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This article examines preservice Spanish teachers' perceptions of linguistic sexism, norm, and use in Spanish. Analysis of 723 participants' answers showed that sexism and linguistic non-adequacy were associated. Results proved that the exclusion of women from the generic masculine in Spanish was considered sexist, and that participants used some Gender Fair Language (GFL) mechanisms to make women visible when deemed necessary, especially with professions. Also, regardless of its adherence to norm, linguistic sexism was perceived as grammatically wrong. Thus, GFL criteria were finding their way into use even if contrary to norm. Therefore, policies based on direct intervention in the training of preservice teachers Spanish as a first language would produce a more egalitarian use of language.

The maritime pine (Pinus pinaster Ait.) is a highly valuable Mediterranean conifer. However, recurrent drought events threaten its propagation and conservation. P. pinaster populations exhibit remarkable differences in drought tolerance. To explore these differences, we analyzed stem transcriptional profiles of grafts combining genotypes with contrasting drought responses under well-watered and water-stress regimes. Our analysis underscored that P. pinaster drought tolerance is mainly associated with constitutively expressed genes, which vary based on genotype provenance. However, we identified key genes encoding proteins involved in water stress response, abscisic acid signaling, and growth control including a PHD chromatin regulator, a histone deubiquitinase, the ABI5-binding protein 3, and transcription factors from Myb-related, DOF NAC and LHY families. Additionally, we identified that drought-tolerant rootstock could enhance the drought tolerance of sensitive scions by regulating the accumulation of transcripts involved in carbon mobilization, osmolyte biosynthesis, flavonoid and terpenoid metabolism, and reactive oxygen species scavenging. These included genes encoding galactinol synthase, CBL-interacting serine/threonine protein kinase 5, BEL1-like homeodomain protein, dihydroflavonol 4-reductase, and 1-deoxy-D-xylulose-5-phosphate. Our results revealed several hub genes that could help us to understand the molecular and physiological response to drought of conifers. Based on all the above, grafting with selected drought-tolerant rootstocks is a promising method for propagating elite recalcitrant conifer species, such as P. pinaster. [ABSTRACT FROM AUTHOR]

The walnut industry in Argentina has grown in recent years, especially in northern Patagonia. However, this expansion has also brought new challenges, including the emergence of diseases threatening the health and productivity of walnut plantations. One of the most important diseases affecting walnut crops worldwide is 'ink disease' or 'walnut dieback'. The aim of this study was to characterize ink disease, identify the aetiological agents, and estimate its incidence in walnut orchards of northern Patagonia, Argentina. Symptomatic trees were observed in the seven surveyed walnut orchards, showing a range of symptoms, including chlorosis and wilting, stem cankers and desiccation. In vivo assay and molecular analyses revealed that not only Phytophthora (P.) but also Phytopythium (Ph.) species are the causal agents of the disease, with P. drechsleri, Ph. mercuriale and Ph. vexans being the most virulent over the commonly used rootstock Juglans hindsii. Notably, Ph. vexans was the most frequently isolated pathogen, suggesting its prevalence and potential impact on the regional walnut industry. Overall, this study provides critical insights into the prevalence and impact of Phytophthora and Phytopythium species on walnut health in northern Patagonia. The presence of multiple pathogenic oomycete species raises concerns about the health of walnut orchards, as well as the potential risk of pathogen transmission to other fruit crops in the region. The findings will help growers to develop better cultural practices and implement measures to guarantee the sustainability of the walnut industry in Patagonia. [ABSTRACT FROM AUTHOR]

Cross-sectional scholarship demonstrates the importance of the U.S. racial structure in precipitating dramatic racial divisions in serious crime across neighborhoods. Yet, we know much less about the degree and sources of racial disparities in how neighborhood crime changes over time, despite considerable evolution in the components of the racial order. We articulate a dynamic racial structural perspective that centers the unfolding nature of residential segregation in producing and altering racially structured socioeconomic realities. We contend that these racialized structural inequalities, in turn, lead neighborhoods on unequal paths of crime change. We assess this perspective with new panel data (circa 2000 and 2010) from the National Neighborhood Crime Study for 7,875 census tracts across 75 cities. Despite considerable socioeconomic upheaval and demographic change during the first decade of the 2000s, we find substantial disparities in neighborhood violence and burglary change that indicate the reproduction of the ethno-racial divide. Furthermore, our dynamic racial structural model explains much of these inequalities in crime change. A dynamic racial structure perspective lays a foundation for understanding the consequences of the evolving U.S. racial structure for unequal exposure to crime across neighborhoods over time. [ABSTRACT FROM AUTHOR]

This paper explores the performance of ChatGPT and GeoGebra Discovery when dealing with automatic geometric reasoning and discovery. The emergence of Large Language Models has attracted considerable attention in mathematics, among other fields where intelligence should be present. We revisit a couple of elementary Euclidean geometry theorems discussed in the birth of Artificial Intelligence and a non-trivial inequality concerning triangles. GeoGebra succeeds in proving all these selected examples, while ChatGPT fails in one case. Our thesis is that both GeoGebra and ChatGPT could be used as complementary systems, where the natural language abilities of ChatGPT and the certified computer algebra methods in GeoGebra Discovery can cooperate in order to obtain sound and—more relevant—interesting results. [ABSTRACT FROM AUTHOR]