Taylor University

In 2023, the Taylor University Archives set out to migrate its digital collections from Microsoft Access to ArchivesSpace. This decision was driven by significant staff changes within the archives and by the imminent risk of total digital collection loss due to the instability of an overburdened Access database. The success of the migration depended heavily on collaboration between the Taylor University Archives, the Private Academic Library Network of Indiana and the Anderson University Archives. This partnership was instrumental in enabling the Taylor University Archives to complete the transfer of its main collection’s data into ArchivesSpace two years ahead of schedule. This paper shares not only the methods used to implement ArchivesSpace but also the benefits of collaborating with other institutions already using the platform. This article is also included in The Business & Management Collection which can be accessed at http:// hstalks/business.

The use of technology in mental health programs has significantly increased access and interaction for users and psychology care. There is a newer platform known as BetterMood that focuses on making user interaction easier and making the registration of users requiring mental health care less complicated. Here, the work of research describes the system architecture of BetterMood, that is, the user registration procedure, and presents a sequence diagram describing the used verification mechanisms. Through the application of a formal validation process, BetterMood guarantees data accuracy and protection, ultimately providing an uninterrupted and trusted user experience. The results demonstrate the significance of clearly defined system interactions in instilling user trust and usability in digital mental health interventions.

Using directly measured cardiorespiratory fitness (i.e. VO2max) in epidemiological/population studies is rare due to practicality issues. As such, predicting VO2max is an attractive alternative. Most equations that predict VO2max adopt additive rather than multiplicative models despite evidence that the latter provides superior fits and more biologically interpretable models. Furthermore, incorporating some but not all confounding variables may lead to inflated mass exponents (∝ M0.75) as in the allometric cascade. Hence, the purpose of the current study was to develop multiplicative, allometric models to predict VO2max incorporating most well-known, but some less well-known confounding variables (FVC, forced vital capacity; FEV1, forced expiratory volume in 1 s) that might provide a more dimensionally valid model (∝ M2/3) originally proposed by Astrand and Rodahl. We adopted the following three-dimensional multiplicative allometric model for VO2max (l⋅min-1) = Mk1·HTk2·WCk3·exp(a + b·age + c·age2 + d·%fat)·ε, (M, body mass; HT, height; WC, waist circumference; %fat, percentage body fat). Model comparisons (goodness-of-fit) between the allometric and equivalent additive models was assessed using the Akaike information criterion plus residual diagnostics. Note that the intercept term 'a' was allowed to vary for categorical fixed factors such as sex and physical inactivity. Analyses revealed that significant predictors of VO2max were physical inactivity, M, WC, age2, %fat, plus FVC, FEV1. The body-mass exponent was k1 = 0.695 (M0.695), approximately∝M2/3. However, the calculated effect-sizes identified age2 and physical inactivity, not mass, as the strongest predictors of VO2max. The quality-of-fit of the allometric models were superior to equivalent additive models. Results provide compelling evidence that multiplicative allometric models incorporating FVC and FEV1 are dimensionally and theoretically superior at predicting VO2max(l⋅min-1) compared with additive models. If FVC and FEV1 are unavailable, a satisfactory model was obtained simply by using HT as a surrogate.

African American (AA) women are disproportionately affected by hypertension. Discrimination, which can be traumatic, and depressive symptoms are independently associated with blood pressure (BP). We assessed whether the combined influence of discrimination and race-related trauma and depressive symptoms influenced BP over time. We conducted a secondary data analysis of data from a longitudinal cohort study examining factors associated with BP in 250 AA/Black mother-child dyads. Eligible participants were AA/Black mothers, 21 years and older, with a biological child aged 3-5 years. Clinical (BP, body mass index) and psychosocial measures (racial discrimination, major discrimination, race-related stress, depressive symptoms) were examined. Principal component analysis and linear regression were completed to assess the associations of discrimination, race-related trauma, and depressive symptoms with maternal BP. Data from 183 participants were analyzed. Principal component analysis identified 2 key components: overall discrimination and race-related trauma (principal component 1) and depressive symptoms (principal component 2), which explained 83% of data variation. Linear regression analyses revealed principal component 1 was associated with changes in systolic BP (b = 0.92; P = .04), whereas principal component 2 was not (b = 0.31; P = .71). Our findings highlight the need to further explore experiences of discrimination and race-related trauma as a contributing factor for hypertension. In addition, building on existing efforts, future studies should further analyze the presentation of depressive symptoms among AA women to inform the development and validation of culturally sensitive screening tools that effectively capture these symptoms and enhance access to care.

The two terms of our title have long been destined for each other but, in the style of a Hollywood romantic comedy, have taken their sweet time to merge in an embrace. This special issue wants to be a setting for such a moment. We come into this with a double-pronged hypothesis: that “Beat time” is queer time, as it disrupts and rearranges the chronological patterns of straight society, and that recent critical work on queer temporality—the particular rhythms and tempos of queer minorities—c...

Differential Privacy (DP) has become a crucial framework for preserving data privacy, especially in the field of Natural Language Processing (NLP). This survey provides a comprehensive overview of existing DP applications in NLP, focusing on key aspects such as application scenario classification, diversity of privacy mechanisms, utility-performance trade-offs, data granularity, empirical studies versus theoretical analysis, and emerging challenges with future directions.

This article explores the conundrum of biofilm formation in orthodontics, its impact on oral health, and the role of the bonding procedure. Biofilms are resilient structures formed through stages like attachment, adhesion, growth, and maturation, with the extracellular matrix (EPS) playing a vital role. The bonding procedure unintentionally creates surfaces where bacteria thrive, leading to biofilm development. Factors like oral hygiene, diet, and bracket design influence biofilm formation. Maintaining oral hygiene during orthodontic treatment can be challenging due to food trapping and cleaning difficulties. Strategies to minimize biofilms involve patient education, improved bonding techniques, and antimicrobial agents. Biofilms can lead to dental decay, gingivitis, periodontitis, and white spot lesions. Combating biofilms requires collaboration, patient education, and ongoing research. Improved management can lead to better oral health outcomes for orthodontic patients.