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A plethora of research has identified that undergraduate students experience higher levels of general anxiety disorder (GAD) with questionnaires primarily being used diagnose students. However, the potential for linguistic analysis and the emotional Stroop test as measurements of GAD remains unexplored, especially if both were to be used together. The present study aimed to produce a novel measure of GAD using both linguistic measures and the emotional Stroop task. This research study employed a quantitative approach and an experimental research design. A volunteer sample of 17 undergraduate students completed an online questionnaire, a written task, and an emotional Stroop task distributed via social media and the University of Birmingham Research Participation Scheme. This study produced a novel questionnaire for GAD and was utilised as a baseline measure. This study used two independent T-tests to measure the overall sentiment of written responses of participants and the frequency of first-person singular pronouns in written response. Additionally, two independent T-tests were used to measure reaction times and accuracy on the emotional Stroop Task. The findings highlighted no statistical differences between higher and lower levels of GAD and linguistic responses and reaction times and accuracy on the emotional Stroop test, suggesting that the measures utilised in the present study may not be able to predict GAD. As such, the findings of this study underscore the complexity of GAD and extend our understanding of GAD measurements. By illuminating the emotional, behavioural and cognitive factors of GAD, this study advocates for more awareness in university settings and proactive support for undergraduate students.

Medium- and high-entropy alloys (M/HEAs) mix several principal elements with near-equiatomic composition and represent a model-shift strategy for designing previously unknown materials in metallurgy1-8, catalysis9-14 and other fields15-18. One of the core hypotheses of M/HEAs is lattice distortion5,19,20, which has been investigated by different numerical and experimental techniques21-26. However, determining the three-dimensional (3D) lattice distortion in M/HEAs remains a challenge. Moreover, the presumed random elemental mixing in M/HEAs has been questioned by X-ray and neutron studies27, atomistic simulations28-30, energy dispersive spectroscopy31,32 and electron diffraction33,34, which suggest the existence of local chemical order in M/HEAs. However, direct experimental observation of the 3D local chemical order has been difficult because energy dispersive spectroscopy integrates the composition of atomic columns along the zone axes7,32,34 and diffuse electron reflections may originate from planar defects instead of local chemical order35. Here we determine the 3D atomic positions of M/HEA nanoparticles using atomic electron tomography36 and quantitatively characterize the local lattice distortion, strain tensor, twin boundaries, dislocation cores and chemical short-range order (CSRO). We find that the high-entropy alloys have larger local lattice distortion and more heterogeneous strain than the medium-entropy alloys and that strain is correlated to CSRO. We also observe CSRO-mediated twinning in the medium-entropy alloys, that is, twinning occurs in energetically unfavoured CSRO regions but not in energetically favoured CSRO ones, which represents, to our knowledge, the first experimental observation of correlating local chemical order with structural defects in any material. We expect that this work will not only expand our fundamental understanding of this important class of materials but also provide the foundation for tailoring M/HEA properties through engineering lattice distortion and local chemical order.

Emotion is closely associated with language, but we know very little about how children express emotion in their own writing. We used a large-scale, cross-sectional, and data-driven approach to investigate emotional expression via writing in children of different ages, and whether it varies for boys and girls. We first used a lexicon-based bag-of-words approach to identify emotional content in a large corpus of stories (N>100,000) written by 7- to 13-year-old children. Generalized Additive Models were then used to model changes in sentiment across age and gender. Two other machine learning approaches (BERT and TextBlob) validated and extended these analyses, converging on the finding that positive sentiments in children's writing decrease with age. These findings echo reports from previous studies showing a decrease in mood and an increased use of negative emotion words with age. We also found that stories by girls contained more positive sentiments than stories by boys. Our study shows the utility of large-scale data-driven approaches to reveal the content and nature of children's writing. Future experimental work should build on these observations to understand the likely complex relationships between written language and emotion, and how these change over development.

Advances in immunotherapy in the last decade have revolutionized treatment paradigms across multiple cancer diagnoses. However, only a minority of patients derive durable benefit and progress with traditional approaches, such as cancer vaccines, remains unsatisfactory. A key to overcoming these barriers resides with a deeper understanding of tumor antigen presentation and the complex and dynamic heterogeneity of tumor-infiltrating antigen-presenting cells (APCs). Reminiscent of the 'second touch' hypothesis proposed by Klaus Ley for CD4+ T cell differentiation, the acquisition of full effector potential by lymph node- primed CD8+ T cells requires a second round of co-stimulation at the site where the antigen originated, i.e. the tumor bed. The tumor stroma holds a prime role in this process by hosting specialized APC niches, apparently distinct from tertiary lymphoid structures, that support second antigenic touch encounters and CD8+ T cell effector proliferation and differentiation. We propose that APC within second-touch niches become licensed for co-stimulation through stromal-derived instructive signals emulating embryonic or wound-healing provisional matrix remodeling. These immunostimulatory roles of stroma contrast with its widely accepted view as a physical and functional 'immune barrier'. Stromal control of antigen presentation makes evolutionary sense as the host stroma-tumor interface constitutes the prime line of homeostatic 'defense' against the emerging tumor. In this review, we outline how stroma-derived signals and cells regulate tumor antigen presentation and T-cell effector differentiation in the tumor bed. The re-definition of tumor stroma as immune rheostat rather than as inflexible immune barrier harbors significant untapped therapeutic opportunity.