Background-Long-term follow-up of weight loss interventions is essential, but collecting weights can be difficult, and self-reports inaccurate. We examined the relationship between weight measures obtained in the context of a weight loss trial and in routine clinical care.

In this paper, we propose particle swarm optimization (PSO)-enhanced ensemble deep neural networks and hybrid clustering models for skin lesion segmentation. A PSO variant is proposed, which embeds diverse search actions including simulated annealing, levy flight, helix behavior, modified PSO, and differential evolution operations with spiral search coefficients. These search actions work in a cascade manner to not only equip each individual with different search operations throughout the search process but also assign distinctive search actions to different particles simultaneously in every single iteration. The proposed PSO variant is used to optimize the learning hyper-parameters of convolutional neural networks (CNNs) and the cluster centroids of classical Fuzzy C-Means clustering respectively to overcome performance barriers. Ensemble deep networks and hybrid clustering models are subsequently constructed based on the optimized CNN and hybrid clustering segmenters for lesion segmentation. We evaluate the proposed ensemble models using three skin lesion databases, i.e., PH2, ISIC 2017, and Dermofit Image Library, and a blood cancer data set, i.e., ALL-IDB2. The empirical results indicate that our models outperform other hybrid ensemble clustering models combined with advanced PSO variants, as well as stateof-the-art deep networks in the literature for diverse challenging image segmentation tasks.

The transition of traditional schooling to online learning during the COVID-19 pandemic disrupted formal school education. Though at home, teachers and students continued teaching and learning in socially distant ways using online technologies. From various teacher surveys, only about 60% of students in the United States regularly engaged with learning activities. Teachers and parents also expressed a significant need for help to keep students motivated and engaged in learning activities. During the pandemic, online learning left teachers and parents needing support for learning activities that motivate and engage students. Project-based learning is an increasingly popular pedagogical practice centered around students working collaboratively on projects while the teacher facilitates learning activities and progression. Project-based learning embodies several factors considered central to motivation in online learning. In this paper, we inquire how this approach presents itself as a candidate for learning during the pandemic when considering students’ motivation to learn through online learning experiences. We construct a conceptual framework informed by motivational theories that share core tenets with this form of learning and use the framework to analyze interviews of 11 teachers from 4 schools that taught with a project-based learning approach before the pandemic and transitioned to teaching, using it online, in the Spring of 2020. From our analyses of the teachers’ narratives, we discuss teaching aspects of the approach that lend themselves well to online teaching, elements that the teachers believe are missing, and how educators might cater to these missing aspects with a focus on student motivation to learn.

Diabetic patients from two clinics were studied to determine relationships between knowledge, management, and control of the disease. No relation was found between management and control. A number of questions are raised for further study.

Purpose This paper aims to understand how elementary school educators who teach subjects that traditionally require hands-on work in schools are rising to the challenge of losing brick-and-mortar facilities in the wake of the Coronavirus disease 2019 (COVID-19) crisis. Design/methodology/approach The authors interviewed six elementary school educators and developed iterative grounded codes from the interviews to understand how the teachers are rising to the challenge of teaching online, what supports they need, and how they are viewing their roles and student learning in the present landscape. Findings In response to losing brick-and-mortar schools, teachers are rising to the challenge by creating creative assignments and communicating with students and parents via multiple platforms. They are learning to use technology to create meaningful, socially distant learning experiences and, in the process, blurring their own boundaries between work and life. They exercise compassion for their students while providing the best education they can in these circumstances. Practical implications This work provides administrators, educators, policymakers and technology developers insight into the challenges teachers are facing. Originality/value In addition to the timeliness of this study in light of the COVID 19 crisis, the focus on elementary school students, who often need support from parents or guardians to use Web technologies, and subjects traditionally requiring face-to-face interactions and hands-on work contribute to the originality of the study.

Self-help promises the chance of being ''better''. Across multifarious platforms, including books, apps and television shows, it offers hope that we can be our own agents of change for a happier life. Critical research troubles this premise, arguing that the recurring trope of the individualistic ideal-self found in self-help literature is at the expense of seeking solutions in collective, feminist, or otherwise politicised activism. Self-help is also problematically gendered, since women are often positioned as particularly in need of improvement, an understanding further intensified by postfeminist sensibility. These issues are examined conceptually before introducing 10 articles on self-help published in Feminism & Psychology across three decades and brought together as a Virtual Special Issue to offer a significant body of work for scholars and students alike.

The recent next generation science standards in the United States have emphasized learning about complex systems as a core feature of science learning. Over the past 15 years, a number of educational tools and theories have been investigated to help students learn about complex systems; but surprisingly, little research has been devoted to identifying the supports that teachers need to teach about complex systems in the classroom. In this paper, we aim to address this gap in the literature. We describe a 2-year professional development study in which we gathered data on teachers' abilities and perceptions regarding the delivery of computer-supported complex systems curricula. We present results across the 2 years of the project and demonstrate the need for particular instructional supports to improve implementation efforts, including providing differentiated opportunities to build expertise and addressing teacher beliefs about whether computational-model construction belongs in the science classroom. Results from students' classroom experiences and learning over the 2 years are offered to further illustrate the impact of these instructional supports.

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