlled trials and observational studies.Peer reviewe

From the Trenches: A Cross-Sectional Study Applying the GRADE Tool in Systematic Reviews of Healthcare Interventions

Background: GRADE was developed to address shortcomings of tools to rate the quality of a body of evidence. While much has been published about GRADE, there are few empirical and systematic evaluations. Objective: To assess GRADE for systematic reviews (SRs) in terms of inter-rater agreement and identify areas of uncertainty. Design: Cross-sectional, descriptive study. Methods: We applied GRADE to three SRs (n = 48, 66, and 75 studies, respectively) with 29 comparisons and 12 outcomes overall. Two reviewers graded evidence independently for outcomes deemed clinically important a priori. Inter-rater reliability was assessed using kappas for four main domains (risk of bias, consistency, directness, and precision) and overall quality of evidence. Results: For the first review, reliability was: k = 0.41 for risk of bias; 0.84 consistency; 0.18 precision; and 0.44 overall quality. Kappa could not be calculated for directness as one rater assessed all items as direct; assessors agreed in 41 % of cases. For the second review reliability was: 0.37 consistency and 0.19 precision. Kappa could not be assessed for other items; assessors agreed in 33 % of cases for risk of bias; 100 % directness; and 58 % overall quality. For the third review, reliability was: 0.06 risk of bias; 0.79 consistency; 0.21 precision; and 0.18 overall quality. Assessors agreed in 100 % of cases for directness. Precision created the most uncertainty due to difficulties in identifying ‘‘optimal’ ’ information size and ‘‘clinica

Towards improving early diagnosis of congenital Chagas disease in an endemic setting.

: Congenital Trypanosoma cruzi transmission is now estimated to account for 22% of new infections, representing a significant public health problem across Latin America and internationally. Treatment during infancy is highly efficacious and well tolerated, but current assays for early detection fail to detect &gt;50% of infected neonates and 9 month follow-up is low. : Women presenting for delivery in two urban hospitals in Santa Cruz department, Bolivia were screened by rapid test. Specimens from infants of infected women were tested by microscopy (micromethod), quantitative PCR (qPCR) and IgM trypomastigote excreted-secreted antigen (TESA)-blots at birth and 1 month, and by IgG serology at 6 and 9 months. : Among 487 infants of 476 seropositive women, congenital T. cruzi infection was detected in 38 infants of 35 mothers (7.8%). In cord blood, qPCR, TESA-blot and micromethod sensitivities/specificities were 68.6%/99.1%, 58.3%/99.1% and 16.7%/100%, respectively. When birth and 1 month results were combined, cumulative sensitivities reached 84.2%, 73.7% and 34.2%, respectively. Low birth weight and/or respiratory distress were reported in 11 (29%) infected infants. Infants with clinical signs had higher parasite loads and were significantly more likely to be detected by micromethod. : The proportion of T. cruzi infected infants with clinical signs has fallen from the 1990s, but symptomatic congenital Chagas disease still represents a significant, albeit increasingly challenging to detect, public health problem. Molecular methods could facilitate earlier diagnosis and circumvent loss to follow-up but remain logistically and economically prohibitive for routine screening in resource-limited settings.<br/