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Background: Excessive worry during adolescence can significantly impact mental health. Understanding adolescent concerns may help inform mental health early intervention strategies. Objective: This study aimed to identify frequent concerns among Australian secondary school students, exploring individual and demographic differences. Whether adolescents' most frequently reported concern was associated with mental health and wellbeing was also investigated. Methods: A total of N = 4086 adolescents (Mage = 13.92) participated in an online survey, reporting their top concerns alongside demographic characteristics, mental health, and wellbeing. Data were analysed using both qualitative and quantitative approaches. Results: Thematic analysis identified 11 different themes of adolescent concerns. A frequency analysis showed concerns relating to 'School and Academics' were most common (24.52% of all responses), consistent across females, males, school location (regional vs metropolitan areas), and socioeconomic background. Sexuality and gender diverse adolescents more frequently reported concerns about 'Mental Health and Wellbeing' and 'Social Relationships'. Linear mixed models found 'School and Academic' concerns were associated with lower symptoms of depression (p < 0.001, d = 0.16) and anxiety (p < 0.001, d = 0.19) and higher wellbeing (p = 0.03, d = 0.07) compared to all other concerns. Conclusion: 'School and Academic' concerns were most common, however not associated with poorer mental health or wellbeing. Sexuality and gender diverse adolescents were more likely to report concerns regarding 'Mental Health and Wellbeing' and 'Social Relationships'. Efforts aimed solely at reducing academic stress may not be the most effective approach to improving adolescent mental health. Longitudinal data into how concerns evolve over time could provide a nuanced understanding of their relationship with future mental health challenges.

Learning by Evaluating (LbE) is an instructional approach that involves students making comparative judgements of pairs of artifacts, such as student work, portfolios, prototypes, or curated images related to a topic of instruction to enhance critical thinking and decision-making skills. Situated as a primer for learning, the efficacy of LbE stems from actively engaging students in the evaluation process, scaffolding their learning, fostering self-reflection in decision-making, and facilitating the transfer of acquired skills and concepts to academic contexts and project work. However, there is an opportunity to gain deeper insights into classroom integration of LbE and the factors that may influence the student experience. This study adopts a design-based research approach to analyze LbE within a secondary STEM education setting, with the objective of optimizing classroom integration. By analyzing student comments generated during LbE, the research explores factors shaping the students' learning experiences, examining the extent to which students engage in informed decision-making, offer justifications, and express sentiments throughout the process. Additionally, the study explores how teachers strategically incorporate LbE into their classroom, aligning LbE sessions with curriculum objectives. Findings indicate a diverse pattern of student engagement, sentiments, and decision-making approaches across STEM classrooms. This study contributes to research on LbE by offering insights into the dynamics between teacher implementation and student engagement. The insights gained highlight the potential for refining the effectiveness of LbE within the classroom. Notably, the research emphasizes the significance of how LbE sessions are framed and strategically integrated to enrich the overall educational experience for both students and educators.

In design courses, reviewing how others have solved design problems or completed projects is common practice and often encouraged by educators. Using student work as examples can provide context for assessment criteria and help students approach new design problems. While studies have explored the use of exemplars in various disciplines, little research has focused on which exemplars to use (e.g., high-quality, low-quality) in design, technology, and engineering fields. To address this gap, researchers conducted a literature review of 33 articles on exemplar use in secondary and post-secondary education. The analysis revealed nine themes related to exemplar use and their impact on student learning, including (1) Clarity of instruction, (2) Learner focus, (3) Motivation for learning, (4) Student reflection on learning, (5) Building student self-efficacy, (6) Identifying instructional challenges, (7) Providing contrasting cases, (8) The relationship between exemplar quality and student work quality, and (9) Raising the bar for learning outcomes. Findings suggest that simply providing an exemplar is not enough and that the selection of an exemplar can have positive or negative impacts on student motivation, understanding, and application. Carefully selecting exemplars and engaging in dialogue with students can help them identify expectations, recognize quality work, and identify potential misconceptions. These findings have implications for those involved in design, technology, and engineering education. Educators can use these findings to guide their selection of exemplars and engage students in meaningful dialogue to aid their learning. Researchers can also use these findings to further investigate the use of exemplars in these fields.

The purpose of this study was to determine the influence that a novel, industry-situated, Science, Technology, Engineering, and Mathematics (STEM) Learning Laboratory (STEM Lab) experience may have on students' (ages 10-18) perceptions of manufacturing-related careers as well as to identify any challenges/strategies for the implementation of these informal learning spaces within manufacturing facilities. STEM labs, which are similar to makerspaces, can be defined as physical spaces where students can learn integrated skills and content through hands-on experiences (Roy and Love, 2017). While STEM labs can be found in a variety of settings (e.g., school libraries, museums, or even theme parks), the industry-situated STEM lab that is the focus of this study is a unique application of such a learning environment in an informal space within a manufacturing facility. However, the aim for this specific space is to offer local students an opportunity to see manufacturing, the people that work there, and the skills that might be necessary to pursue a future career in the various aspects of this industry. This type of career awareness and preparation initiative has become an area of interest for manufacturers as they continue to face increasing challenges with attracting employees and confronting negative, potentially outdated, perceptions of manufacturing-related careers. That being said, this research will not attempt to justify the STEM lab initiative, but will instead provide a critical view of this novel context and this type of informal learning environment. This research objective was pursued by interviewing key industry stakeholders and analyzing an existing dataset-consisting of both student surveys and drawing tests-collected by the host manufacturer over the first year of the lab's operation. By triangulating the data gathered from stakeholder interviews and both student surveys and drawing tests, which were collected before and after their experience with the STEM lab at the manufacturing facilities, this research sheds light on the challenges that similar industry-situated learning environments might face, as well as provides opportunities to potentially enhance the experience from both the student and industry perspective.

Classroom research has demonstrated the capacity for significantly influencing student learning by engaging students in evaluation of previously submitted work as an intentional priming exercise for learning; we call this experience "Learning by Evaluating" (LbE). Expanding on current LbE research, we set forth to investigate the impact on student learning by intentionally differing the quality of examples evaluated by the students using adaptive comparative judgement. In this research, university design students (N = 468 students) were randomly assigned to one of three treatment groups; while each group evaluated previously collected student work as an LbE priming activity, the work evaluated by each group differed in quality. Using a three-group experimental design, one group of students only evaluated high quality examples, the second only evaluated low quality examples, and the third group of students evaluated a set of mixed-quality examples of the assignment they were about to work on. Following these LbE priming evaluations, students completed the assigned work and then their projects were evaluated to determine if there was a difference between student performance by treatment condition. Additional qualitative analysis was completed on student LbE rationales to explore similarities and differences in student cognitive judgments based on intervention grouping. No significant difference was found between the groups in terms of achievement, but several differences in group judgement approach were identified and future areas needing investigation were highlighted.

Explicitly incorporating the effects of chemical phenomena such as chemical pretreatment and mineral scaling during the design of treatment systems is critical; however, the complexity of these phenomena and limitations on data have historically hindered the incorporation of detailed water chemistry into the modeling and optimization of water desalination systems. Thus, while qualitative assessments and experimental studies on chemical pretreatment and scaling are abundant in the literature, very little has been done to assess the technoeconomic implications of different chemical pretreatment alternatives within the context of end-to-end water treatment train optimization. In this work, we begin to address this challenge by exploring the impact of pH control during pretreatment on the cost and operation of a high-recovery desalination train. We compare three pH control methods used in water treatment (H2SO4, HCl, and CO2) and assess their impact on the operation of a desalination plant for brackish water and seawater. Our results show that the impact of the acid choice on the cost can vary widely depending on the water source, with CO2 found to be up to 11% and 49% more expensive than HCl in the seawater and brackish cases, respectively. We also find that the acid chemistry can significantly influence upstream processes, with use of H2SO4 requiring more calcium removal in the softening step to prevent gypsum scaling in HPRO system. Our work highlights why incorporating water chemistry information is critical when evaluating the key cost and operational drivers for high-recovery desalination treatment trains.

The stability of fractional Chern insulators is widely believed to be predicted by the resemblance of their single-particle spectra to Landau levels. We investigate the scope of this geometric stability hypothesis by analyzing the stability of a set of fractional Chern insulators that explicitly do not have a Landau level continuum limit. By computing the many-body spectra of Laughlin states in a generalized Hofstadter model, we analyze the relationship between single-particle metrics, such as trace inequality saturation, and many-body metrics, such as the magnitude of the many-body and entanglement gaps. We show numerically that the geometric stability hypothesis holds for Chern bands that are not continuously connected to Landau levels, as well as conventional Chern bands, albeit often requiring larger system sizes to converge for these configurations.

Cost-optimization models are powerful tools for evaluating emerging water treatment processes. However, to date, optimization models do not incorporate detailed chemical reaction phenomena, limiting the assessment of pretreatment and mineral scaling. Moreover, novel approaches for high-salinity and high-recovery desalination are typically proposed without direct quantification of pretreatment needs or mineral scaling. This work addresses a critical gap in the literature by presenting a modeling framework that includes complex water chemistry predictions with process-scale optimization. We use this approach to conduct a technoeconomic assessment on a conceptual high-recovery treatment train that includes chemical pretreatment (i.e., soda ash softening and recarbonation) and membrane-based desalination (i.e., standard and high-pressure reverse osmosis). We demonstrate how to develop and integrate accurate multidimensional surrogate models for predicting precipitation, pH, and mineral scaling tendencies. Our findings show that cost-optimal results balance the costs of pretreatment with reverse osmosis system design. Optimizing across a range of water recoveries (i.e., 50-90%) reveals multiple cost-optimal schemas that vary the chemical dosing in pretreatment and the design and operation of reverse osmosis. Our results reveal that pretreatment costs can be more than double the cost of the primary desalination process at high recoveries due to the extensive pretreatment required to control scaling. This work emphasizes the importance of and provides a framework for including chemistry and mineral scaling predictions in the evaluation of emerging technologies in high-recovery desalination.

Adaptive comparative judgment (ACJ) has been widely used to evaluate classroom artifacts with reliability and validity. In the ACJ experience we examined, students were provided a pair of images related to backpack design. For each pair, students were required to select which image could help them ideate better. Then, they were prompted to provide a justification for their decision. Data were from 15 high school students taking engineering design courses. The current study investigated how students' reasoning differed based on selection. Researchers analyzed the comments in two ways: (1) computer-aided quantitative content analysis and (2) qualitative content analysis. In the first analysis, we performed sentiment analysis and word frequency analysis using natural language processing. Based on the findings, we explored how the design thinking process was embedded in student reasoning, and if the reasoning varied depending on the claim. Results from sentiment analysis showed that students tend to reveal more strong positive sentiment with short comments when providing reasoning for the selected design. In contrast, when providing reasoning for those items not chosen, results showed a weaker negative sentiment with more detailed reasons. Findings from word frequency analysis showed that students valued the function of design as well as the user perspective, specifically, convenience. Additionally, students took aesthetic features of each design into consideration when identifying the best of the two pairs. Within the engineering design thinking context, we found students empathize by identifying themselves as users, define user's needs, and ideate products from provided examples.

Biology is perhaps the most complex of the sciences, given the incredible variety of chemical species that are interconnected in spatial and temporal pathways that are daunting to understand. Their interconnections lead to emergent properties such as memory, consciousness, and recognition of self and non-self. To understand how these interconnected reactions lead to cellular life characterized by activation, inhibition, regulation, homeostasis, and adaptation, computational analyses and simulations are essential, a fact recognized by the biological communities. At the same time, students struggle to understand and apply binding and kinetic analyses for the simplest reactions such as the irreversible first-order conversion of a single reactant to a product. This likely results from cognitive difficulties in combining structural, chemical, mathematical, and textual descriptions of binding and catalytic reactions. To help students better understand dynamic reactions and their analyses, we have introduced two kinds of interactive graphs and simulations into the online educational resource, Fundamentals of Biochemistry, a LibreText biochemistry book. One is available for simple binding and kinetic reactions. The other displays progress curves (concentrations vs. time) for simple reactions and complex metabolic and signal transduction pathways. Users can move sliders to change dissociation and kinetic constants as well as initial concentrations and see instantaneous changes in the graphs. They can also export data into a spreadsheet for further processing, such as producing derivative Lineweaver-Burk and traditional Michaelis-Menten graphs of initial velocity (v[subscript 0]) versus substrate concentration.

The selective modification of nitrogen heteroaromatics enables the development of new chemical tools and accelerates drug discovery. While methods that focus on expanding or contracting the skeletal structures of heteroaromatics are emerging, methods for the direct exchange of single core atoms remain limited. Here, we present a method for 14N → 15N isotopic exchange for several aromatic nitrogen heterocycles. This nitrogen isotope transmutation occurs through activation of the heteroaromatic substrate by triflylation of a nitrogen atom, followed by a ring-opening/ring-closure sequence mediated by 15N-aspartate to effect the isotopic exchange of the nitrogen atom. Key to the success of this transformation is the formation of an isolable 15N-succinyl intermediate, which undergoes elimination to give the isotopically labeled heterocycle. These transformations occur under mild conditions in high chemical and isotopic yields.

Abstract: Climate change is increasing the frequency, severity, and extent of wildfires and drought in many parts of the world, with numerous repercussions for the physical, chemical, and biological characteristics of streams. However, information on how these perturbations affect top predators and their impacts on lower trophic levels in streams is limited. The top aquatic predator in southern California streams is native Oncorhynchus mykiss, the endangered southern California steelhead trout (trout). To examine relationships among the distribution of trout, environmental factors, and stream invertebrate resources and assemblages, we sampled pools in 25 stream reaches that differed in the presence (nine reaches) or absence (16 reaches) of trout over 12 years, including eight reaches where trout were extirpated during the study period by drought or post‐fire flood disturbances. Trout were present in deep pools with high water and habitat quality. Invertebrate communities in trout pools were dominated by a variety of medium‐sized collector–gatherer and shredder invertebrate taxa with non‐seasonal life cycles, whereas tadpoles and large, predatory invertebrates (Odonata, Coleoptera, Hemiptera [OCH]), often with atmospheric breather traits, were more abundant in troutless than trout pools. Structural equation modelling of the algal‐based food web indicated a trophic cascade from trout to predatory invertebrates to collector–gatherer taxa and weaker direct negative trout effects on grazers; however, both grazers and collector–gatherers also were positively related to macroalgal biomass. Structural equation modelling also suggested that bottom‐up interactions and abiotic factors drove the detritus‐based food web, with shredder abundance being positively related to leaf litter (coarse particulate organic matter) levels, which, in turn, were positively related to canopy cover and negatively related to flow. These results emphasise the context dependency of trout effects on prey communities and of the relative importance of top‐down versus bottom‐up interactions on food webs, contingent on environmental conditions (flow, light, nutrients, disturbances) and the abundances and traits of component taxa. Invertebrate assemblage structure changed from a trout to a troutless configuration within a year or two after trout were lost owing to post‐fire scouring flows or drought. Increases in OCH abundance after trout were lost were much more variable after drought than after fire. The reappearance of trout in one stream resulted in quick, severe reductions in OCH abundance. These results indicate that climate‐change induced disturbances can result in the extirpation of a top predator, with cascading repercussions for stream communities and food webs. This study also emphasises the importance of preserving or restoring refuge habitats, such as deep, shaded, perennial, cool stream pools with high habitat and water quality, to prevent the extirpation of sensitive species and preserve native biodiversity during a time of climate change.