Algorithms for the self-optimisation of chemical reactions

Self-optimising chemical systems have experienced a growing momentum in recent years, with the evolution of self-optimising platforms leading to their application for reaction screening and chemical synthesis. With the desire for improved process sustainability, self-optimisation provides a cheaper, faster and greener approach to the chemical development process. The use of such platforms aims to enhance the capabilities of the researcher by removing the need for labor-intensive experimentation, allowing them to focus on more challenging tasks. The establishment of these systems have enabled opportunities for self-optimising platforms to become a key element of a laboratory’s repertoire. To enable the wider adoption of self-optimising chemical platforms, this review summarises the history of algorithmic usage in chemical reaction self-optimisation, detailing the functionality of the algorithms and their applications in a way that is accessible for chemists and highlights opportunities for the further exploitation of algorithms in chemical synthesis moving forward

Alternating polarity for enhanced electrochemical synthesis

Synthetic electrochemistry has recently become an exciting technology for chemical synthesis. The majority of reported syntheses use either constant current or constant potential, however a few use nonlinear profiles – mostly alternating polarity – to maintain efficiency throughout the process, such as controlling deposits on electrodes or ensuring even use of electrodes. However, even though parameters that are associated with such profiles, such as the frequency, can have a major impact on the reaction outcome, they are often not investigated. Herein, we report the crucial impact that the applied frequency of the alternating polarity has on the observed reaction rate of Cu(I)–NHC complex formation and demonstrate that this can be manipulated to give enhanced yield that is stable over extended reaction times

Exploring the Usefulness of Pre-Visit Materials for Children with Autism at a Public Museum

Abstract Children with autism spectrum disorder (ASD) participate in community-based settings at lower rates than typically developing children. Museums provide a structured, predictable, and supportive place for children with ASD to learn. Visiting a museum may create unique challenges for children with ASD and their families. Sensory processing disorder (SPD) is a common barrier to participation that makes it difficult to process information coming in through the senses. For children who are easily overstimulated, crowds, noise, and long lines can be a source of anxiety and stress. Providing pre-visit materials such as social stories, accessibility maps, and communication books can support engagement in the museum setting. This study explored the usefulness of pre-visit materials for children with ASD who attended a low sensory event at a public museum. Data were collected during interviews with 22 parents and care partners. All participants found the pre-visit materials useful before and during the museum visit. Participants provided recommendations for improvement including developing multiple formats (e.g., audio, video), different languages, and limiting the pictures per page. This study highlights the unique value of occupational therapy in a community setting. Occupational therapists consider how features of the environment may support or limit participation. The pre-visit materials developed in this study may help museums offer more inclusive experiences to children with ASD and their families. Partnerships with disciplines such as occupational therapy may help museums and other community organizations welcome visitors of all abilities. Plain Language Summary Museums are key educational resources in the community. Families of children with autism spectrum disorder (ASD) face unique challenges to participating in museum settings. This study explored the usefulness of pre-visit materials including a social story, accessibility map, and communication book. These materials were developed through a partnership between a public museum, occupational therapy graduate program, and 22 parents and care partners of children with ASD. All participants found the pre-visit materials useful for improving participation in a museum visit. This study highlights the unique value of occupational therapy at a museum. The materials developed for this study could be replicated to promote a more inclusive experience in other community settings. Partnering with disciplines experienced in working with people with disabilities can assist in creating welcoming environments for people of all abilities. Additional research is needed to explore the benefits of collaborative partnerships between community organizations and occupational therapy programs

Structural properties and Raman spectroscopy of lipid Langmuir monolayers at the air-water interface

Spectra of octadecylamine (ODA) Langmuir monolayers and egg phosphatidylcholine (PC)/ODA-mixed monolayers at the air-water interface have been acquired. The organization of the monolayers has been characterized by surface pressure-area isotherms. Application of polarized optical microscopy provides further insight in the domain structures and interactions of the film components. Surface-enhanced Raman scattering (SERS) data indicate that enhancement in Raman spectra can be obtained by strong interaction between headgroups of the surfactants and silver particles in subphase. By mixing ODA with phospholipid molecules and spreading the mixture at the air-water interface, we acquired vibrational information of phospholipid molecules with surfactant-aided SERS effect.Comment: 8 pages, 9 figure

Problematic usage of the internet and eating disorder and related psychopathology: a multifaceted, systematic review and meta-analysis

© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Eating disorders are widespread illnesses with significant impact. There is growing concern about how those at risk of eating disorders overuse online resources to their detriment. We conducted a pre-registered systematic review and meta-analysis of studies examining Problematic Usage of the Internet (PUI) and eating disorder and related psychopathology. The meta-analysis comprised n = 32,295 participants, in which PUI was correlated with significant eating disorder general psychopathology Pearson r = 0.22 (s.e. = 0.04, p < 0.001), body dissatisfaction r = 0.16 (s.e. = 0.02, p < 0.001), drive-for-thinness r = 0.16 (s.e. = 0.04, p < 0.001) and dietary restraint r = 0.18 (s.e. = 0.03). Effects were not moderated by gender, PUI facet or study quality. Results are in support of PUI impacting on eating disorder symptoms; males may be equally vulnerable to these potential effects. Prospective and experimental studies in the field suggest that small but significant effects exist and may have accumulative influence over time and across all age groups. Those findings are important to expand our understanding of PUI as a multifaceted concept and its impact on multiple levels of ascertainment of eating disorder and related psychopathology.Peer reviewe

Interpreting the Outsider Tradition in British European Policy Speeches from Thatcher to Cameron

The article investigates how British European policy thinking has been informed by what it identifies as an ‘outsider’ tradition of thinking about ‘Europe’ in British foreign policy dating from imperial times to the presen. The article begins by delineating five phases in the evolution of the outsider tradition through a survey of the relevant historiography back to 1815. The article then examines how prime ministers from Margaret Thatcher to David Cameron have looked to various inflections of the outsider tradition to inform their European discourses. The focus in the speech data sections is on British identity, history and the realist appreciation of international politics that informed the leaders’ suggestions for EEC/EU reform. The central argument is that historically informed narratives such as those making up the outsider tradition do not determine opinion-formers’ outlooks, but that they can be deeply impervious to rapid change

Automated Self-Optimisation of Multi-Step Reaction and Separation Processes Using Machine Learning

There has been an increasing interest in the use of automated self-optimising continuous flow platforms for the development and manufacture in synthesis in recent years. Such processes include multiple reactive and work-up steps, which need to be efficiently optimised. Here, we report the combination of multi-objective optimisation based on machine learning methods (TSEMO algorithm) with self-optimising platforms for the optimisation of multi-step continuous reaction processes. This is demonstrated for a pharmaceutically relevant Sonogashira reaction. We demonstrate how optimum reaction conditions are re-evaluated with the changing downstream work-up specifications in the active learning process. Furthermore, a Claisen-Schmidt condensation reaction with subsequent liquid-liquid separation was optimised with respect to three-objectives. This approach provides the ability to simultaneously optimise multi-step processes with respect to multiple objectives, and thus has the potential to make substantial savings in time and resources

Rapid, Automated Determination of Reaction Models and Kinetic Parameters

We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and kinetic parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding with minimal user input. An automated flow chemistry platform was employed to initially conduct linear flow-ramp experiments to rapidly map the reaction profile of three processes using transient flow data. Following experimental data acquisition, a computational approach was utilised to discriminate between all possible reaction models as well as identify the correct kinetic parameters for each process. Species that are known to participate in the process (starting materials, intermediates, products) are initially inputted by the user prior to flow ramp experiments, then all possible model candidates are compiled into a model library based on their potential to occur after mass balance assessment. Parallel computational optimisation then evaluates each model by algorithmically altering the kinetic parameters of the model to allow convergence of a simulated kinetic curve to the experimental data provided. Statistical analysis then determines the most likely reaction model based on model simplicity and agreement with experimental data. This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost. The computational approach herein described can be employed using data from any set of experiments and the code is open-source

SUDDEN CARDIAC DEATH: ROLE OF LEFT VENTRICULAR DYSFUNCTION

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72037/1/j.1749-6632.1982.tb55219.x.pd