Automated detection of invariant manifold intersections using grid based approach

When designing spacecraft trajectories, there exist cases where a trade-off between time-of-flight and fuel become crucial to the mission design scenario, especially for unmanned missions where longer time-of-flight solutions can be considered. One effective way to produce longer time of flight solutions is to leverage the natural dynamics of the system, which lends towards low energy trajectories. The dynamical structures of such systems provide global transport in multi-body regimes, and therefore avenues to low-cost solutions in a minimum fuel or Delta-V sense. Trajectories using the natural dynamics are termed low-energy (LE), and typically include either impulsive or low-thrust control to navigate from one global transport to the next. The multi-body model studied in this thesis is the circular restricted three-body problem (CR3BP) and the dynamical structure of interest are the invariant manifolds of the Euler-Lagrange points. The construction of LE trajectories in the CR3BP is most often accomplished by manually finding homoclinic and/or heteroclinic intersections of invariant manifolds located on specific Poincare surfaces of section. Historically, these patch-points are chosen by hand and used to seed either differential correction, at most yielding a feasible solution, or a control transcription with nonlinear programming to hopefully yield a locally optimal solution. Manual selection of these patch-points is a severe limitation of the current LE trajectory optimization approach and greatly reduces the chance to identify a globally optimal solution. The focus of this thesis is to present an automated solution which removes the bottleneck of characterization and analysis of these intersections of invariant manifolds. This thesis will demonstrate the application of the functionality to autonomously detect and characterize intersections of invariant manifolds, as well as explore the effects of different parameters on performance and generated solutions

6G Underlayer Network Concepts for Ultra Reliable and Low Latency Communication in Manufacturing

Underlayer networks in the context of 6G for manufacturing are crucial. They address the evolving needs of highly interconnected and autonomous systems in industry. The digitalization of manufacturing processes, driven by the Internet of Things and increased data availability, enables more efficient and demand-driven production. However, wireless connectivity, which offers flexibility and easy integration of components, comes with challenges such as signal interference or high latency. A new management system is needed to coordinate and route traffic of multiple networks in a specific coverage area. This paper proposes underlayer networks designed for manufacturing, providing low latency, reliability, and security. These networks enable wireless connectivity and integration of wireless technologies into the manufacturing environment, enhancing flexibility and efficiency. The paper also discusses network slicing, spectrum sharing, and the limitations of current wireless networks in manufacturing. It introduces a network concept for underlayer networks and evaluates its application in closed-loop communication for machine tools. The study concludes with future research prospects in this area

Finite Element Simulation Combination to Predict the Distortion of Thin Walled Milled Aluminum Workpieces as a Result of Machining Induced Residual Stresses

Machining induced residual stresses (MIRS) are a main driver for distortion of monolithic thin walled aluminum workpieces. A typical machining process for manufacturing such geometries for the aerospace industry is milling. In order to avoid high costs due to remanufacturing or part rejection, a simulation combination, consisting of two different finite element method (FEM) models, is developed to predict the part distortion due to MIRS. First, a 3D FEM cutting simulation is developed to predict the residual stresses due to machining. This simulation avoids cost intensive residual stress measurements. The milling process of the aluminum alloy AA7050-T7451 with a regular end mill is simulated. The simulation output, MIRS, forces and temperatures, is validated by face milling experiments on aluminum. The model takes mechanical dynamic effects, thermomechanical coupling, material properties and a damage law into account. Second, a subsequent finite element simulation, characterized by a static, linear elastic model, where the simulated MIRS from the cutting model are used as an input and the distortion of the workpiece is calculated, is presented. The predicted distortion is compared to an additional experiment, where a 1 mm thick wafer was removed at the milled surface of the aluminum workpiece. Furthermore, a thin walled component that represents a down scaled version of an aerospace component is manufactured and its distortion is analyzed. The results show that MIRS could be forecasted with moderate accuracy, which leads to the conclusion that the FEM cutting model needs to be improved in order to use the MIRS for a correct prediction of the distortion with the help of the linear elastic FEM model. The linear elastic model on the other hand is able to predict the part distortion with higher accuracy when using measured data instead of MIRS from the cutting simulation

Signatures of Classical Periodic Orbits on a Smooth Quantum System

Gutzwiller's trace formula and Bogomolny's formula are applied to a non--specific, non--scalable Hamiltonian system, a two--dimensional anharmonic oscillator. These semiclassical theories reproduce well the exact quantal results over a large spatial and energy range.Comment: 12 pages, uuencoded postscript file (1526 kb

Toward semiclassical theory of quantum level correlations of generic chaotic systems

In the present work we study the two-point correlation function $R(\epsilon)$ of the quantum mechanical spectrum of a classically chaotic system. Recently this quantity has been computed for chaotic and for disordered systems using periodic orbit theory and field theory. In this work we present an independent derivation, which is based on periodic orbit theory. The main ingredient in our approach is the use of the spectral zeta function and its autocorrelation function $C(\epsilon)$. The relation between $R(\epsilon)$ and $C(\epsilon)$ is constructed by making use of a probabilistic reasoning similar to that which has been used for the derivation of Hardy -- Littlewood conjecture. We then convert the symmetry properties of the function $C(\epsilon)$ into relations between the so-called diagonal and the off-diagonal parts of $R(\epsilon)$. Our results are valid for generic systems with broken time reversal symmetry, and with non-commensurable periods of the periodic orbits.Comment: 15 pages(twocolumn format), LaTeX, EPSF, (figures included

recommendations by the Conect4Children expert advice group

Funding Information: Competing interests: A.V.R. has received Speaker fees/Consultant for Abbvie, Novartis, UCB, SOBI, Eli Lilly and Roche. N.M. reports grants outside the submitted work in the last five years from the Medical Research Council, National Institute of Health Research, March of Dimes, British Heart Foundation, HCA international, Health Data Research UK, Shire Pharmaceuticals, Chiesi Pharmaceuticals, Prolacta Life Sciences, and Westminster Children’s Research Fund; N.M. is a member of the Nestle Scientific Advisory Board and accepts no personal remuneration for this role. N.M. reports travel and accommodation reimbursements from Chiesi, Nestle and Shire. N.M. is a member of C4C, International Neonatal Collaboration (INC), UK National Research Ethics Advisory Service and MHRA advisory groups and/or working parties. S.W. has received compensation as a member of the scientific advisory board of AM Pharma, Novartis and Khondrion and receives research funding from IMI2 for the Conect4children project. B.A. has worked for GlaxoSmithKline between October 2006 and September 2009 and holds company shares. Between October 2009 and May 2015, she has worked for Novartis. M.S. has recieved research grant and honoraria for meetings and Advisory Boards from Alexion, Sanofi/Genzyme, Takeda, CHIESI, Ultragenix, Orchard, Orphazyme. P.I. is a permanent employee of Bayer AG, Germany. M.V. has received compensation for Advisory boards or Steering committes from Roche, Novartis, Achillion, Apellis, Retrophin/Travere, Alexion pharmaceuticals. C.M. has been a consultant to or has received honoraria from Janssen, Angelini, Servier, Nuvelution, Otsuka, Lundbeck, Pfizer, Neuraxpharm and Esteve outside the submitted work. She declares conflicts of interest unrelated to the present work. M.C. had advisory roles for AstraZeneca, Bayer, Bristol Myers Squibb, Eisai, Lilly, and Roche in the last 2 years (outside the topic of the submitted work, for oncology drugs). M.J. has received research grants from Shire and has been engaged as a speaker or consultant by Shire, Ginsana, PCM Scientific Evolan, and New Nordic, all unrelated to the present work. P.S. has received speaker fees and participated at advisory boards for Biomarin, Zogenyx, GW Pharmaceuticals, and has received research funding by ENECTA BV, GW Pharmaceuticals, Kolfarma srl., Eisai. E.R. has received speaker fees and participated at advisory boards for Eisai and has received research funding by GW Pharmaceuticals, Pfizer, Italian Ministry of Health (MoH) and the Italian Medicine Agency (AIFA). This work was developed within the framework of the DINOGMI Department of Excellence of MIUR 2018-2022 (legge 232 del 2016). M.A.R. is a member of the c4c Ethics Expert Group and received compensation for ethical consulting activities from Bayer AG Wallace Crandall is employee of Eli Lilly and Co. P.C. is an employee of UCB, and owns stock in the company. She was previously an employee of GSK and owns stock in the company. N.R. has received honoraria for consultancies or speaker bureaus from the following pharmaceutical companies in the past 3 years: Ablynx, Amgen, Astrazeneca-Medimmune, Aurinia, Bayer, Bristol Myers and Squibb, Cambridge Healthcare Research (CHR), Celgene, Domain therapeutic, Eli-Lilly, EMD Serono, Glaxo Smith and Kline, Idorsia, Janssen, Novartis, Pfizer, Sobi, UCB. The IRCCS Istituto Giannina Gaslini (IGG), where NR works as full-time public employee has received contributions from the following industries in the last 3 years: Bristol Myers and Squibb, Eli-Lilly, F Hoffmann-La Roche, Novartis, Pfizer, Sobi. This funding has been reinvested for the research activities of the hospital in a fully independent manner, without any commitment with third parties. M.L. receives/has received consultation fees from CSL Behring, Novartis, Roche and Octopharma, travel grants from Merck Serono, and been awarded educational grants to organise meetings by Novartis, Biogen Idec, Merck Serono and Bayer. All other authors have no disclosures. Funding Information: Conect4children has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777389. The Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. The views expressed in this article are the personal views of the author(s) and should not be interpreted as made on behalf of, or reflecting the position of, the regulatory agency/agencies or organisations with which the author(s) is/are employed/affiliated . Publisher Copyright: © 2021, The Author(s).Background: The COVID-19 pandemic has had a devastating impact on multiple aspects of healthcare, but has also triggered new ways of working, stimulated novel approaches in clinical research and reinforced the value of previous innovations. Conect4children (c4c, www.conect4children.org) is a large collaborative European network to facilitate the development of new medicines for paediatric populations, and is made up of 35 academic and 10 industry partners from 20 European countries, more than 50 third parties, and around 500 affiliated partners. Methods: We summarise aspects of clinical research in paediatrics stimulated and reinforced by COVID-19 that the Conect4children group recommends regulators, sponsors, and investigators retain for the future, to enhance the efficiency, reduce the cost and burden of medicines and non-interventional studies, and deliver research-equity. Findings: We summarise aspects of clinical research in paediatrics stimulated and reinforced by COVID-19 that the Conect4children group recommends regulators, sponsors, and investigators retain for the future, to enhance the efficiency, reduce the cost and burden of medicines and non-interventional studies, and deliver research-equityWe provide examples of research innovation, and follow this with recommendations to improve the efficiency of future trials, drawing on industry perspectives, regulatory considerations, infrastructure requirements and parent–patient–public involvement. We end with a comment on progress made towards greater international harmonisation of paediatric research and how lessons learned from COVID-19 studies might assist in further improvements in this important area.publishersversionepub_ahead_of_prin

Recon3D enables a three-dimensional view of gene variation in human metabolism

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life

Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies

Background: The application of rehabilitation robots has grown during the last decade. While meta-analyses have shown beneficial effects of robotic interventions for some patient groups, the evidence is less in others. We established the Advanced Robotic Therapy Integrated Centers (ARTIC) network with the goal of advancing the science and clinical practice of rehabilitation robotics. The investigators hope to exploit variations in practice to learn about current clinical application and outcomes. The aim of this paper is to introduce the ARTIC network to the clinical and research community, present the initial data set and its characteristics and compare the outcome data collected so far with data from prior studies. Methods: ARTIC is a pragmatic observational study of clinical care. The database includes patients with various neurological and gait deficits who used the driven gait orthosis Lokomat® as part of their treatment. Patient characteristics, diagnosis-specific information, and indicators of impairment severity are collected. Core clinical assessments include the 10-Meter Walk Test and the Goal Attainment Scaling. Data from each Lokomat® training session are automatically collected. Results: At time of analysis, the database contained data collected from 595 patients (cerebral palsy: n = 208; stroke: n = 129; spinal cord injury: n = 93; traumatic brain injury: n = 39; and various other diagnoses: n = 126). At onset, average walking speeds were slow. The training intensity increased from the first to the final therapy session and most patients achieved their goals. Conclusions: The characteristics of the patients matched epidemiological data for the target populations. When patient characteristics differed from epidemiological data, this was mainly due to the selection criteria used to assess eligibility for Lokomat® training. While patients included in randomized controlled interventional trials have to fulfill many inclusion and exclusion criteria, the only selection criteria applying to patients in the ARTIC database are those required for use of the Lokomat®. We suggest that the ARTIC network offers an opportunity to investigate the clinical application and effectiveness of rehabilitation technologies for various diagnoses. Due to the standardization of assessments and the use of a common technology, this network could serve as a basis for researchers interested in specific interventional studies expanding beyond the Lokomat®