Optimal Reliability for Components under Thermomechanical Cyclic Loading

We consider the existence of optimal shapes in the context of the thermomechanical system of partial differential equations (PDE) using the recent approach based on elliptic regularity theory. We give an extended and improved definition of the set of admissible shapes based on a class of sufficiently differentiable deformation maps applied to a baseline shape. The obtained set of admissible shapes again allows one to prove a uniform Schauder estimate for the elasticity PDE. In order to deal with thermal stress, a related uniform Schauder estimate is also given for the heat equation. Special emphasis is put on Robin boundary conditions, which are motivated from convective heat transfer. It is shown that these thermal Schauder estimates can serve as an input to the Schauder estimates for the elasticity equation. This is needed to prove the compactness of the (suitably extended) solutions of the entire PDE system in some state space that carries a c2-H\"older topology for the temperature field and a C3-H\"older topology for the displacement. From this one obtains he property of graph compactness, which is the essential tool in an proof of the existence of optimal shapes. Due to the topologies employed, the method works for objective functionals that depend on the displacement and its derivatives up to third order and on the temperature field and its derivatives up to second order. This general result in shape optimization is then applied to the problem of optimal reliability, i.e. the problem of finding shapes that have minimal failure probability under cyclic thermomechanical loading.Comment: 32 pages 1 figur

Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks

Quantifying predictive uncertainty of deep semantic segmentation networks is essential in safety-critical tasks. In applications like autonomous driving, where video data is available, convolutional long short-term memory networks are capable of not only providing semantic segmentations but also predicting the segmentations of the next timesteps. These models use cell states to broadcast information from previous data by taking a time series of inputs to predict one or even further steps into the future. We present a temporal postprocessing method which estimates the prediction performance of convolutional long short-term memory networks by either predicting the intersection over union of predicted and ground truth segments or classifying between intersection over union being equal to zero or greater than zero. To this end, we create temporal cell state-based input metrics per segment and investigate different models for the estimation of the predictive quality based on these metrics. We further study the influence of the number of considered cell states for the proposed metrics.Comment: 14 pages, 4 figures, this work is related to arXiv:1811.00648 and arXiv:1911.0507

The Perilipin Homologue, Lipid Storage Droplet 2, Regulates Sleep Homeostasis and Prevents Learning Impairments Following Sleep Loss

Starvation, which is common in the wild, appears to initiate a genetic program that allows fruitflies to remain awake without the sleepiness and cognitive impairments that typically follow sleep deprivation

Environmental Communication Pedagogy for Sustainability: Developing Core Capacities to Engage with Complex Problems

Pedagogy informed by environmental communication can enhance collaboration within and outside the classroom. Through our collaborative, sustainability-focused work within the United States and internationally, we identified core capacities that prepare people to work together to form inclusive organizations and identify and respond to pressing socioecological problems.We describe six activities we have used in adult learner classrooms, on interdisciplinary and transdisciplinary research teams, and with organizational, governmental, and business partners to improve collaborations for sustainability-related problem solving. We conclude with a reflection on opportunities for situated assessment practices

Estudos traducionais de neuropsiquiatria e esquizofrenia: modelos animais genéticos e de neurodesenvolvimento

Sintomas psiquiátricos são subjetivos por natureza e tendem a se sobrepor entre diferentes desordens. Sendo assim, a criação de modelos de uma desordem neuropsiquiátrica encontra desafios pela falta de conhecimento dos fundamentos da fisiopatologia e diagnósticos precisos. Modelos animais são usados para testar hipóteses de etiologia e para representar a condição humana tão próximo quanto possível para aumentar nosso entendimento da doença e avaliar novos alvos para a descoberta de drogas. Nesta revisão, modelos animais genéticos e de neurodesenvolvimento de esquizofrenia são discutidos com respeito a achados comportamentais e neurofisiológicos e sua associação com a condição clínica. Somente modelos animais específicos de esquizofrenia podem, em último caso, levar a novas abordagens diagnósticas e descoberta de drogas. Argumentamos que biomarcadores moleculares são importantes para aumentar a tradução de animais a humanos, já que faltam a especificidade e a fidelidade necessárias às leituras comportamentais para avaliar sintomas psiquiátricos humanos.Psychiatric symptoms are subjective by nature and tend to overlap between different disorders. The modelling of a neuropsychiatric disorder therefore faces challenges because of missing knowledge of the fundamental pathophysiology and a lack of accurate diagnostics. Animal models are used to test hypotheses of aetiology and to represent the human condition as close as possible to increase our understanding of the disease and to evaluate new targets for drug discovery. In this review, genetic and neurodevelopmental animal models of schizophrenia are discussed with respect to behavioural and neurophysiological findings and their association with the clinical condition. Only specific animal models of schizophrenia may ultimately lead to novel diagnostic approaches and drug discovery. We argue that molecular biomarkers are important to improve animal to human translation since behavioural readouts lack the necessary specificity and reliability to assess human psychiatric symptoms

Agricultural Production and Externalities Simulator (APES) prototype to be used in Prototype 1 of SEAMLESS-IF

Production Economics,

Library of model components for process simulation relevant to production activities, Prototype 1 versions

Production Economics,

Elimination of Metastatic Melanoma Using Gold Nanoshell-Enabled Photothermal Therapy and Adoptive T Cell Transfer

Ablative treatments such as photothermal therapy (PTT) are attractive anticancer strategies because they debulk accessible tumor sites while simultaneously priming antitumor immune responses. However, the immune response following thermal ablation is often insufficient to treat metastatic disease. Here we demonstrate that PTT induces the expression of proinflammatory cytokines and chemokines and promotes the maturation of dendritic cells within tumor-draining lymph nodes, thereby priming antitumor T cell responses. Unexpectedly, however, these immunomodulatory effects were not beneficial to overall antitumor immunity. We found that PTT promoted the infiltration of secondary tumor sites by CD11b+Ly-6G/C+ myeloid-derived suppressor cells, consequently failing to slow the growth of poorly immunogenic B16-F10 tumors and enhancing the growth of distant lung metastases. To exploit the beneficial effects of PTT activity against local tumors and on antitumor immunity whilst avoiding the adverse consequences, we adoptively transferred gp100-specific pmel T cells following PTT. The combination of local control by PTT and systemic antitumor immune reactivity provided by adoptively transferred T cells prevented primary tumor recurrence post-ablation, inhibited tumor growth at distant sites, and abrogated the outgrowth of lung metastases. Hence, the combination of PTT and systemic immunotherapy prevented the adverse effects of PTT on metastatic tumor growth and optimized overall tumor control

Volume 11

Table of Contents: Introduction, Dr. Roger A. Byrne, Dean From the Editor, Dr. Larissa Kat Tracy From the Designers, Rachel English, Rachel Hanson Synthesis of 3,5-substituted Parabens and their Antimicrobial Properties, Jacob Coarney, Ryan White Chernobyl: Putting Perestroika and Glasnot to the Test, Joseph Hyman Art by Jenny Raven Watering Down Accessibility: The Issue with Public Access to Alaska\u27s Federal Waterways, Meagan Garrett Why Has the Democratic Republic of the Congo outsourced its Responsibility to Educate its Citizens? Ibrahim Kante Art by Summer Meinhard A Computational Study of Single Molecule Diodes, Lauren Johnson Satire of the State through Discourse: Applying Althusser and Bakhtin, William Dean Howells Editha , Glen Spencer Design by Laura Gottschalk Why did the United Kingdom Vote to Leave the European Union?, Christopher Siefke Art by Pink Powell Art by Natasha Woodmany Method of Detection of PFOA in Water Samples, Katharine Colley Art by Abbey Mays The Rhetorical Construction of eSports\u27 Legitimacy, Charlotte Pott

Developing the next generation of renewable energy technologies:an overview of low-TRL EU-funded research projects

A cluster of eleven research and innovation projects, funded under the same call of the EU’s H2020 programme, are developing breakthrough and game-changing renewable energy technologies that will form the backbone of the energy system by 2030 and 2050 are, at present, at an early stage of development. These projects have joined forces at a collaborative workshop, entitled ‘ Low-TRL Renewable Energy Technologies’, at the 10th Sustainable Places Conference (SP2022), to share their insights, present their projects’ progress and achievements to date, and expose their approach for exploitation and market uptake of their solutions.</p