A fast vertical trajectory prediction method for air traffic management, and relevant ATM system

The invention concerns a method and system for the prediction of aircrafts vertical trajectory, in particular for Air Traffic Management, comprising the following flight calculation modules: Take-off; Climb; Cruise; Descent; and Landing, corresponding to the relevant flight phases, wherein: the calculation of the predicted aircraft trajectory is effected by using a set of TEM equations comprising, as output variables, the vertical rate of climb or descent, the true air speed, the energy share factor, the thrust and the drag, the mass of the aircraft modeled as point-mass, and comprising, as inpu variables, the Mach number depending on true air speed and temperature and altitude, the gravity acceleration, and the fuel flow, and the flight path angle; the calculation of the predicted aircraft trajectory for Cruise phase, wherein only the mass is varying, is performed by using the following analytical solution to said set of TEM equations

Access to Mental Health Care during the First Wave of the COVID-19 Pandemic in Italy: Results from the COMET Multicentric Study

The COVID-19 pandemic represents an unprecedented public health emergency, with consequences at the political, social, and economic levels. Mental health services have been called to play a key role in facing the impact of the pandemic on the mental health of the general population. In the period March-May 2020, an online survey was implemented as part of the Covid Mental Health Trial (COMET), a multicentric collaborative study carried out in Italy, one of the Western countries most severely hit by the pandemic. The present study aims to investigate the use of mental health resources during the first wave of the pandemic. The final sample consisted of 20,712 participants, mainly females (N = 14,712, 71%) with a mean age of 40.4 ± 14.3 years. Access to mental health services was reported in 7.7% of cases. Among those referred to mental health services, in 93.9% of cases (N = 1503 subjects) a psychological assessment was requested and in 15.7% of cases (N = 252) a psychiatric consultation. People reporting higher levels of perceived loneliness (OR 1.079, 95% CI 1.056-1.101, p < 0.001), practicing smart-working (OR 1.122, 95% CI 0.980-1.285, p = 0.095), using avoidant (OR 1.586, 95% CI 1.458-1.725, p < 0.001) and approach (OR 1.215, 95% CI 1.138-1.299, p < 0.001) coping strategies more frequently accessed mental health services. On the other hand, having higher levels of perceived social support (OR 0.833, 95% CI 0.795-0.873, p < 0.001) was associated with a reduced probability to access mental health services. The COVID-19 pandemic represents a new threat to the mental health and well-being of the general population, therefore specific strategies should be implemented to promote access to mental healthcare during the pandemic and afterwards

Evidence for a vortex-glass transition in superconducting Ba(Fe0.9_{0.9}Co0.1_{0.1})2_{2}As2_{2}

Measurements of magneto-resistivity and magnetic susceptibility were performed on single crystals of superconducting Ba(Fe$_{0.9}$Co$_{0.1}$)$_{2}$As$_{2}$ close to the conditions of optimal doping. The high quality of the investigated samples allows us to reveal a dynamic scaling behaviour associated with a vortex-glass phase transition in the limit of weak degree of quenched disorder. Accordingly, the dissipative component of the ac susceptibility is well reproduced within the framework of Havriliak-Negami relaxation, assuming a critical power-law divergence for the characteristic correlation time $\tau$ of the vortex dynamics. Remarkably, the random disorder introduced by the Fe$_{1-x}$Co$_{x}$ chemical substitution is found to act on the vortices as a much weaker quenched disorder than previously reported for cuprate superconductors such as, e.g., Y$_{1-x}$Pr$_{x}$Ba$_{2}$Cu$_{3}$O$_{7-\delta}$.Comment: 10 pages, 8 figure

The effect of social media and infodemic on mental health during the COVID-19 pandemic: results from the COMET multicentric trial

On January 30, 2020, the World Health Organization (WHO) declared the status of pandemic due to the COVID-19 infection. The initial phases of the pandemic were characterized by uncertainty and public fears. In order to cope with such unexpected conditions, people adopted different coping strategies, including search for information, accessing Internet, and using social media. The present study based on the COMET collaborative research network aims to: (1) assess use of Internet and of social media among the Italian general population; (2) explore differences in web usage between people with pre-existing mental disorders and the general population; (3) identify changes over time in social media usage along the phase 1 of the pandemic; (4) identify the clinical, socio-demographic and contextual predictors of excessive use of social media. A significant increase in time spent on Internet, with an average time of 4.8 &amp; PLUSMN; 0.02 h per day, was found in the global sample of 20,720 participants. Compared with the general population, Internet use was significantly higher in people with pre-existing mental disorders (5.2 &amp; PLUSMN; 0.1 h vs. 4.9 &amp; PLUSMN; 0.02; p &lt; 0.005). According to the multivariate logistic regression model, the risk of excessive use of social media and Internet was significantly higher in people with moderate levels of depressive symptoms (OR: 1.26, CI 95%: 0.99 to 1.59, p &lt; 0.0.005); while protective factors were being students (OR: 0.72, CI 95%: 0.53 to 0.96, p &lt; 0.0029) and living in central Italy (OR: 0.46, CI 95%: 0.23 to 0.90, p &lt; 0.002). The evaluation of social media and Internet use by the general population represents a first step for developing specific protective and supportive interventions for the general population, including practical suggestions on how to safely use Internet and social media

The Impact of Quarantine and Physical Distancing Following COVID-19 on Mental Health : Study Protocol of a Multicentric Italian Population Trial

The COVID-19 pandemic and its related containment measures-mainly physical distancing and isolation-are having detrimental consequences on the mental health of the general population worldwide. In particular, frustration, loneliness, and worries about the future are common reactions and represent well-known risk factors for several mental disorders, including anxiety, affective, and post-traumatic stress disorders. The vast majority of available studies have been conducted in China, where the pandemic started. Italy has been severely hit by the pandemic, and the socio-cultural context is completely different from Eastern countries. Therefore, there is the need for methodologically rigorous studies aiming to evaluate the impact of COVID-19 and quarantine measures on the mental health of the Italian population. In fact, our results will help us to develop appropriate interventions for managing the psychosocial consequences of pandemic. The "COVID-IT-mental health trial" is a no-profit, not-funded, national, multicentric, cross-sectional population-based trial which has the following aims: a) to evaluate the impact of COVID-19 pandemic and its containment measures on mental health of the Italian population; b) to identify the main areas to be targeted by supportive long-term interventions for the different categories of people exposed to the pandemic. Data will be collected through a web-platform using validated assessment tools. Participants will be subdivided into four groups: a) Group 1-COVID-19 quarantine group. This group includes the general population which are quarantined but not isolated, i.e., those not directly exposed to contagion nor in contact with COVID-19+ individuals; b) Group 2-COVID-19+ group, which includes isolated people directly/indirectly exposed to the virus; c) Group 3-COVID-19 healthcare staff group, which includes first- and second-line healthcare professionals; d) Group 4-COVID-19 mental health, which includes users of mental health services and all those who had already been diagnosed with a mental disorder. Mental health services worldwide are not prepared yet to manage the short- and long-term consequences of the pandemic. It is necessary to have a clear picture of the impact that this new stressor will have on mental health and well-being in order to develop and disseminate appropriate interventions for the general population and for the other at-risk groups

“New” cyanobacterial blooms are not new: two centuries of lake production are related to ice cover and land use

Recent cyanobacterial blooms in otherwise unproductive lakes may be warning signs of impending eutrophication in lakes important for recreation and drinking water, but little is known of their historical precedence or mechanisms of regulation. Here, we examined long-term sedimentary records of both general and taxon-specific trophic proxies from seven lakes of varying productivity in the northeastern United States to investigate their relationship to historical in-lake, watershed, and climatic drivers of trophic status. Analysis of fossil pigments (carotenoids and chlorophylls) revealed variable patterns of past primary production across lakes over two centuries despite broadly similar changes in regional climate and land use. Sediment abundance of the cyanobacterium Gloeotrichia, a large, toxic, nitrogen-fixing taxon common in recent blooms in this region, revealed that this was not a new taxon in the phytoplankton communities but rather had been present for centuries. Histories of Gloeotrichia abundance differed strikingly across lakes and were not consistently associated with most other sediment proxies of trophic status. Changes in ice cover most often coincided with changes in fossil pigments, and changes in watershed land use were often related to changes in Gloeotrichia abundance, although no single climatic or land-use factor was associated with proxy changes across all seven lakes. The degree to which changes in lake sediment records co-occurred with changes in the timing of ice-out or agricultural land use was negatively correlated with the ratio of watershed area to lake area. Thus, both climate and land management appeared to play key roles in regulation of primary production in these lakes, although the manner in which these factors influenced lakes was mediated by catchment morphometry. Improved understanding of the past interactions between climate change, land use, landscape setting, and water quality underscores the complexity of mechanisms regulating lake and cyanobacterial production and highlights the necessity of considering these interactions—rather than searching for a singular mechanism—when evaluating the causes of ongoing changes in low-nutrient lakes

Loneliness in Young Adults During the First Wave of COVID-19 Lockdown: Results From the Multicentric COMET Study

The COVID-19 pandemic has affected the mental and physical health of the general population at any age, but it is expected to have a protracted and severe consequences for younger populations. The pandemic has had several consequences on mental health including anger and irritability, depressive symptoms and somatic complaints, insomnia, lack of motivation, and loneliness. In particular, loneliness and its related negative feelings are thought to be particularly pronounced during young adulthood because of the many social changes that young people deal with during this period of life. Therefore, it is essential to evaluate the type of impact of the pandemic on the mental health of young people and their levels of loneliness experienced during the first phase of the lockdown. Based on the largest Italian study on the effects of the COVID-19 pandemic on the mental health of general population, in this paper we aim to: (1) describe the levels of loneliness in a national sample of Italian young adults aged 18–34 years, during the first wave of lockdown in 2020; (2) evaluate the clinical and socio-demographic differences in young adults reporting low vs. high levels of loneliness; (3) assess the role of clinical symptomatology, coping strategies, levels of resilience, and duration of lockdown as possible predictors of loneliness. The final sample consists of 8,584 people, mainly female (72.6%), single, with a mean age of 26.4 (±4.4) years. The mean score at the UCLA was 47.5 (±13.6), with 27% (N = 2,311) of respondents exceeding the cut-off for high levels of loneliness. High levels of loneliness were predicted by the presence of avoidant coping strategies, such as self-distraction (Beta coefficient, B = 0.369, 95% Confidence Interval, CI = 0.328–0.411), venting (B = 0.245, 95% CI = 0.197–0.293), denial (B = 0.110, 95% CI = 0.061–0.159), and emotional disengagement (B = 0.133, 95% CI = 0.080–0.185). Weeks of exposure to the pandemic were significantly associated with worsening of loneliness (p &lt; 0.000). There is currently considerable interest in trying to reduce loneliness, both within the context of COVID-19 and more generally. Our results highlight that young people are at a higher risk of developing loneliness and suggest that more interventions and practical guidelines are needed

Interaction Pattern of Arg 62 in the A-Pocket of Differentially Disease-Associated HLA-B27 Subtypes Suggests Distinct TCR Binding Modes

The single amino acid replacement Asp116His distinguishes the two subtypes HLA-B*2705 and HLA-B*2709 which are, respectively, associated and non-associated with Ankylosing Spondylitis, an autoimmune chronic inflammatory disease. The reason for this differential association is so far poorly understood and might be related to subtype-specific HLA:peptide conformations as well as to subtype/peptide-dependent dynamical properties on the nanoscale. Here, we combine functional experiments with extensive molecular dynamics simulations to investigate the molecular dynamics and function of the conserved Arg62 of the α1-helix for both B27 subtypes in complex with the self-peptides pVIPR (RRKWRRWHL) and TIS (RRLPIFSRL), and the viral peptides pLMP2 (RRRWRRLTV) and NPflu (SRYWAIRTR). Simulations of HLA:peptide systems suggest that peptide-stabilizing interactions of the Arg62 residue observed in crystal structures are metastable for both B27 subtypes under physiological conditions, rendering this arginine solvent-exposed and, probably, a key residue for TCR interaction more than peptide-binding. This view is supported by functional experiments with conservative (R62K) and non-conservative (R62A) B*2705 and B*2709 mutants that showed an overall reduction in their capability to present peptides to CD8+ T cells. Moreover, major subtype-dependent differences in the peptide recognition suggest distinct TCR binding modes for the B*2705 versus the B*2709 subtype

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating