A Shell Model for Free Vibration Analysis of Carbon Nanoscroll

The financial support of Iran Nanotechnology Initiative Council is gratefully acknowledged. Nicola Maria Pugno is supported by the European Research Council PoC 2015 “Silkene” No. 693670, by the European Commission H2020 under the Graphene Flagship Core 1 No. 696656 (WP14 “Polymer Nanocomposites”) and under the FET proactive “Neurofibres” No. 732344

Environmental and genetic influences on early attachment

Attachment theory predicts and subsequent empirical research has amply demonstrated that individual variations in patterns of early attachment behaviour are primarily influenced by differences in sensitive responsiveness of caregivers. However, meta-analyses have shown that parenting behaviour accounts for about one third of the variance in attachment security or disorganisation. The exclusively environmental explanation has been challenged by results demonstrating some, albeit inconclusive, evidence of the effect of infant temperament. In this paper, after reviewing briefly the well-demonstrated familial and wider environmental influences, the evidence is reviewed for genetic and gene-environment interaction effects on developing early attachment relationships. Studies investigating the interaction of genes of monoamine neurotransmission with parenting environment in the course of early relationship development suggest that children's differential susceptibility to the rearing environment depends partly on genetic differences. In addition to the overview of environmental and genetic contributions to infant attachment, and especially to disorganised attachment relevant to mental health issues, the few existing studies of gene-attachment interaction effects on development of childhood behavioural problems are also reviewed. A short account of the most important methodological problems to be overcome in molecular genetic studies of psychological and psychiatric phenotypes is also given. Finally, animal research focusing on brain-structural aspects related to early care and the new, conceptually important direction of studying environmental programming of early development through epigenetic modification of gene functioning is examined in brief

Five insights from the Global Burden of Disease Study 2019

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe

Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

Background The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. Funding The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38)

Analysis of performance and energy consumption in the cloud

International audienceWe analyze here a cloud system represented by hysteresis multi server queueing system. It is characterized by forward and backward thresholds for activation and deactivation of block of servers representing a set of VMs (Virtual Machines). The system is represented by a complex Markov Chain which is difficult to analyse when the size of the system is huge. We propose both analytical and numerical mathematical methods for deriving the steady-state probability distribution. We compute then performance and energy consumption measures and we define an overall cost taking into account both aspects. We compare the proposed methods with respect to the computation time and we analyse the impact of some parameters on the behaviour of the syste