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Introduction: Older adults with cancer facing competing treatments must prioritize between various outcomes. This study assessed health outcome prioritization among older adults with cancer starting chemotherapy. Methods: Secondary analysis of a randomized trial addressing vulnerabilities in older adults with cancer. Patients completed three validated outcome prioritization tools: 1) Health Outcomes Tool: prioritizes outcomes (survival, independence, symptoms) using a visual analog scale; 2) Now vs. Later Tool: rates the importance of quality of life at three times—today versus 1 or 5 years in the future; and 3) Attitude Scale: rates agreement with outcome‐related statements. The authors measured the proportion of patients prioritizing various outcomes and evaluated their characteristics. Results: A total of 219 patients (median [range] age 71 [65–88], 68% with metastatic disease) were included. On the Health Outcomes Tool, 60.7% prioritized survival over other outcomes. Having localized disease was associated with choosing survival as top priority. On the Now vs. Later Tool, 50% gave equal importance to current versus future quality of life. On the Attitude Scale, 53.4% disagreed with the statement "the most important thing to me is living as long as I can, no matter what my quality of life is"; and 82.2% agreed with the statement "it is more important to me to maintain my thinking ability than to live as long as possible". Conclusion: Although survival was the top priority for most participants, some older individuals with cancer prioritize other outcomes, such as cognition and function. Clinicians should elicit patient‐defined priorities and include them in decision‐making. In this secondary analysis of 219 older participants (median age 71 years) from a randomized trial addressing vulnerabilities in older adults with cancer, 61% prioritized survival over other outcomes such as maintaining their independence or being free from symptoms. Clinicians should elicit patient‐defined priorities and include them in decision‐making when discussing treatment. [ABSTRACT FROM AUTHOR]

Background: Deep discussions play an important role in students' online learning. However, researchers have largely focused on engaging students in deep discussions in online asynchronous forums. Few studies have investigated how to promote deep discussion via mobile instant messaging (MIM). Objectives: In this study, we applied learning analytical tools (i.e., KBdeX and word clouds) to enhance students' shared epistemic agency and thereby support their deep discussions in MIM. Methods: Forty Chinese college students participated in this study and reflected on their MIM engagement by participating in the learning analytics (LA)‐augmented meta‐discourse sessions. The study used multiple data analysis methods, including content analysis, statistical analysis, epistemic network analysis and lag sequential analysis. Results: We found that LA engaged students in deep discussions and shared epistemic agency‐related discourse, such as creating shared understanding, creating knowledge objects, and projective and regulative processes. In particular, word clouds engaged students in more complete shared epistemic agency discourse trajectory which started from creating awareness of unknowns, then progressed to setting projective plans and sharing information, and ultimately, creating shared understanding. Moreover, our analysis indicated that epistemic agency discourse moves of creating shared understanding led students to a high level of deep discussion. Implications: This study contributes to research by extending the 'comparison paradigm', which focuses on comparing (a)synchronous forums with MIM, to a 'design paradigm', which mobilises design features from (a)synchronous forums to MIM and using learning analytical tools to engage students in deep online discussions by promoting their epistemic agency. Lay Description: What is known in this subject matter: Supporting students' online deep discussions is important.Prior studies have shown multiple technological and pedagogical strategies to support deep discussions in (a)synchronous discussion forums, but few studies in mobile instant messaging (MIM).MIM is a quasi‐synchronous tool. It is difficult to transform the traditional external scaffolds (i.e., scripts or teachers' facilitation) which promote deep discussions from (a)synchronous forums to MIM. What this paper adds to this: We constructed a design framework which used learning analytical tools‐augmented meta‐discourse to engage students in shared epistemic agency discourse moves to promote their deep discussion in MIM.We conducted multiple types of analyses (content analysis, statistical analysis, epistemic network analysis and lag sequential analysis) on students' WeChat message (a major MIM in China).Results indicated both learning analytical tools helped engage students in shared epistemic agency discourse moves, such as creating shared understanding, creating knowledge objects, projective and regulative, thus, to promote students' deep discussions. Word cloud especially engaged students in more complete shared epistemic agency discourse trajectory. Moreover, analysis results indicated that shared epistemic agency discourse moves of creating shared understanding would lead students to a high level of deep discussions. Implications of study findings for practitioners: Our study provides a feasible way to educational practitioners who want to promote students' deep discussions in their online learning course (both fully online and flipped classroom mode).Knowledge Building Discourse Explorer (KBDeX presents the original analysis results of students' written messages in discussion forums as socio‐cognitive networks.) could be implemented in the classroom. The objective is to encourage students to understand the importance of connecting with peers' ideas in a one‐session implementation period.If time allows, teachers could use word cloud and meta‐discourse to engage students in socio‐metacognitive conversations in class to promote their shared epistemic agency discourse in online discussions. [ABSTRACT FROM AUTHOR]

The difference effect and hydrogen evolution behavior of pure Mg in alkaline NH4+ containing solutions are systematically investigated. The Mg electrode exhibits a positive difference effect, rather the traditional negative difference effect, with the anomalous hydrogen evolution in the alkaline 0.1 M (NH4)2SO4, 0.1 M NH4HCO3 and 0.05 M (NH4)2CO3 solutions. This is primarily attributed to the corrosion product film dissolution effect of NH4+ and the formation of the black corrosion products. The hydrogen evolution kinetics with the difference effects are deduced and explained by the prevailing incomplete film Mg+ mechanism and enhanced catalytic activity mechanism. [ABSTRACT FROM AUTHOR]

Background: Older women with breast cancer frequently experience toxicity‐related hospitalizations during adjuvant chemotherapy. Although the geriatric assessment can identify those at risk, its use in clinic remains limited. One simple, low‐cost marker of vulnerability in older persons is fall history. Here, the authors examined whether falls prechemotherapy can identify older women at risk for toxicity‐related hospitalization during adjuvant chemotherapy for breast cancer. Methods: In a prospective study of women >65 years old with stage I–III breast cancer treated with adjuvant chemotherapy, the authors assessed baseline falls in the past 6 months as a categorical variable: no fall, one fall, and more than one fall. The primary end point was incident hospitalization during chemotherapy attributable to toxicity. Multivariable logistic regression was used to examine the association between falls and toxicity‐related hospitalization, adjusting for sociodemographic, disease, and geriatric covariates. Results: Of the 497 participants, 60 (12.1%) reported falling before chemotherapy, and 114 (22.9%) had one or more toxicity‐related hospitalizations. After adjusting for sociodemographic, disease, and geriatric characteristics, women who fell more than once within 6 months before chemotherapy had greater odds of being hospitalized from toxicity during chemotherapy compared to women who did not fall (50.0% vs. 20.8% experienced toxicity‐related hospitalization, odds ratio, 4.38; 95% confidence interval, 1.66–11.54, p =.003). Conclusions: In this cohort of older women with early breast cancer, women who experienced more than one fall before chemotherapy had an over 4‐fold increased risk of toxicity‐related hospitalization during chemotherapy, independent of sociodemographic, disease, and geriatric factors. In this study, nearly one in four older women with early breast cancer experienced toxicity‐related hospitalization during chemotherapy. Women who reported more than one fall in the 6 months leading up to chemotherapy had a greater than four times higher odds of experiencing toxicity‐related hospitalization during treatment than women who reported no falls. [ABSTRACT FROM AUTHOR]

In the laser powder bed fusion additive manufacturing process, the quality of fabrications is intricately tied to the laser–matter interaction, specifically the formation of the melt pool. This study experimentally examined the intricacies of melt pool characteristics and surface topography across diverse laser powers and speeds via single-track laser scanning on a bare plate and powder bed for 316L stainless steel. The results reveal that the presence of a powder layer amplifies melt pool instability and worsens irregularities due to increased laser absorption and the introduction of uneven mass from the powder. To provide a comprehensive understanding of melt pool dynamics, a high-fidelity computational model encompassing fluid dynamics, heat transfer, vaporization, and solidification was developed. It was validated against the measured melt pool dimensions and morphology, effectively predicting conduction and keyholing modes with irregular surface features. Particularly, the model explained the forming mechanisms of a defective morphology, termed swell-undercut, at high power and speed conditions, detailing the roles of recoil pressure and liquid refilling. As an application, multiple-track simulations replicate the surface features on cubic samples under two distinct process conditions, showcasing the potential of the laser–matter interaction model for process optimization. [ABSTRACT FROM AUTHOR]