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The phase field method is becoming the de facto choice for the numerical analysis of complex problems that involve multiple initiating, propagating, interacting, branching and merging fractures. However, within the context of finite element modelling, the method requires a fine mesh in regions where fractures will propagate, in order to capture sharp variations in the phase field representing the fractured/damaged regions. This means that the method can become computationally expensive when the fracture propagation paths are not known a priori. This paper presents a 2D hp-adaptive discontinuous Galerkin finite element method for phase field fracture that includes a posteriori error estimators for both the elasticity and phase field equations, which drive mesh adaptivity for static and propagating fractures. This combination means that it is possible to be reliably and efficiently solve phase field fracture problems with arbitrary initial meshes, irrespective of the initial geometry or loading conditions. This ability is demonstrated on several example problems, which are solved using a light-BFGS (Broyden–Fletcher–Goldfarb–Shanno) quasi-Newton algorithm. The examples highlight the importance of driving mesh adaptivity using both the elasticity and phase field errors for physically meaningful, yet computationally tractable, results. They also reveal the importance of including p-refinement, which is typically not included in existing phase field literature. The above features provide a powerful and general tool for modelling fracture propagation with controlled errors and degree-of-freedom optimised meshes. 

Imaging spectroscopy is a powerful tool used to support diverse Earth science and applications objectives, ranging from understanding and mitigating widespread impacts of climate change to management of water at farm‐scale. Community studies, such as those deployed by NASA's Surface Biology and Geology and ESA's Copernicus Hyperspectral Imaging Mission for the Environment, have offered new and tangible insights into user needs that are then incorporated into overall mission planning and design. These technologies and tools will be key to develop and consolidate downstream services for users and resource management, given the current pressures on the environment posed by climate change and population growth. This process has highlighted the degree to which planned mission capabilities are responsive to community needs. In this study, we analyze user requirements belonging to the Italian Copernicus User Forum and to the user pool of NASA's Surface Biology and Geology community for the synergic use of hyperspectral imaging technology, providing a reference for the development of earth observation services and the consolidation of existing ones. In addition, potential cross‐mission coordination is analyzed to highlight key benefits—(a) addressing shared community needs around products requiring more frequent temporal revisit and (b) shared resources and community expertise around algorithm development. This paper discusses the critical role of early engagement with users to establish a community of practice ready to work with high spatial resolution imaging spectroscopy data sets. The main outcome is a guide for the synergetic use of hyperspectral mission and data together with the identification of the main gaps between user needs and satellite capabilities influencing the development of key national and trans‐national downstream services.

 

Recognizing the affective state of children with autism spectrum disorder (ASD) in real-world settings poses challenges due to the varying head poses, illumination levels, occlusion and a lack of datasets annotated with emotions in in-the-wild scenarios. Understanding the emotional state of children with ASD is crucial for providing personalized interventions and support. Existing methods often rely on controlled lab environments, limiting their applicability to real-world scenarios. Hence, a framework that enables the recognition of affective states in children with ASD in uncontrolled settings is needed. This paper presents a framework for recognizing the affective state of children with ASD in an in-the-wild setting using heart rate (HR) information. More specifically, an algorithm is developed that can classify a participant’s emotion as positive, negative, or neutral by analyzing the heart rate signal acquired from a smartwatch. The heart rate data are obtained in real time using a smartwatch application while the child learns to code a robot and interacts with an avatar. The avatar assists the child in developing communication skills and programming the robot. In this paper, we also present a semi-automated annotation technique based on facial expression recognition for the heart rate data. The HR signal is analyzed to extract features that capture the emotional state of the child. Additionally, in this paper, the performance of a raw HR-signal-based emotion classification algorithm is compared with a classification approach based on features extracted from HR signals using discrete wavelet transform (DWT). The experimental results demonstrate that the proposed method achieves comparable performance to state-of-the-art HR-based emotion recognition techniques, despite being conducted in an uncontrolled setting rather than a controlled lab environment. The framework presented in this paper contributes to the real-world affect analysis of children with ASD using HR information. By enabling emotion recognition in uncontrolled settings, this approach has the potential to improve the monitoring and understanding of the emotional well-being of children with ASD in their daily lives.

 

“An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions” is a fundamental outcome of all engineering programs. Students conduct laboratory experiments in all areas of engineering and report on their findings. New faculty, however, have little experience or training in how to develop effective lab report assignments and instruct students on how to write laboratory reports. In an effort to improve both the teaching and learning of laboratory report writing, engineering educators from three distinct universities (one large public research university, one small public polytechnic university, and one private undergraduate university) developed a series of online laboratory report writing instructional modules. These modules were presented to laboratory instructors, half with less than four years of teaching experience—at a Community of Practice (CoP) retreat in the spring of 2022. Focus groups were conducted with the instructors to determine the potential benefits and shortcomings of the modules, after which the modules underwent significant revisions. Near the conclusion of the CoP retreat, participants reported feeling motivated to implement the newly revised modules to improve their laboratory report writing instruction. Follow-up focus groups were conducted in the following winter to determine if this motivation remained high throughout the summer and resulted in the development of new and improved laboratory assignments in the new academic year. The paper will briefly introduce the modules and present the results of these focus group meetings. 

Anodic electrolytic etching of germanium has been performed in hydrogen peroxide etchants with controlled external conditions. In-situ current and ex-situ etch-depths were measured and tracked with respect to etchant composition and stir rates. Gas bubbles formed during the etching process were found to cause non-uniformity in etch-current and surface quality. The effects were minimized in specific composition spaces. Quantitative analysis revealed a linear correlation of the number of electrons transferred during germanium oxidation with the number of surface atoms removed. Experimental results of 2.77 electrons/atom deviate significantly from 4 electrons/atom previously reported for silicon. The conclusion is that etching mechanisms for germanium are sufficiently different from those for silicon which invalidates the direct transfer of processing techniques between the two materials.

 

This study focuses on the effectiveness of learning transfer-focused or transfer-focused lab report writing instructional modules on engineering undergraduates’ lab report writing in entry-level engineering laboratory courses. The modules are novel due to their shared language to describe and reinforce foundational writing terms used by the writing faculty and are ready for immediate use by engineering lab instructors. Three different universities, consisting of a polytechnical university, a liberal arts-anchored private university, and a branch campus of a research-one land grant university, participated. Student lab report samples from six various sophomore-level engineering courses were collected. For the control group, none of the participating lab instructors accessed the transfer-focused modules (academic years of 2019-2020 and 2020-2021); sixty-four control group lab report samples were collected (n = 64). In the academic year 2021-2022, the lab instructors had access to the transfer-focused modules via the web to be encouraged to update their lab instructions; the experimental group lab report samples were collected from forty-two students (n = 42). Using defined writing outcomes, a panel of engineering lab instructors assessed the participating students’ early (one of the first reports in the class) and late lab reports (written near the end of the course). The lab report assessment analysis indicates that only 30% of the control group students could write their early lab reports at a satisfactory level, while 60% of the experimental group students reached a satisfactory level in their early labs. For both early and late lab reports, the experimental group students outperformed most outcomes over the control group. The notably improved outcomes were related to audience awareness, data presentation, data analysis, and data interpretation. The transfer-focused lab report writing pedagogy enhanced engineering undergraduates’ ability to engage in critical thinking practices, including analysis, interpretation, and evaluation of their lab data/products. Additionally, students appeared to improve their awareness of a technical audience, expecting engineering language, styles, and conventions commonly shared by writers in engineering.