Some Notes on Congruency

Some Notes on Congruency is an examination of the seemingly arbitrary methods in which the built environment facilitates order among its inhabitants (eg., parking lot striping, roadway signs). Asphalt fissures observed at the main intersection in Red Hook, NY were used as a starting off point for making the photographs contained within this book. A lens with a focal length that closely resembles the range of human vision was used to communicate the experience of discovering fissures from my perspective as a pedestrian and motorist. I was most captivated by temporal, subtle fissures, such as the replanting of flower beds in a shopping mall before opening time (page 25). These discoveries most often occurred within public spaces, such as bridges, hallways, parking garages, roads, sidewalks and sites of critical infrastructure. In transforming three dimensional space into a two dimensional object, photography provided me the opportunity to examine the complexities of the built environment that I once took for granted

Effectiveness of Unsupervised Training in Deep Learning Neural Networks

Deep learning is a field of research attracting nowadays much attention, mainly because deep architectures help in obtaining outstanding results on many vision, speech and natural language processing – related tasks. To make deep learning effective, very often an unsupervised pretraining phase is applied. In this article, we present experimental study evaluating usefulness of such approach, testing on several benchmarks and different percentages of labeled data, how Contrastive Divergence (CD), one of the most popular pretraining methods, influences network generalization

Robust artificial neural networks and outlier detection. Technical report

Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model. By replacing the traditional least squares criterion with the least trimmed squares criterion, in which half of data is treated as potential outliers, one can fit accurate regression models to strongly contaminated data. High-breakdown methods have become very well established in linear regression, but have started being applied for non-linear regression only recently. In this work, we examine the problem of fitting artificial neural networks to contaminated data using least trimmed squares criterion. We introduce a penalized least trimmed squares criterion which prevents unnecessary removal of valid data. Training of ANNs leads to a challenging non-smooth global optimization problem. We compare the efficiency of several derivative-free optimization methods in solving it, and show that our approach identifies the outliers correctly when ANNs are used for nonlinear regression

PTSD and DNA Methylation in Select Immune Function Gene Promoter Regions: A Repeated Measures Case-Control Study of U.S. Military Service Members

Background: The underlying molecular mechanisms of PTSD are largely unknown. Distinct expression signatures for PTSD have been found, in particular for immune activation transcripts. DNA methylation may be significant in the pathophysiology of PTSD, since the process is intrinsically linked to gene expression. We evaluated temporal changes in DNA methylation in select promoter regions of immune system-related genes in U.S. military service members with a PTSD diagnosis, pre- and post-diagnosis, and in controls. Methods: Cases (n = 75) had a post-deployment diagnosis of PTSD in their medical record. Controls (n = 75) were randomly selected service members with no PTSD diagnosis. DNA was extracted from pre- and post-deployment sera. DNA methylation (%5-mC) was quantified at specific CpG sites in promoter regions of insulin-like growth factor 2 (IGF2), long non-coding RNA transcript H19, interleukin-8 (IL8), IL16, and IL18 via pyrosequencing. We used multivariate analysis of variance and generalized linear models to calculate adjusted means (adjusted for age, gender, and race) to make temporal comparisons of %5-mC for cases (pre- to post-deployment) versus controls (pre- to post-deployment). Results: There were significant differences in the change of %5-mC pre- to post-deployment between cases and controls for H19 (cases: +0.57%, controls: −1.97%; p = 0.04) and IL18 (cases: +1.39%, controls: −3.83%; p = 0.01). For H19 the difference was driven by a significant reduction in %5-mC among controls; for IL18 the difference was driven by both a reduction in %5-mC among controls and an increase in %5-mC among cases. Stratified analyses revealed more pronounced differences in the adjusted means of pre-post H19 and IL18 methylation differences for cases versus controls among older service members, males, service members of white race, and those with shorter deployments (6–12 months). Conclusion: In the study of deployed personnel, those who did not develop PTSD had reduced %5-mC levels of H19 and IL18 after deployment, while those who did develop PTSD had increased levels of IL18. Additionally, pre-deployment the people who later became cases had lower levels of IL18 %5-mC compared with controls. These findings are preliminary and should be investigated in larger studies

Validation of a solvent-based process for the smoothing of additively manufactured 3D models of nasal cavities

In order to improve the reliability of diagnosis of nasal breathing disorders, aerodynamic properties have to be analyzed through experiments based on 3D models. The surface properties of the prepared respective 3D models using fused deposition modeling (FDM) should match those of native nasal cavities, thus representing their normal state and typical pathologies. In this work, we validated the smoothing of dual extruded 3D printed samples of PLA (polylactide) and PVA (polyvinyl alcohol) using the solvent TFE (trifluoroethanol). The smoothing was conducted in vapour and liquid phases of TFE. Before and after treatment of the samples in liquid and vapour phases of TFE, mass and surface roughness analysis were performed. The results of this work will help to produce and process a representative model of the human paranasal sinuses, which can be created using CT data from a patient

Internal Stirring: An Approach to Approximate Evaluation of Shielding Effectiveness of Small Slotted Enclosures

The research for this paper was a collaboration between: 1 Plum Ltd., Wspolna 19, Ignatki, 16-001 Kleosin, Poland 2 Bialystok University of Technology, Wiejska 45D, 15-351 Bialystok, Poland 3 De Montfort University, The Gateway, Leicester, LE1 9BH, UK 4 University of L’Aquila, UAq EMC Laboratory, I-67100, L’Aquila, ItalyA new technique for approximate evaluation of a small slotted enclosure shielding effectiveness (SE) is proposed. The enclosure under test is equipped with a built-in, rotating, conductive stirrer, and the SE is determined for discrete angles of the stirrer position. The SE characteristics computed in the frequency domain for the enclosure with the stirrer are compared to those of the enclosure containing different arrangements of printed circuit boards. The paper concludes that the inclusion of an internal stirrer is a potentially beneficial approach to shielding effectiveness testing

Resting heart rate and its change induced by physical training in patients with ischemic heart disease at various ages treated with beta-blockers

Background: The present study was aimed at possible modifications of resting HR induced by systematic physical training in patients of different age populations with ischemic heart disease (IHD) subjected to chronic therapeutic beta-blockade. Methods: The goal was the assessment of initial resting heart rate (HR) and its change after 6 months of physical training in two groups of patients with IHD at various ages (A: 55.5 &plusmn; &plusmn; 4.6 years; B: 72.5 &plusmn; 4.37 years) treated with beta-blockers, the dosage of which was not modified during the observation. Results: Comparison between the groups A and B concerned the initial rHR (min-1): 79.3 &plusmn; &plusmn; 8.3 vs. 73.6 &plusmn; 8.3 (p < 0.01), the after-training rHR: 70.9 &plusmn; 7.9 vs. 67.7 &plusmn; 8.4 (NS), and the delta of rHR: -8.4 &plusmn; 4.8 vs. -5.9 &plusmn; 2.8 (p < 0.01). Statistically significant correlation coefficients both between the patients&#8217; ages and the initial rHR (r = -0.377) and the delta of rHR (r = 0.347) were noted. Conclusions: The reduction of rHR after 6-months of training was less in the older IHD patients because of their lower initial rHR compared with the younger patients, which was probably determined more by physiological vagotonia than therapeutic beta-blockade. (Cardiol J 2007; 14: 493-496

Under-five mortality: spatial-temporal clusters in Ifakara HDSS in South-eastern Tanzania.

BACKGROUND\ud \ud Childhood mortality remains an important subject, particularly in sub-Saharan Africa where levels are still unacceptably high. To achieve the set Millennium Development Goals 4, calls for comprehensive application of the proven cost-effective interventions. Understanding spatial clustering of childhood mortality can provide a guide in targeting the interventions in a more strategic approach to the population where mortality is highest and the interventions are most likely to make an impact.\ud \ud METHODS\ud \ud Annual child mortality rates were calculated for each village, using person-years observed as the denominator. Kulldorff's spatial scan statistic was used for the identification and testing of childhood mortality clusters. All under-five deaths that occurred within a 10-year period from 1997 to 2006 were included in the analysis. Villages were used as units of clusters; all 25 health and demographic surveillance sites (HDSS) villages in the Ifakara health and demographic surveillance area were included.\ud \ud RESULTS\ud \ud Of the 10 years of analysis, statistically significant spatial clustering was identified in only 2 years (1998 and 2001). In 1998, the statistically significant cluster (p < 0.01) was composed of nine villages. A total of 106 childhood deaths were observed against an expected 77.3. The other statistically significant cluster (p < 0.05) identified in 2001 was composed of only one village. In this cluster, 36 childhood deaths were observed compared to 20.3 expected. Purely temporal analysis indicated that the year 2003 was a significant cluster (p < 0.05). Total deaths were 393 and expected were 335.8. Spatial-temporal analysis showed that nine villages were identified as statistically significant clusters (p < 0.05) for the period covering January 1997-December 1998. Total observed deaths in this cluster were 205 while 150.7 were expected.\ud \ud CONCLUSION\ud \ud There is evidence of spatial clustering in childhood mortality within the Ifakara HDSS. Further investigations are needed to explore the source of clustering and identify strategies of reaching the cluster population with the existing effective interventions. However, that should happen alongside delivery of interventions to the broader population