Financial Deepening, Trade Openness and Economic Growth in Latin America and the Caribbean

This contribution investigates the direct and indirect causal interactions between financial deepening, trade openness and economic growth for 13 Latin American and Caribbean countries. Using a rather general approach to identify indicators for financial deepening and to detect Granger causality within a VAR/VECM framework, we find almost no evidence for the popular hypothesis of finance-led growth. Evidence of bidirectional finance-growth causality is stronger but mostly unstable in the long run. Most results indicate a demand-following or insignificant relationship between finance and growth in Latin America. This finding seems to be consistent with regard to the weakness and deficiencies of the region's financial systems. Further, there is no evidence that finance indirectly and unilaterally induces growth via the channel of trade openness. Thus, policies that prioritize financial and trade liberalization cannot be supported by this study. Instead, a holistic policy approach seems to be preferable that promotes the determinants of both real sector growth and financial development. As a result, financial factors may positively and significantly contribute to economic development in the region.Financial Markets, Economic Growth, Openness, Hsiao’s Granger Causality, Latin America and Caribbean

Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices

The ubiquity of mobile devices fosters the combined use of ecological momentary assessments (EMA) and mobile crowdsensing (MCS) in the field of healthcare. This combination not only allows researchers to collect ecologically valid data, but also to use smartphone sensors to capture the context in which these data are collected. The TrackYourTinnitus (TYT) platform uses EMA to track users’ individual subjective tinnitus perception and MCS to capture an objective environmental sound level while the EMA questionnaire is filled in. However, the sound level data cannot be used directly among the different smartphones used by TYT users, since uncalibrated raw values are stored. This work describes an approach towards making these values comparable. In the described setting, the evaluation of sensor measurements from different smartphone users becomes increasingly prevalent. Therefore, the shown approach can be also considered as a more general solution as it not only shows how it helped to interpret TYT sound level data, but may also stimulate other researchers, especially those who need to interpret sensor data in a similar setting. Altogether, the approach will show that measuring sound levels with mobile devices is possible in healthcare scenarios, but there are many challenges to ensuring that the measured values are interpretable

Unsupervised classification of operator workload from brain signals

Objective. In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Approach. Subjects executed a task on a touch screen that required continuous effort of visual and motor processing with alternating difficulty. We first employed classical approaches for workload state classification that operate on the sensor space of EEG and compared those to the performance of three state-of-the-art spatial filtering methods: common spatial patterns (CSPs) analysis, which requires binary label information; source power co-modulation (SPoC) analysis, which uses the subjects' error rate as a target function; and canonical SPoC (cSPoC) analysis, which solely makes use of cross-frequency power correlations induced by different states of workload and thus represents an unsupervised approach. Finally, we investigated the effects of fusing brain signals and peripheral physiological measures (PPMs) and examined the added value for improving classification performance. Main results. Mean classification accuracies of 94%, 92% and 82% were achieved with CSP, SPoC, cSPoC, respectively. These methods outperformed the approaches that did not use spatial filtering and they extracted physiologically plausible components. The performance of the unsupervised cSPoC is significantly increased by augmenting it with PPM features. Significance. Our analyses ensured that the signal sources used for classification were of cortical origin and not contaminated with artifacts. Our findings show that workload states can be successfully differentiated from brain signals, even when less and less information from the experimental paradigm is used, thus paving the way for real-world applications in which label information may be noisy or entirely unavailable.BMBF, 01GQ0850, Bernstein Fokus Neurotechnologie - Nichtinvasive Neurotechnologie für Mensch-Maschine Interaktio

Literature-based requirements analysis review of persuasive systems design for mental health applications

Mental health problems are becoming more common while access to treatment is often not available to everyone who needs help. Recent advances in information technology, the wide availability of the internet, the emergence of smartphones and their common usage worldwide raise hope for more treatment options for mental health disorders. Many mobile phone apps that claim to assist in treating a variety of mental health disorders are already available, and the number of such apps continues to increase. The availability of such apps raises many questions about their effectiveness, suitable treatment methods, possibilities for use alongside traditional treatment methods, possible risks and other uncertainties. Beside mobile apps, internet-based apps are also being introduced with similar sets of challenges and ambiguities. One area of research that is gaining a lot of attention recently is Persuasive System Design and Behavior Change. Persuasive System Design is considered one solution that has the potential to help solve the challenges of lack of user motivation and adherence when utilizing mental health applications. The goal of this paper is to perform a literature review, in order to determine the most essential requirements for a persuasively designed mental health application. As part of this process, the challenges and requests of the end-user will be taken into account in order to make recommendations for the future design of such applications

Eingruppierungsunterschiede von Frauen und Männern beim Staat als Arbeitgeber

"In diesem Beitrag wird untersucht, welche Eingruppierungsunterschiede zwischen Männern und Frauen beim Staat als Arbeitgeber im Jahre 1980 bestanden haben. Das empirische Material liefert die Beschäftigtenstichprobe aus dem "Paderborner Datensatz". Verwendet werden zwei Regressionsmodelle mit den Humankapital-Variablen Geschlecht, Schulbildung, Alter und Betriebszugehörigkeitsdauer, die Methode der Komponentenzerlegung sowie ein Index für geschlechtsspezifische Segregation. Die Analyse zeigt, daß Frauen insgesamt gesehen im Durchschnitt niedriger als Männer eingruppiert sind, wobei die Differenz nur zu rund 33% auf Unterschiede in der Humankapitalausstattung zurückgeführt werden kann. Bei einer Aufgliederung in die Statusgruppen Beamte, Angestellte und Arbeiter wird der Befund der Benachteiligung von Frauen für jede dieser drei Gruppen - wenn auch in unterschiedlichem Ausmaße - bestätigt. Dieses Bild ändert sich jedoch stark, wenn innerhalb der Statusgruppen weiter nach Laufbahngruppen bzw. Diensten unterschieden wird: In einer Mehrheit dieser Gruppen sind keine Eingruppierungsbenachteiligungen von Frauen festzustellen, so daß die o.a. Befunde nur auf Benachteiligungen in folgenden Gruppen zurückzuführen sind: Beamtinnen im höheren Dienst, weibliche Angestellte im mittleren Dienst sowie un- und angelernte Arbeiterinnen. Die Unterschiede sind in der Gruppe der un- und angelernten Arbeiterinnen und Arbeiter am stärksten ausgeprägt, bei den Beamtinnen und Beamten des einfachen Dienstes am geringsten. Die Ergebnisse dürfen wegen der Begrenztheit der Datenbasis, der ausschließlichen Berücksichtigung von Humankapitalvariablen sowie der im Prinzip bekannten Besonderheiten der Einstellungspraxis staatlicher Arbeitgeber (Bedeutung der Schulbildung als Zugangsvoraussetzung) nicht überinterpretiert werden. (Autorenreferat)staatlicher Sektor, Frauen, Männer, Eingruppierung, Einkommensunterschied

eSano – An eHealth Platform for Internet- and Mobile-based Interventions

The prevention and treatment of mental disorders and chronic somatic diseases is a core challenge for health care systems of the 21th century. Mental- and behavioral health interventions provide the means for lowering the public health burden. However, structural deficits, reluctance to use existing services, perceived stigma and further personal and environmental reasons restrict the uptake of these evidence-based approaches. Internet- and mobile-based interventions (IMIs) might overcome some of the limitations of on-site interventions by providing an anonymous, scalable, time- and location-independent, yet evidence-based approach. In order to implement digital mental and behavioral health concepts across the life-span into practice, a technical solution to support the design, creation, and execution of IMIs is needed. However, there are various conceptual, technical as well as legal challenges to implementing a corresponding software solution in the healthcare domain. Therefore, the work at hand (1) identifies these challenges and derives a number of respective requirements, (2) introduces the eHealth platform eSano, a software project developed by an interdisciplinary team of computer scientists, psychologists, therapists, and other domain experts, with the aim to serve as a flexible basis for mental and behavioral research and health care, and (3) provides technical insights into the developed platform and its approach to address the aforementioned requirements

Combining Mobile Crowdsensing and Ecological Momentary Assessments in the Healthcare Domain

The increasing prevalence of smart mobile devices (e.g., smartphones) enables the combined use of mobile crowdsensing (MCS) and ecological momentary assessments (EMA) in the healthcare domain. By correlating qualitative longitudinal and ecologically valid EMA assessment data sets with sensor measurements in mobile apps, new valuable insights about patients (e.g., humans who suffer from chronic diseases) can be gained. However, there are numerous conceptual, architectural and technical, as well as legal challenges when implementing a respective software solution. Therefore, the work at hand (1) identifies these challenges, (2) derives respective recommendations, and (3) proposes a reference architecture for a MCS-EMA-platform addressing the defined recommendations. The required insights to propose the reference architecture were gained in several large-scale mHealth crowdsensing studies running for many years and different healthcare questions. To mention only two examples, we are running crowdsensing studies on questions for the tinnitus chronic disorder or psychological stress. We consider the proposed reference architecture and the identified challenges and recommendations as a contribution in two respects. First, they enable other researchers to align our practical studies with a baseline setting that can satisfy the variously revealed insights. Second, they are a proper basis to better compare data that was gathered using MCS and EMA. In addition, the combined use of MCS and EMA increasingly requires suitable architectures and associated digital solutions for the healthcare domain

Comprehensive insights into the TrackYourTinnitus database

The ubiquity of smart mobile devices facilitates data collection in the healthcare domain. Two of the concepts, which can be applied in this context, are mobile crowdsensing (MCS) and ecological momentary assessment (EMA). TrackYourTinnitus (TYT) is an advanced mobile healthcare platform that combines both concepts enabling the monitoring and evaluation of the users’ individual variability of tinnitus symptoms. This paper describes the underlying data set and structure of the TYT mobile platform and highlights selected issues whose investigation provides advanced insights into the users of this mobile platform as well as their data

Development of a ³He magnetometer for a neutron electric dipole moment experiment

We have developed a highly sensitive 3He magnetometer for the accurate measurement of the magnetic field in an experiment searching for an electric dipole moment of the neutron. By measuring the Larmor frequency of nuclear spin polarized 3He atoms a sensitivity on the femto-Tesla scale can be achieved. A 3He/Cs-test facility was established at the Institute of Physics of the Johannes Gutenberg University in Mainz to investigate the readout of 3He free induction decay with a lamp-pumped Cs magnetometer. For this we designed and built an ultra-compact and transportable polarizer unit which polarizes 3He gas up to 55% by metastability exchange optical pumping. The polarized 3He was successfully transfered from the polarizer into a glass cell mounted in a magnetic shield and the 3He free induction decay was detected by a lamp-pumped Cs magnetometer.PACS numbers07.55.Ge Magnetometers for magnetic field measurements; 13.40 Electric and magnetic moments; 14.20 Protons and neutrons