Automatisierte VHDL-Code-Generierung eines Delta-Sigma Modulators

Im vorliegenden Beitrag wird eine automatische Generierung des VHDL-Codes eines Delta-Sigma Modulators präsentiert. Die Koeffizientenmultiplikation wird hierbei durch Bit-Serielle-Addition durchgeführt. Mit Hilfe zweier neuer Matlab Funktionen wird der Systementwurf durch die bekannte Delta-Sigma Toolbox von R. Schreier erweitert und direkt synthesefähiger VHDL Code erzeugt

Corrosion properties of electrodeposited Cu/Co multilayers

The paper presents the results of corrosion resistance of Cu/Co multilayer systems fabricated by using the electrolytic method. The systems obtained were composed of layers differing in number and thickness, which was determined by observing the cross-sections of the samples using scanning electron microscopy (SEM). The measurements of multilayer system corrosion properties carried out in 3,5 % NaCl solution showed different corrosion resistance depending on system thickness. The microscopic observations revealed the effect of the aggressive environment on the Cu/Co multilayer systems manufactured, adopting various forms of corrosion degradation

Preparation and selected properties of Al88Y8-xFe4+x (x = 0, 1, 2 at. %) Alloys in bulk form

The paper presents selected properties of AlYFe rapidly solidified alloys. Samples in the form of plates, obtained by pressure casting method, were subjected to structural tests in order to determine the mechanical properties of the alloys, as well as their corrosion resistance. The corrosion resistance of samples was examined using polarization tests in 3,5 % NaCl solution at 25 °C. The influence of this corrosive medium on the sample’s surface was analyzed with microscopic observations and energy-dispersive spectroscopy (EDS). The mechanical properties of alloys were determined by Vickers hardness tests. The results showed that the properties of Al88Y8-xFe4+x (x = 0, 1, 2 at. %) alloys are related to changes in the content of alloying elements

Fabrication and selected properties of multilayer Fe/Cu systems

The paper presents investigation results of the structure and selected physical properties of multilayer systems obtained by the electrolysis method. The obtained samples compose of 20 alternate layers of Fe/Cu with the following single layer thicknesses: 50 nm and 100 nm. The multilayer Fe/Cu systems for electromagnetic field shielding are characterized by relatively good quality. On the basis of topographical tests, no major defects have been found. As a result of magnetic studies, it has been found that the samples are magnetically soft materials

Preparation and selected properties of Al88Y8-xFe4+x (x = 0, 1, 2 at. %) Alloys in bulk form

The paper presents selected properties of AlYFe rapidly solidified alloys. Samples in the form of plates, obtained by pressure casting method, were subjected to structural tests in order to determine the mechanical properties of the alloys, as well as their corrosion resistance. The corrosion resistance of samples was examined using polarization tests in 3,5 % NaCl solution at 25 °C. The influence of this corrosive medium on the sample’s surface was analyzed with microscopic observations and energy-dispersive spectroscopy (EDS). The mechanical properties of alloys were determined by Vickers hardness tests. The results showed that the properties of Al88Y8-xFe4+x (x = 0, 1, 2 at. %) alloys are related to changes in the content of alloying elements

Turning to God in the Face of Ostracism: Effects of Social Exclusion on Religiousness

The present research proposes that individuals who are socially excluded can turn to religion to cope with the experience. Empirical studies conducted to test this hypothesis consistently found that socially excluded persons reported (a) significantly higher levels of religious affiliation (Studies 1, 2, and 4) and (b) stronger intentions to engage in religious behaviors (Study 2) than comparable, nonexcluded individuals. Direct support for the stress-buffering function of religiousness was also found, with a religious prime reducing the aggression-eliciting effects of consequent social rejection (Study 5). These effects were observed in both Christian and Muslim samples, revealing that turning to religion can be a powerful coping response when dealing with social rejection. Theoretical and practical implications of these findings are discussed

Religion and Self: Notions from a Cultural Psychological Perspective

After a brief introduction of a cultural psychological perspective, this paper turns to the concept of self. The paper proposes to conceive of that reality to which the concepts of self refer as a narrative, employing especially autobiographies and other ego-documents in empirical exploration. After discussing some psychological theories about “self,” the paper points out that they may well be applied in research on personal religiosity

Computer-based intrapartum fetal monitoring and beyond: A review of the 2nd Workshop on Signal Processing and Monitoring in Labor (October 2017, Oxford, UK).

The second Signal Processing and Monitoring in Labor workshop gathered researchers who utilize promising new research strategies and initiatives to tackle the challenges of intrapartum fetal monitoring. The workshop included a series of lectures and discussions focusing on: new algorithms and techniques for cardiotocogoraphy (CTG) and electrocardiogram acquisition and analyses; the results of a CTG evaluation challenge comparing state-of-the-art computerized methods and visual interpretation for the detection of arterial cord pH <7.05 at birth; the lack of consensus about the role of intrapartum acidemia in the etiology of fetal brain injury; the differences between methods for CTG analysis "mimicking" expert clinicians and those derived from "data-driven" analyses; a critical review of the results from two randomized controlled trials testing the former in clinical practice; and relevant insights from modern physiology-based studies. We concluded that the automated algorithms performed comparably to each other and to clinical assessment of the CTG. However, the sensitivity and specificity urgently need to be improved (both computerized and visual assessment). Data-driven CTG evaluation requires further work with large multicenter datasets based on well-defined labor outcomes. And before first tests in the clinic, there are important lessons to be learnt from clinical trials that tested automated algorithms mimicking expert CTG interpretation. In addition, transabdominal fetal electrocardiogram monitoring provides reliable CTG traces and variability estimates; and fetal electrocardiogram waveform analysis is subject to promising new research. There is a clear need for close collaboration between computing and clinical experts. We believe that progress will be possible with multidisciplinary collaborative research

Classification of Caesarean Section and Normal Vaginal Deliveries Using Foetal Heart Rate Signals and Advanced Machine Learning Algorithms

ABSTRACT – Background: Visual inspection of Cardiotocography traces by obstetricians and midwives is the gold standard for monitoring the wellbeing of the foetus during antenatal care. However, inter- and intra-observer variability is high with only a 30% positive predictive value for the classification of pathological outcomes. This has a significant negative impact on the perinatal foetus and often results in cardio-pulmonary arrest, brain and vital organ damage, cerebral palsy, hearing, visual and cognitive defects and in severe cases, death. This paper shows that using machine learning and foetal heart rate signals provides direct information about the foetal state and helps to filter the subjective opinions of medical practitioners when used as a decision support tool. The primary aim is to provide a proof-of-concept that demonstrates how machine learning can be used to objectively determine when medical intervention, such as caesarean section, is required and help avoid preventable perinatal deaths. Methodology: This is evidenced using an open dataset that comprises 506 controls (normal virginal deliveries) and 46 cases (caesarean due to pH ≤7.05 and pathological risk). Several machine-learning algorithms are trained, and validated, using binary classifier performance measures. Results: The findings show that deep learning classification achieves Sensitivity = 94%, Specificity = 91%, Area under the Curve = 99%, F-Score = 100%, and Mean Square Error = 1%. Conclusions: The results demonstrate that machine learning significantly improves the efficiency for the detection of caesarean section and normal vaginal deliveries using foetal heart rate signals compared with obstetrician and midwife predictions and systems reported in previous studies

Writing Toward Readers\u27 Better Health: A Case Study Examining the Development of Online Health Information

Each year, more people search the Internet for health information. Through a case study conducted at a prominent health information company, I will show that technical communicators are well suited to contribute to the development of online health information. Like other technical communicators, online health information developers must make rhetorical choices based on audience needs, function within specific social contexts, and work through challenges of writing, editing, and project management