Shape optimization is an indispensable step in any aerodynamic design. However, the inherent complexity and non-linearity associated with fluid mechanics as well as the high-dimensional design space ...intrinsic to such problems make airfoil shape optimization a challenging task. Current approaches relying on gradient-based or gradient-free optimizers are data-inefficient in that they do not leverage accumulated knowledge, and are computationally expensive when integrating Computational Fluid Dynamics (CFD) simulation tools. Supervised learning approaches have addressed these limitations but are constrained by user-provided data. Reinforcement learning (RL) provides a data-driven approach bearing generative capabilities. We formulate the airfoil design as a Markov decision process (MDP) and investigate a Deep Reinforcement Learning (DRL) approach to airfoil shape optimization. A custom RL environment is developed allowing the agent to successively modify the shape of an initially provided 2D airfoil and to observe the associated changes in aerodynamic metrics such as lift-to-drag (L/D), lift coefficient (C
) and drag coefficient (C
). The learning abilities of the DRL agent are demonstrated through various experiments in which the agent's objective-maximizing L/D, maximizing C
or minimizing C
-as well as the initial airfoil shape are varied. Results show that the DRL agent is able to generate high performing airfoils within a limited number of learning iterations. The strong resemblance between the artificially produced shapes and those found in the literature highlights the rationality of the decision-making policy learned by the agent. Overall, the presented approach demonstrates the relevance of DRL to airfoil shape optimization and brings forward a successful application of DRL to a physics-based aerodynamics problem.
Many non-binary individuals AFAB (assigned female at birth) seek gestational parenthood. However, the limited available literature is often focused on trans men and overlooks the conception, ...pregnancy, and birth experiences of non-binary parents.
The study aimed to capture the unique reproduction narratives of non-binary people AFAB.
Five non-binary individuals volunteered to participate in this study. Data were collected using largely unstructured, in-depth, tape-recorded interviews. Thematic analysis of the verbatim transcripts and tape recordings yielded a chronological, cohesive narrative for each participant. Four participants reviewed their narrative and confirmed that their story was accurately represented. The individual narratives were then woven into one collective narrative, and common themes across the participants' stories were identified.
Before conception, most participants considered how to balance their medical and social transitions with their reproductive goals. Conception was relatively easy and straightforward for the four participants who used their partner's sperm. The gendered nature of, and language surrounding, pregnancy greatly impacted participant's reproductive experiences, leading to feelings of isolation and loneliness, difficulties finding maternity clothes and gender dysphoria. Participants desired gender-affirming care and reported mostly positive experiences with their healthcare providers. Their gender identity influenced their experiences of parenthood, as well as the decisions they made regarding the disclosure of their gender identity to others, their gender presentation, chestfeeding, and parental designations.
The cisnormative and heteronormative scripts that surround pregnancy shaped the reproductive narratives of those who participated in this research. The findings reinforce the importance of inclusive, gender-affirming healthcare and social support services.
The system complexity that characterizes current systems warrants an integrated and comprehensive approach to system design and development. This need has brought about a paradigm shift towards ...Model-Based Systems Engineering (MBSE) approaches to system design and a departure from traditional document-centric methods. While MBSE shows great promise, the ambiguities and inconsistencies present in Natural Language (NL) requirements hinder their conversion to models directly. The field of Natural Language Processing (NLP) has demonstrated great potential in facilitating the conversion of NL requirements into a semi-machine-readable format that enables their standardization and use in a model-based environment. A first step towards standardizing requirements consists of classifying them according to the type (design, functional, performance, etc.) they represent. To that end, a language model capable of classifying requirements needs to be fine-tuned on labeled aerospace requirements. This paper presents an open-source, annotated aerospace requirements corpus (the first of its kind) developed for the purpose of this effort that includes three types of requirements, namely design, functional, and performance requirements. This paper further describes the use of the aforementioned corpus to fine-tune BERT to obtain the aeroBERT-Classifier: a new language model for classifying aerospace requirements into design, functional, or performance requirements. Finally, this paper provides a comparison between aeroBERT-Classifier and other text classification models such as GPT-2, Bidirectional Long Short-Term Memory (Bi-LSTM), and bart-large-mnli. In particular, it shows the superior performance of aeroBERT-Classifier on classifying aerospace requirements over existing models, and this is despite the fact that the model was fine-tuned using a small labeled dataset.
We examined the life histories of older lesbian, bisexual, and queer women, focusing on the stories they told about their bodies and sexuality from early to later life. Guided by a narrative ...constructionist approach, a series of two life history interviews were conducted with 17 lesbian, bisexual, and queer women aged 65–86. Two themes were constructed through a narrative thematic analysis: Queering the Corset: Negotiating Gender Expression and (Aspirational) Aging Body Acceptance. Participants experienced body-related freedom through ‘tomboy’ expressions of physicality as children. This body autonomy was constrained in adolescence and adulthood due to heterosexist messages surrounding idealized femininity relayed by family and (heterosexual) men, which disrupted self-care yet catalyzed attuned, queer desire and positive embodiment. Women worked to accept their bodies as they aged; they experienced some body dissatisfaction in relation to age-related body changes, yet gratitude and pride in their older queer identities. The findings highlight concurrent positive and negative body image, and breadth of body-related experiences ranging from attunement and agency to discomfort and disruption throughout the life course. This work contributes to body image and embodiment research by moving beyond dominant (youthful) heteronormative perspectives by illuminating how ageism and heterosexism can shape body-related experiences.
•Body histories of older lesbian, bisexual, or queer women are understudied.•Participants experienced body-related freedom and autonomy in childhood.•(Heterosexist) femininity disrupted embodiment in adolescence and adulthood.•Attuned queer desire and embodiment were experienced in mid to later adulthood.•Aging body dissatisfaction, gratitude, and pride were experienced concurrently.
The increased complexity of modern systems is calling for an integrated and comprehensive approach to system design and development and, in particular, a shift toward Model-Based Systems Engineering ...(MBSE) approaches for system design. The requirements that serve as the foundation for these intricate systems are still primarily expressed in Natural Language (NL), which can contain ambiguities and inconsistencies and suffer from a lack of structure that hinders their direct translation into models. The colossal developments in the field of Natural Language Processing (NLP), in general, and Large Language Models (LLMs), in particular, can serve as an enabler for the conversion of NL requirements into machine-readable requirements. Doing so is expected to facilitate their standardization and use in a model-based environment. This paper discusses a two-fold strategy for converting NL requirements into machine-readable requirements using language models. The first approach involves creating a requirements table by extracting information from free-form NL requirements. The second approach consists of an agile methodology that facilitates the identification of boilerplate templates for different types of requirements based on observed linguistic patterns. For this study, three different LLMs are utilized. Two of these models are fine-tuned versions of Bidirectional Encoder Representations from Transformers (BERTs), specifically, aeroBERT-NER and aeroBERT-Classifier, which are trained on annotated aerospace corpora. Another LLM, called flair/chunk-english, is utilized to identify sentence chunks present in NL requirements. All three language models are utilized together to achieve the standardization of requirements. The effectiveness of the methodologies is demonstrated through the semi-automated creation of boilerplates for requirements from Parts 23 and 25 of Title 14 Code of Federal Regulations (CFRs).
Ovarian cancer impacts approximately 1 in 75 women. Sexual health is receiving increasing attention as a critical aspect of gynecologic cancer treatment and a component of quality of life. Therefore, ...investigating how women with ovarian cancer experience and express sexuality is an important area of inquiry.
To evaluate how women with ovarian cancer experience and express sexuality, a major determinant of quality of life, in the context of their illness.
In a mixed-methods approach, 6 validated self-report questionnaires (n = 64) and an in-depth focus group (n = 3) were used to gather data.
The quantitative phase of the study showed that women with ovarian cancer have a poorer quality of life and higher rates of sexual dysfunction and sexual distress compared with published norms from the general population. They also have lower levels of relationship satisfaction and increased rates of depression. The qualitative phase of the study revealed 6 themes: (i) changes to relationship satisfaction; (ii) sexual difficulties; (iii) challenges with body image; (iv) gaps in communication with healthcare providers; (v) feelings of guilt, grief, resentment, anxiety, and fear; and (vi) strategies used for coping.
Ovarian cancer impacts women’s lives beyond mere survival, including their sexual function and quality of life. Healthcare providers are urged to prepare women with ovarian cancer for these challenges and offer information and resources to help improve their quality of life and sexuality.
Fischer OJ, Marguerie M, Brotto LA. Sexual Function, Quality of Life, and Experiences of Women with Ovarian Cancer: A Mixed-Methods Study. Sex Med 2019;7:530–539.
Postural threat elicits modifications to standing balance. However, the underlying neural mechanism(s) responsible remain unclear. Shifts in attention focus including directing more attention to ...balance when threatened may contribute to the balance changes. Sample entropy, a measure of postural sway regularity with lower values reflecting less automatic and more conscious control of balance, may support attention to balance as a mechanism to explain threat-induced balance changes. The main objectives were to investigate the effects of postural threat on sample entropy, and the relationships between threat-induced changes in physiological arousal, perceived anxiety, attention focus, sample entropy, and traditional balance measures. A secondary objective was to explore if biological sex influenced these relationships.
Healthy young adults (63 females, 42 males) stood quietly on a force plate without (No Threat) and with (Threat) the expectation of receiving a postural perturbation (i.e., forward/backward support surface translation). Mean electrodermal activity and anterior-posterior centre of pressure (COP) sample entropy, mean position, root mean square, mean power frequency, and power within low (0-0.05 Hz), medium (0.5-1.8 Hz), and high-frequency (1.8-5 Hz) components were calculated for each trial. Perceived anxiety and attention focus to balance, task objectives, threat-related stimuli, self-regulatory strategies, and task-irrelevant information were rated after each trial.
Significant threat effects were observed for all measures, except low-frequency sway. Participants were more physiologically aroused, more anxious, and directed more attention to balance, task objectives, threat-related stimuli, and self-regulatory strategies, and less to task-irrelevant information in the Threat compared to No Threat condition. Participants also increased sample entropy, leaned further forward, and increased the amplitude and frequency of COP displacements, including medium and high-frequency sway, when threatened. Males and females responded in the same way when threatened, except males had significantly larger threat-induced increases in attention to balance and high-frequency sway. A combination of sex and threat-induced changes in physiological arousal, perceived anxiety, and attention focus accounted for threat-induced changes in specific traditional balance measures, but not sample entropy. Increased sample entropy when threatened may reflect a shift to more automatic control. Directing more conscious control to balance when threatened may act to constrain these threat-induced automatic changes to balance.
Spark Change Olivia Van Ledtje, Cynthia Merrill
2019, 2019-09-23
eBook
Discover the transformational work of student Olivia Van Ledtje, who exemplifies responsible online activism, inspiring both kids and adults in the global community. Kids are naturally curious about ...the world around them. They seek ways to understand and interact with their environment, often using digital tools to do so. Imagine a world where children's curiosities are amplified -- helping them see the power of their thinking, perspective and voice. Spark Change examines the multitude of possibilities available when students are given the opportunity to amplify their learning online, centering on three ideas of citizenship: be a good person, be critical and be an advocate for something you care about in life.The book introduces readers to Liv, a young changemaker empowered to use digital tools to create and share content online. Liv's story offers readers an opportunity to explore how students can use technology as a tool for empathy, equity and activism. Kids can't become changemakers if they aren't empowered to think beyond their own community. Liv's online sense of agency serves as an example of maximizing opportunities, developing a powerful voice and making global connections that deepen her compassion for people and the world.This book: * Follows a model of gradual release of responsibility -- I do, we do, you do -- to show how to teach kids how to approach connected-learning experiences. * Draws on rich literacy and technology research on student identity and pairing literacy and thinking in a digital age. * Illustrates the value of creation and connected learning, weaving in the critical need for digital literacy for students. * Features young students as digital leaders, providing examples of digital activism and the power of authentic student voice and participation. Connected-learning opportunities help students develop key understandings about the world around them. This book shows how these understandings lead to social action, and how students develop a deeper sense of empathy and kindness from interacting with the world. Audience: K-12 educators, school administrators and parents
This paper offers a comprehensive examination of the process involved in developing and automating supervised end-to-end machine learning workflows for forecasting and classification purposes. It ...offers a complete overview of the components (i.e., feature engineering and model selection), principles (i.e., bias–variance decomposition, model complexity, overfitting, model sensitivity to feature assumptions and scaling, and output interpretability), models (i.e., neural networks and regression models), methods (i.e., cross-validation and data augmentation), metrics (i.e., Mean Squared Error and F1-score) and tools that rule most supervised learning applications with numerical and categorical data, as well as their integration, automation, and deployment. The end goal and contribution of this paper is the education and guidance of the non-AI expert academic community regarding complete and rigorous machine learning workflows and data science practices, from problem scoping to design and state-of-the-art automation tools, including basic principles and reasoning in the choice of methods. The paper delves into the critical stages of supervised machine learning workflow development, many of which are often omitted by researchers, and covers foundational concepts essential for understanding and optimizing a functional machine learning workflow, thereby offering a holistic view of task-specific application development for applied researchers who are non-AI experts. This paper may be of significant value to academic researchers developing and prototyping machine learning workflows for their own research or as customer-tailored solutions for government and industry partners.
The incidence of head and neck cutaneous squamous cell carcinoma (HNcSCC) is unevenly distributed between men and women. At present, the mechanism behind this disparity remains elusive. This study ...conducted a systematic review and meta-analysis of proportions to investigate the disparity between sexes for patients with HNcSCC. PubMed, Scopus, EMBASE, MEDLINE, Emcare and CINAHL were searched in November 2021 and June 2022 (N > 50, English, human), and studies which examined the association between sex and HNcSCC were included. Analysis was conducted using RStudio with data and forest plots displaying males as a proportion of total patients with HNcSCC. Two independent researchers performed study selection, data extraction, data analysis and risk of bias. Eighty-two studies (1948 to 2018) comprising approximately 186,000 participants (67% male, 33% female) from 29 countries were included. Significantly more males had HNcSCC overall (71%; CI: 67−74). Males were also significantly more affected by cSCC of the ear (92%; CI: 89−94), lip (74%; CI: 66−81), and eyelid (56%; CI: 51−62). This study found HNcSCC disproportionately affected males overall and across all subtypes. Improving our understanding of sex-specific mechanisms in HNcSCC will better inform our preventive, therapeutic and prognostic practices.
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