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The COVID-19 crisis still has a firm grip on the aviation industry after global air traffic slumped to 66% below the previous year's level in 2020, and many airlines could only be saved from bankruptcy by special loans or direct state equity investments. At the same time, there is increasing pressure on airlines to accelerate the decarbonization of the sector. Recently, many countries, such as China, the EU, and the US have significantly tightened their climate targets. Air travel is considered a particularly damaging form of travel since before Greta Thunberg's "Friday for Future" movement. As a result, aviation will be expected to make a stronger contribution to decarbonization going forward. The question is how air transport, which has been badly hit by the COVID-19 pandemic, can succeed in converting to climate-neutral flying. An international survey conducted in the fall of 2020 with more than 220 aviation experts and senior managers provides interesting insights and concrete advice on how a path to climate-neutral air transport can be designed and which new risks need to be considered in particular on this path.

This chapter examines the newspaper debates on the EU Constitutional Treaty in seven European states: the Czech Republic, Germany, France, the Slovak Republic, Slovenia, Switzerland, and the UK.

In this work we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pur- suit algorithm and called Dependency Multichannel Matching Pursuit (DMMP). It takes the physiologically explainable and statistically observable topographic dependencies between the channels into account, namely the spatial smoothness of neighboring electrodes that is im- plied by the electric lead¯eld. DMMP decomposes a multichannel signal as a weighted sum of atoms from a given dictionary where the single channels are represented from exactly the same subset of a complete dictionary. The decomposition is illustrated on topographical EEG data during di®erent physiological conditions using a complete Gabor dictionary. Further the extension of the single-channel time-frequency distribution to a multichannel time-frequency distribution is given. This can be used for the visualization of the decomposition structure of multichannel EEG. A clustering procedure applied to the topographies, the vectors of the corresponding contribution of an atom to the signal in each channel produced by DMMP, leads to an extremely sparse topographic decomposition of the EEG.

In order to permit a brain computer efficient communication, it is important to dispose of an efficient algorithm to decode the brain electrical activity. We will focus our attention on an algorithm based on microstates segmentation of the brain electrical activity. First of all, we are going to use electroencephalogram measurements (EEG, 10/20 international system) to collect the electrical activity of the brain. Each sixteen electrodes of the EEG will sample the data at the same rate, forming a matrix of measures. The algorithm is based on the hypothesis that a particular mental activity will generate momentary detectable potential scalp maps (Event Related Potentials, ERP). A mental activity can therefore be seen as a sequential organization of scalp maps, called microstates. To find the best microstates representing a particular mental activity is an exiting challenge. We are going to express the sets of data obtained through EEG as time series of nonoverlapping microstates with different intensities. The algorithm will then converge to a set of microstates representing the data with minimum error. Another inherent problem is that of the ideal number of microstate. How many scalp maps should we use to represent our set of data? The cross validation method is the more adequate for resolving this kind of problems. Applying this method to the data will give us an approximate number of states with a certain error. Improvements of the algorithm are also introduced. There were necessary to guarantee better results and more efficiency. Results are presented in the Comparison section, in which the qualities of the algorithm are underlined by some results analysis. We also compute its complexity and have created an indicator to improve our utilisation of the algorithm. The appendix provides the mathematical demonstrations of the algorithm formulas and focuses its attention on trying to explain all the difficult to understand concepts.

7 pags., 4 figs., 2 tabs., Oceanic emissions of iodine destroy ozone, modify oxidative capacity, and can form new particles in the troposphere. However, the impact of iodine in the stratosphere is highly uncertain due to the lack of previous quantitative measurements. Here, we report quantitative measurements of iodine monoxide radicals and particulate iodine (Iy,part) from aircraft in the stratosphere. These measurements support that 0.77 ± 0.10 parts per trillion by volume (pptv) total inorganic iodine (Iy) is injected to the stratosphere. These high Iy amounts are indicative of active iodine recycling on ice in the upper troposphere (UT), support the upper end of recent Iy estimates (0 to 0.8 pptv) by the World Meteorological Organization, and are incompatible with zero stratospheric iodine injection. Gas-phase iodine (Iy,gas) in the UT (0.67 ± 0.09 pptv) converts to Iy,part sharply near the tropopause. In the stratosphere, IO radicals remain detectable (0.06 ± 0.03 pptv), indicating persistent Iy,part recycling back to Iy,gas as a result of active multiphase chemistry. At the observed levels, iodine is responsible for 32% of the halogen-induced ozone loss (bromine 40%, chlorine 28%), due primarily to previously unconsidered heterogeneous chemistry. Anthropogenic (pollution) ozone has increased iodine emissions since preindustrial times (ca. factor of 3 since 1950) and could be partly responsible for the continued decrease of ozone in the lower stratosphere. Increasing iodine emissions have implications for ozone radiative forcing and possibly new particle formation near the tropopause., The GV aircraft was operated by the NCAR’s Earth Observing Laboratory’s (EOL) Research Aviation Facility. The involvement of the NSF-sponsored Lower Atmospheric Observing Facilities, managed and operated by NCAR/EOL, is acknowledged. R.V. acknowledges funding by NSF Awards AGS-1104104 (TORERO), AGS-1261740 (CONTRAST), and AGS-1620530. ATom-1 and 2 were supported by NASA’s Earth System Science Pathfinder Program EVS-2 funding (Grants NNX15AH33A, NNX15AJ23G, and 80NSSC19K0124). This study has received funding from the European Research Council Executive Agency under the European Union’s Horizon 2020 Research and Innovation Programme (Project ERC2016-COG 726349 CLIMAHAL).

IntroductionNegative symptoms are a core feature of schizophrenia but their pathophysiology remains elusive. They cluster in a motivation-related domain, including apathy, anhedonia, asociality and in an expression-related domain, including alogia and blunted affect.AimOur aim was to investigate the different neurobiological underpinnings of the two domains using the brain electrical microstates (MS), which reflect global patterns of functional connectivity with high temporal resolution.MethodWe recorded multichannel resting EEGs in 142 schizophrenia patients (SCZ) and in 64 healthy controls (HC), recruited to the Italian network for research on psychoses study. Four microstates (MS) classes were computed from resting EEG data using the K-Mean clustering algorithm. Pearson's coefficient was used to investigate correlations of microstates measures with negative symptom domains, assessed by the Brief Negative Symptoms Scale (BNSS).ResultsSCZ, in comparison to HC, showed increased contribution and duration of MS-C. Only the avolition domain of BNSS correlated with the contribution and occurrence of MS-A. Within the same domain, anticipatory anhedonia, apathy and asociality, but not consummatory anhedonia, were positively correlated with contribution and occurrence of microstate A. Asociality was also negatively correlated with contribution and occurrence of MS-D.ConclusionOur findings support different neurobiological underpinnings of the negative symptom domains, avolition and expressive deficit. Furthermore, our results lend support to the hypothesis that only anticipatory anhedonia is linked to the avolition domain of the negative symptoms. Mixed results in the literature concerning the presence of MS-A and D abnormalities in schizophrenia might be related to the syndrome heterogeneity.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionIn subjects with schizophrenia (SCZ), the disorganization factor was found to be a strong predictor of real-life functioning. “Conceptual disorganization” (P2), “difficulties in abstract thinking” (N5) and “poor attention” (G11) are considered core aspects of the disorganization factor, as assessed by PANSS. The overlap of these items with neurocognitive functions is debated and should be further investigated.AimsWithin the Italian network for research on psychoses study, electrophysiological and neurocognitive correlates of the disorganization factor and its component items were investigated.MethodsResting state EEGs were recorded in 145 stabilized SCZ and 69 matched healthy controls (HC). Spectral amplitude (SAmp) was averaged in nine frequency bands. MATRICS consensus cognitive battery (MCCB) was used for neurocognitive assessment. Band SAmp differences and correlations with psychopathology and MCCB scores were explored by global randomization statistics.ResultsSCZ showed increased delta, theta, and beta1 and decreased alpha2 SAmp. A negative correlation between alpha1 and disorganization was observed in SCZ. At the item level, only N5 showed this correlation. MCCB neurocognitive composite was associated with P2 and N5 but not with alpha1 SAmp.ConclusionsOur findings suggest an heterogeneity of the disorganization dimension and a partial overlap with neurocognitive domains. The N5, “difficulties in abstract thinking”, had a unique association with alpha1 SAmp, which is thought to be involved in the formation of conceptual maps.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Brain electrical microstates represent spatial configurations of scalp recorded brain electrical activity and are considered to be the basic elements of stepwise processing of information in the brain. In the present study, the hypothesis of a temporo-limbic dysfunction in panic disorder (PD) was tested by investigating the topographic descriptors of brain microstates, in particular the one corresponding to the Late Positive Complex (LPC), an event-related potential (ERP) component with generators in these regions. ERPs were recorded in PD patients and matched healthy subjects during a target detection task, in a central (CC) and a lateral condition (LC). In the CC, a leftward shift of the LPC microstate positive centroid was observed in the patients with PD versus the healthy control subjects. In the LC, the topographic descriptor of the first microstate showed a rightward shift, while those of both the second and the fourth microstate, corresponding to the LPC, revealed a leftward shift in the PD patients versus the healthy control subjects. These findings indicate an overactivation of the right hemisphere networks involved in early visual processing and a hypoactivation of the right hemisphere circuits involved in LPC generators in PD. In line with this interpretation, the abnormal topography of the LPC microstate, observed in the CC, was associated with a worse performance on a test exploring right temporo-hippocampal functioning. Topographical abnormalities found for the LPC microstate in the LC were associated with a higher number of panic attacks, suggesting a pathogenetic role of the right temporo-hippocampal dysfunction in PD.