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This music score was submitted for Resonate 2024: An Open Access Call for Scores by the UCLA Music Library with Bent Frequency and Jan Berry Baker.

This music score was submitted for Resonate 2024: An Open Access Call for Scores by the UCLA Music Library.

This article proposes ways to authentically amplify writer's workshop for emergent bilinguals. Through the study of one bilingual teacher's mediation in teaching, we examined the affordances that translanguaging and transmodal practices have for emergent bilingual students' writing processes. In this case study, we focused on a writing sequence associated with the well-known Latin American holiday of the Day of the Dead, in which 3rd grade emergent bilinguals wrote "calaveras," or literary poems, as part of an interdisciplinary language arts and social studies lesson. Our work is framed by sociocultural theories of mediation, literacy, and language. Under a multiliteracies pedagogy, we observed how a bilingual teacher and emergent bilinguals negotiate meaning through a variety of linguistic and multimodal resources. In our interactional analysis of talk, we found how the teacher mediated background knowledge and vocabulary as a part of the writing process; we also identified ways in which her mediation included extensive scaffolding as she provided linguistic and disciplinary knowledge needed to write calaveras. Through integrating the tenets of mediation with biliteracy, multiliteracies, and translanguaging pedagogies, this study offers a promising example of how teachers can build a culturally-sustaining writers' workshop to support emergent bilingual learners' language development and writing practices.

Background: Contamination and transmission of different Listeria monocytogenes strains along food chain are a serious threat to public health and food safety. Understanding the distribution of diseases in time and space-time is fundamental in the epidemiological study and in preventive medicine programs. The aim of this study is to estimate listeriosis incidence along 10-years period and to perform space-time cluster analysis of listeriosis cases in Marche Region, Italy. Methods: The number of observed listeriosis cases/year was derived from regional data of surveillance of notifiable diseases and hospital discharge form. The capture and recapture method (C-R method) was applied to estimate the real incidence of listeriosis cases in Marche Region and the space-time scan statistics analysis was performed to detect clusters of space-time of listeriosis cases and add precision to the conventional epidemiological analysis. Results: The C-R method estimation of listeriosis cases was 119 in the 10- year period (2010–2019), with an average of 31.93 % of unobserved cases (lost cases). The estimated mean annual incidence of listeriosis was 0.77 per 100,000 inhabitants (95 %CI 0.65–0.92), accounting for 6.07 % of additional listeriosis cases per year than observed cases. Using the scan statistic, the two most likely clusters were identified, one of these was statistically significant (p

The surging demand for donkey milk has led to a stronger focus on donkey husbandry and reproductive management, particularly in the peripartum period. Techniques to predict parturition are needed to avoid losses due to dystocias, which are frequently related to unattended foaling. In mares, pH and electrolyte analyses of pre-colostrum are used to predict parturition with a good accuracy. The purpose of this study was to evaluate the pH of the mammary secretion using both a pH metre and test strips and the electrolytes (Na+, K + and Ca2+) in the mammary gland secretions of 9 jennies during the 5 days preceding parturition, to understand if the trends of these cations were comparable to those of the mare and to identify possible markers/thresholds of impending parturition. Ca2+ concentrations increased in the days before delivery from day −2 (p

This qualitative case study (Yin, [2014]. "Case Study Research: Design and Methods." 5th Ed. Thousand Oaks, CA: Sage.) emerged from our effort to support teachers, who predominantly identify as monolingual speakers, in learning about translanguaging through a less-explored facet of translanguaging: multimodality. Drawing upon Bezemer and Kress's (2016) social semiotic framework for multimodal analysis and Lin's, [2019]. "Theories of Trans/Languaging and Trans-Semiotizing: Implications for Content-Based Education Classrooms." "International Journal of Bilingual Education and Bilingualism" 22 (1): 5-16. doi:10.1080/13670050.2018.1515175.) Multimodalities Entextualization Cycle (MEC), we ask: 'What did integration of multimodal resources contribute to pre- and in-service teachers' learning about translanguaging in an online asynchronous course within an English as a Second Language teacher education program at a Midwest U.S. university?' Through multimodal analysis (Jewitt 2017), we analyzed the texts teachers created in response to four multimodal tasks; this included analyzing semiotic meaning conveyed through the multiple modes teachers integrated in their responses. We also compared broader patterns in their cumulative learning about translanguaging as a part of an MEC. Our findings suggest that envisioning a cycle of multimodal learning tasks can provide predominantly monolingual-identifying teachers with means to expand their own dynamic repertoires as they make sense of translanguaging. We conclude with recommendations for how language teacher educators can harness multimodal resources to expand teachers' capacity to enact translanguaging as an equity-based pedagogy of hope. (194 words)

Drawing upon tenets of Critical Multilingual Language Awareness (CMLA), we analyzed multimodal compositions created by preservice teachers (PSTs) from two institutions to investigate their meaning-making at the nexus of language, identity, and power. Through analysis of PSTs' multimodal compositions, reflective writing about their coursework, and retrospective interviews, participants shared how these compositions informed their working understandings of CMLA in relation to monoglossic and raciolinguistic language ideologies. Findings from our study suggest that through multimodal composition, PSTs demonstrated varied levels of awareness that one's language practices determine whether they experience acceptance, belonging, and access to education; some PSTs also acknowledged that teachers serve as adjudicators of language, who may reinforce or reject hegemonic language ideologies. This study reinforces the efficacy of integrating opportunities for PSTs to represent their learning through multimodal composition to foster their CMLA.

To better prepare future teachers for an increasingly linguistically diverse student population, teacher education programs have integrated critical language awareness frameworks into their coursework. However, re­search on the influence of such coursework on teachers' critical multilingual awareness is scarce. Given the importance of developing teachers' critical multilingual language awareness (CMLA), this case study explores the impact of experience and course work on a novice language teacher educator and a pre-service teacher's emerging CMLA at a large Mid­western U.S. university. It gauges teachers' evolving awareness of the five CMLA domains (cognitive, social, affective, performance and power), with a particular focus on the power domain. Based on an iterative and recursive qualitative analysis of interview and course artifact data, this study shows that teachers are able to develop CMLA through coursework, especially if they are able to link it to personal experiences. Furthermore, a deep understanding of the power domain of language builds on: (1) an awareness of the other domains of CMLA--in particular the affective and social domains--and (2) the ways these domains impact English learners' equitable access to educational opportunities.

This work analyzed the volume fraction of the sigma phase in a superduplex stainless steel UNS S32760. Two electrochemical testing methodologies were applied for this purpose. Firstly the DL-EPR test was performed in three different electrolytic solutions. The LSV-KOH test was also used, a recent methodology proposal for analyzing these alloys. Seven specimens were solution annealed at 1100 °C for 60 min and heat-treated at 850 and 950 °C for 5, 20, and 60 min to promote the formation of different fractions of the sigma phase. The sigma phase volume fraction present in these specimens was determined by quantitative metallography. The DL-EPR analyses in all three conditions proved to be limited in quantifying the sigma phase, especially in specimens heat-treated at 950 °C. On the other hand, from the analyses with the LSV-KOH technique, it was possible to construct a reference curve between the sigma volume fractions and the electrochemical response of the LSV-KOH test (charge density), obtaining a linear regression coefficient of 0.97. This curve can then be applied to quantify the sigma phase. For comparison, the best regression coefficient obtained for DL-EPR was 0.53. Accompanied by the quantitative analysis, a qualitative analysis of the sigma phase can be made from a deeper analysis of the LSV-KOH voltammograms. In these analyses, it was possible to infer whether the sigma phase morphology is lamellar or in blocks. From the results obtained, it was possible to show that the LSV-KOH test is more precise in quantifying the sigma phase and allows a morphological analysis.

Abstract The prognosis of renal cell carcinoma (RCC) malignant neoplasms deeply relies on an accurate determination of the histological subtype, which currently involves the light microscopy visual analysis of histological slides, considering notably tumor architecture and cytology. RCC subtyping is therefore a time-consuming and tedious process, sometimes requiring expert review, with great impact on diagnosis, prognosis and treatment of RCC neoplasms. In this study, we investigate the automatic RCC subtyping classification of 91 patients, diagnosed with clear cell RCC, papillary RCC, chromophobe RCC, or renal oncocytoma, through deep learning based methodologies. We show how the classification performance of several state-of-the-art Convolutional Neural Networks (CNNs) are perfectible among the different RCC subtypes. Thus, we introduce a new classification model leveraging a combination of supervised deep learning models (specifically CNNs) and pathologist’s expertise, giving birth to a hybrid approach that we termed ExpertDeepTree (ExpertDT). Our findings prove ExpertDT’s superior capability in the RCC subtyping task, with respect to traditional CNNs, and suggest that introducing some expert-based knowledge into deep learning models may be a valuable solution for complex classification cases.

BackgroundPrevious studies have demonstrated that solid organ transplant (SOT) patients undergoing primary total knee arthroplasty (TKA) are at an increased risk of postoperative complications. The purpose of this study is to utilize a large, national database to investigate revision TKA (rTKA) outcomes in SOT patients.MethodsThis was a retrospective review utilizing the Nationwide Readmissions Database (NRD) and ICD-9 codes to identify patients who underwent rTKA from 2010-2014 with a history of at least one SOT. Propensity-score-matching (PSM) was used to compare rTKA outcomes in SOT patients compared to matched patients without SOT.ResultsA total of 303,867 rTKAs, with 464 of those being performed in SOT patients, were included in the study. Of these, 71,903 and 182 were performed for PJI in non-SOT and SOT patients, respectively. rTKA was performed most frequently in kidney transplant patients (53.0%) followed by liver transplant patients (34.3%). For non-PJI patients, SOT patients had a higher 90-day readmission rate than matched non-SOT rTKA patients (23.2% vs 12.6%, p = 0.006). However, there were no differences in 90-day readmission rates for specific rTKA complications, subsequent revision rTKA, or mortality. Among patients undergoing rTKA for PJI, there was no difference in overall 90-day readmission rate, readmission for specific rTKA complications, subsequent revision rTKA, or mortality.ConclusionsWhile the increased medical comorbidities associated with SOT place patients at increased risk for complications following rTKA, it appears that SOT alone does not do so when patients are matched based on overall medical comorbidity.