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Aurore Roland,1,2,&ast; Maxime Windal,1,3,&ast; Giovanni Briganti,4– 7 Charles Kornreich,4,5 Olivier Mairesse1,2,4,8 1Brain, Body and Cognition, Department of Psychology, Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel, Brussels, Belgium; 2Brussels University Consultation Center, Department of Psychology, Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel, Brussels, Belgium; 3Faculty of Psychology, Université Libre de Bruxelles, Brussels, Belgium; 4Laboratoire de Psychologie Médicale et Addictologie, CHU/UVC Brugmann, Brussels, Belgium; 5Faculty of Medicine, Université libre de Bruxelles, Brussels, Belgium; 6Faculty of Medicine, Université de Mons, Mons, Belgium; 7Department of Psychology, Harvard University, Cambridge, MA, USA; 8Vital Signs and PERformance Monitoring (VIPER), LIFE Department, Royal Military Academy, Brussels, Belgium&ast;These authors contributed equally to this workCorrespondence: Aurore Roland, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Elsene, Brussels, Belgium, Tel +32 629 25 26, Email aurore.roland@vub.bePurpose: Insomnia, being a mental disorder, is best conceived as a network of symptoms. With the important increase in insomnia prevalence during the COVID-19 pandemic, our aim was to investigate how the structure of insomnia symptoms in the general population has changed due to the pandemic. We also looked at the directional dependencies of nightmares and of covid- and lockdown-related stress/anxiety and depression in insomnia.Patients and Methods: 5986 persons replied to our online questionnaire for the first wave and 2843 persons to our second wave questionnaire. Both questionnaires included the Insomnia Severity Index (ISI). Regularized Gaussian Graphical Models (GGM) and Bayesian Directed Acyclic Graphs (DAG) were estimated.Results: The pre- and peri-lockdown networks were equally strongly connected (first wave: S = 0.13, p = 0.39; second wave: S = 0.03, p = 0.67), but differed for the first lockdown regarding only six edges (M = 0.13, p < 0.001) and for the second lockdown only five edges (M = 0.16, p < 0.001). These symptoms all worsened during the lockdowns in comparison to before the pandemic (p < 0.001). The diurnal items of the ISI had the highest predictability and centrality values in the GGMs. Lockdown-related stress/anxiety influenced indirectly nightmares through covid-related stress/anxiety, lockdown-related depressive affect and mental fatigue. These reported feelings of stress/anxiety and depression showed an indirect impact on insomnia symptoms through mental and physical fatigue.Conclusion: Though the lockdown slightly intensified insomnia symptoms, it did not alter their network structure. Despite their differences, both GGMs and DAGs agree that the diurnal symptoms of the ISI, play an essential role in the network structure. Both methods confirm the need for emphasizing the cognitive/affective component in the treatment of insomnia (ie cognitive behavioral therapy).Keywords: insomnia, network analysis, covid-19, nightmares, mental health

Aims: The Resilience Scale for Adults (RSA) is a questionnaire that measures protective factors of mental health. The aim of this paper is to perform a network analysis of the RSA in a dataset composed of 675 French-speaking Belgian university students, to identify potential targets for intervention to improve protective factors in individuals. Methods: We estimated a network structure for the 33-item questionnaire and for the six domains of resilience: perception of self, planned future, social competence, structured style, family cohesion and social competence. Node predictability (shared variance with surrounding nodes in the network) was used to assess the connectivity of items. An exploratory graph analysis (EGA) was performed to detect communities in the network: the number of communities detected being different than the original number of factors proposed in the scale, we estimated a new network with the resulting structure and verified the validity of the new construct which was proposed. We provide the anonymised dataset and code in external online materials (10.17632/64db36w8kf.2) to ensure complete reproducibility of the results. Results: The network composed of items from the RSA is overall positively connected with strongest connections arising among items from the same domain. The domain network reports several connections, both positive and negative. The EGA reported the existence of four communities that we propose as an additional network structure. Node predictability estimates show that connectedness varies among the items and domains of the RSA. Conclusions: Network analysis is a useful tool to explore resilience and identify targets for clinical intervention. In this study, the four domains acting as components of the additional four-domain network structure may be potential targets to improve an individual's resilience. Further studies may endeavour to replicate our findings in different samples. [ABSTRACT FROM AUTHOR]

Two independent series of calculations are performed simulating spherical and cylindrical C12E6micelles in a temperature range around the experimental sphere-to-rod transition temperature for surfactant concentrations less than 20% by weight. A comparative analysis of these systems helps to shed light on the microscopic details of the micelle sphere-to-rod transition. In agreement with theoretical models, we find that spherical and cylindrical micelles have a different oil core packing; the core radius of a cylindrical micelle is reduced by a factor of 0.87 with respect to the core radius of a spherical micelle. Despite this contraction, the specific volume of the alkyl tails is larger in a cylindrical micelle than in a spherical micelle. In both geometries, this specific volume follows the same linear increase with temperature. Density measurement experiments are also performed in order to evaluate the specific volume of the hydrophobic tail of surfactants of the C12Ejfamily with jranging from 5 to 8. We observe a good agreement between experimental data and simulation results. Our simulations also show that the spatial distribution of the head groups in the interface is more effective in screening the oil core in the cylindrical aggregate than in the spherical aggregate, reducing by a factor of 2 the oil surface per monomer exposed to water. This screening accounts for a free-energy difference of Δfs= fssph− fscyl≃ +2.5kBTper monomer and mirrors the essential role that the hydrophobic interactions have on the shape transition. We also find that the different interface packing correlates with different conformations and flexibility of the hydrophilic fragments E6, that appear as an entropicreservoir for the transition. Finally, comparing the degree of hydration of a spherical micelle at T= 283 K with that of a cylindrical micelle at T= 318 K, we observe an amount of dehydration in agreement with reported experimental data across the sphere-to-rod transition. However, for aggregates of fixed shape, we find a much smaller amount of dehydration with temperature, suggesting that the shape transition is not a consequence of the measured temperature dehydration but rather the opposite. [ABSTRACT FROM AUTHOR]