Political decentralization and corruption: Evidence from around the world

How does political decentralization affect the frequency and costliness of bribe extraction by corrupt officials? Previous empirical studies, using subjective indexes of perceived corruption and mostly fiscal indicators of decentralization, have suggested conflicting conclusions. In search of more precise findings, we combine and explore two new data sources—an original cross-national data set on particular types of decentralization and the results of a firm level survey conducted in 80 countries about firms' concrete experiences with bribery. In countries with a larger number of government or administrative tiers and (given local revenues) a larger number of local public employees, reported bribery was more frequent. When local—or central—governments received a larger share of GDP in revenue, bribery was less frequent. Overall, the results suggest the danger of uncoordinated rent-seeking as government structures become more complex.postprin

An EEG-based perceptual function integration network for application to drowsy driving

© 2015 Elsevier B.V. All rights reserved. Drowsy driving is among the most critical causes of fatal crashes. Thus, the development of an effective algorithm for detecting a driver's cognitive state demands immediate attention. For decades, studies have observed clear evidence using electroencephalography that the brain's rhythmic activities fluctuate from alertness to drowsiness. Recognition of this physiological signal is the major consideration of neural engineering for designing a feasible countermeasure. This study proposed a perceptual function integration system which used spectral features from multiple independent brain sources for application to recognize the driver's vigilance state. The analysis of brain spectral dynamics demonstrated physiological evidenced that the activities of the multiple cortical sources were highly related to the changes of the vigilance state. The system performances showed a robust and improved accuracy as much as 88% higher than any of results performed by a single-source approach

A unified constitutive model for asymmetric tension and compression creep-ageing behaviour of naturally aged Al-Cu-Li alloy

A set of unified constitutive equations is presented that predict the asymmetric tension and compression creep behaviour and recently observed double primary creep of pre-stretched/naturally aged aluminium-cooper-lithium alloy AA2050-T34. The evolution of the primary micro- and macro-variables related to the precipitation hardening and creep deformation of the alloy during creep age forming (CAF) are analysed and modelled. Equations for the yield strength evolution of the alloy, including an initial reversion and subsequent strengthening, are proposed based on a theory of concurrent dissolution, re-nucleation and growth of precipitates during artificial ageing. We present new observations of so-called double primary creep during the CAF process. This phenomenon is then predicted by introducing effects of interacting microstructures, including evolving precipitates, diffusing solutes and dislocations, into the sinh-law creep model. In addition, concepts of threshold creep stress σth and a microstructure-dependant creep variable H, which behave differently under different external stress directions, are proposed and incorporated into the creep model. This enables prediction of the asymmetric tension and compression creep-ageing behaviour of the alloy. Quantitative transmission electron microscopy (TEM) and related small-angle X-ray scattering (SAXS) analysis have been carried out for selected creep-aged samples to assist the development and calibration of the constitutive model. A good agreement has been achieved between the experimental results and the model. The model has the potential to be applied to creep age forming of other heat-treatable aluminium alloys

Knowledge-based identification of sleep stages based on two forehead electroencephalogram channels

© 2014 Huang, Lin, Ko, Liu, Su and Lin. Sleep quality is important, especially given the considerable number of sleep-related pathologies. The distribution of sleep stages is a highly effective and objective way of quantifying sleep quality. As a standard multi-channel recording used in the study of sleep, polysomnography (PSG) is a widely used diagnostic scheme in sleep medicine. However, the standard process of sleep clinical test, including PSG recording and manual scoring, is complex, uncomfortable, and time-consuming. This process is difficult to implement when taking the whole PSG measurements at home for general healthcare purposes. This work presents a novel sleep stage classification system, based on features from the two forehead EEG channels FP1 and FP2. By recording EEG from forehead, where there is no hair, the proposed system can monitor physiological changes during sleep in a more practical way than previous systems. Through a headband or self-adhesive technology, the necessary sensors can be applied easily by users at home. Analysis results demonstrate that classification performance of the proposed system overcomes the individual differences between different participants in terms of automatically classifying sleep stages. Additionally, the proposed sleep stage classification system can identify kernel sleep features extracted from forehead EEG, which are closely related with sleep clinician's expert knowledge. Moreover, forehead EEG features are classified into five sleep stages by using the relevance vector machine. In a leave-one-subject-out cross validation analysis, we found our system to correctly classify five sleep stages at an average accuracy of 76.7 ± 4.0 (SD) % [average kappa 0.68 ± 0.06 (SD)]. Importantly, the proposed sleep stage classification system using forehead EEG features is a viable alternative for measuring EEG signals at home easily and conveniently to evaluate sleep quality reliably, ultimately improving public healthcare

Identifying changes in EEG information transfer during drowsy driving by transfer entropy

© 2015 Huang, Pal, Chuang and Lin. Drowsy driving is a major cause of automobile accidents. Previous studies used neuroimaging based approaches such as analysis of electroencephalogram (EEG) activities to understand the brain dynamics of different cortical regions during drowsy driving. However, the coupling between brain regions responding to this vigilance change is still unclear. To have a comprehensive understanding of neural mechanisms underlying drowsy driving, in this study we use transfer entropy, a model-free measure of effective connectivity based on information theory. We investigate the pattern of information transfer between brain regions when the vigilance level, which is derived from the driving performance, changes from alertness to drowsiness. Results show that the couplings between pairs of frontal, central, and parietal areas increased at the intermediate level of vigilance, which suggests that an enhancement of the cortico-cortical interaction is necessary to maintain the task performance and prevent behavioral lapses. Additionally, the occipital-related connectivity magnitudes monotonically decreases as the vigilance level declines, which further supports the cortical gating of sensory stimuli during drowsiness. Neurophysiological evidence of mutual relationships between brain regions measured by transfer entropy might enhance the understanding of cortico-cortical communication during drowsy driving

Hard X-ray standing-wave photoemission insights into the structure of an epitaxial Fe/MgO multilayer magnetic tunnel junction

The Fe/MgO magnetic tunnel junction is a classic spintronic system, with current importance technologically and interest for future innovation. The key magnetic properties are linked directly to the structure of hard-to-access buried interfaces, and the Fe and MgO components near the surface are unstable when exposed to air, making a deeper probing, nondestructive, in-situ measurement ideal for this system. We have thus applied hard X-ray photoemission spectroscopy (HXPS) and standing-wave (SW) HXPS in the few kilo-electron-volt energy range to probe the structure of an epitaxially grown MgO/Fe superlattice. The superlattice consists of 9 repeats of MgO grown on Fe by magnetron sputtering on an MgO(001) substrate, with a protective Al2O3 capping layer. We determine through SW-HXPS that 8 of the 9 repeats are similar and ordered, with a period of 33 ± 4 Å, with the minor presence of FeO at the interfaces and a significantly distorted top bilayer with ca. 3 times the oxidation of the lower layers at the top MgO/Fe interface. There is evidence of asymmetrical oxidation on the top and bottom of the Fe layers. We find agreement with dark-field scanning transmission electron microscope (STEM) and X-ray reflectivity measurements. Through the STEM measurements, we confirm an overall epitaxial stack with dislocations and warping at the interfaces of ca. 5 Å. We also note a distinct difference in the top bilayer, especially MgO, with possible Fe inclusions. We thus demonstrate that SW-HXPS can be used to probe deep buried interfaces of novel magnetic devices with few-angstrom precision

Human myometrial artery function and endothelial cell calcium signalling are reduced by obesity: can this contribute to poor labour outcomes?

AIMS:Determining how obesity affects function in human myometrial arteries, to help understand why childbirth has poor outcomes in obese women. METHODS:Myometrial arteries were studied from 84 biopsies. Contraction (vasopressin and U-46619) and relaxation (carbachol, bradykinin, SNAP) was assessed using wire myography. eNOS activity was assessed using L-NAME. Cholesterol was reduced using methyl-β-cyclodextrin to determine whether it altered responses. Differences in endothelial cell intracellular Ca2+ signalling were assessed using confocal microscopy. RESULTS:The effects of BMI on relaxation were agonist specific and very marked; all vessels, irrespective of BMI, relaxed to bradykinin but 0% of vessels (0/13) from obese women relaxed to carbachol, compared to 59% (10/17) from normal weight women. Cholesterol-lowering drugs did not restore carbachol responses (n=6). All vessels, irrespective of BMI, relaxed when NO was directly released by SNAP (n=19). Inhibition of eNOS with L-NAME had a significant effect in normal but not overweight/obese vessels. Compared to bradykinin, a lower proportion of endothelial cells responded to carbachol and the amplitude of the calcium response was significantly less, in all vessels. Furthermore, a significantly lower proportion of endothelial cells responded to carbachol in the overweight/obese group compared to control. In contrast to relaxation, the effect of contractile agonists was unchanged with increasing BMI. CONCLUSIONS:The ability of human myometrial arteries to relax is significantly impaired with obesity, and our data suggest this is due to a deficit in endothelial calcium signalling. This inability to recover following compression during contractions, might contribute to poor labours in obese women. This article is protected by copyright. All rights reserved

Developing an EEG-based on-line closed-loop lapse detection and mitigation system

© 2014 Wang, Huang, Wei, Huang, Ko, Lin, Cheng and Jung. In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments

Transfer learning with large-scale data in brain-computer interfaces

© 2016 IEEE. Human variability in electroencephalogram (EEG) poses significant challenges for developing practical real-world applications of brain-computer interfaces (BCIs). The intuitive solution of collecting sufficient user-specific training/calibration data can be very labor-intensive and time-consuming, hindering the practicability of BCIs. To address this problem, transfer learning (TL), which leverages existing data from other sessions or subjects, has recently been adopted by the BCI community to build a BCI for a new user with limited calibration data. However, current TL approaches still require training/calibration data from each of conditions, which might be difficult or expensive to obtain. This study proposed a novel TL framework that could nearly eliminate requirement of subject-specific calibration data by leveraging large-scale data from other subjects. The efficacy of this method was validated in a passive BCI that was designed to detect neurocognitive lapses during driving. With the help of large-scale data, the proposed TL approach outperformed the within-subject approach while considerably reducing the amount of calibration data required for each individual (∼1.5 min of data from each individual as opposed to a 90 min pilot session used in a standard within-subject approach). This demonstration might considerably facilitate the real-world applications of BCIs