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Perceptions of Own and Others\u27 Skin Tones, Colorism, and Ethnic Identity with South Asian American Emerging Adults
No full textThe present mixed-methods study aimed to examine whether one�s own perceived skin tone and skin tone satisfaction were related to in-group colorism and ethnic identity among a sample of 472 second-generation South Asian American emerging adults aged 18-29 years old. The influences of gender identity on these constructs and their interrelationships were also explored. Quantitative analyses conducted via structural equation modeling (SEM) found that greater skin tone satisfaction was a significant predictor of stronger ethnic identity, a relationship that was stronger for men than women. One�s own perceived skin tone was not a significant predictor of ethnic identity or in-group colorism and was not significantly correlated to skin tone satisfaction. Qualitative analyses using a discovery-oriented approach demonstrated preliminary evidence for the skin tone paradox. The most common self-descriptions of skin tone were lighter-skinned and brown. Ethnic identification and belonging, as well as positive skin tone experiences, were the most frequently shared reasons for skin tone satisfaction level. Participants reported general positive perceptions and experiences and an increased sense of belonging with others of their ethnicity were the most common influences of skin tone on ethnic identity. Areas of quantitative and qualitative convergence include (1) skin tone satisfaction as a salient factor influencing ethnic identity, (2) importance of ethnic identity endorsement, and (3) no influence of gender identity on skin tone perceptions, which corroborates quantitative non-significant findings. Areas of divergence include (1) differences in self-descriptions of one�s own perceived skin tone and (2) an endorsement of skin tone acceptance rather than a desire to change skin tone. The cross-validation of findings are discussed, as well as future directions and practical implications
Encouraging Racial Justice: How Learning about Historic Black-White Allyship can Disrupt White Americans\u27 Disinvestment from Racial Injustice Communication
No full textAbstractWhite Americans often feel blamed when they receive communication about racial injustice. This felt blame often leads them to reject racial injustice communicators and their messages, hindering antiracist action that might have sparked as a result of the communication. White Americans� attitudes about racial injustice are also driven by political ideology, as they are more likely to want to avoid communication about racial injustice the more they lean conservative. White Americans increasingly defensively reject racial injustice communicators the more they perceive blame from the racial injustice communication; I conceptualise this phenomenon as the Blame� Disinvestment effect. In three studies, I showed that learning about historic Black-White antiracist allyship (vs control) disrupts the Blame�Disinvestment effect. Study 1 established evidence of the Blame�Disinvestment effect and then showed that the Black-White allyship intervention reduces the extent to which White Americans defensively reject high blame intensity racial injustice communicators and increases their willingness to perform antiracist actions. Study 2 replicated the findings of Study 1 and showed that for conservatives - but not liberals - the efficacy of the Black-White allyship intervention was driven by its power to increase White Americans� feelings of moral elevation and activate within them an allyship identity. In Study 3, I investigated the efficacy of the intervention combined with ingroup allyship norms and found tha
Coordination Stoichiometry Effects on the Binding Hierarchy of Histamine and Imidazole–M <sup>2+</sup> Complexes
No full textHistidine–M 2+ coordination bonds are a recognized bond motif in biogenic materials with high hardness and extensibility, which has led to growing interest in their use in soft materials for mechanical function. However, the effect of different metal ions on the stability of the coordination complex remains poorly understood, complicating their implementation in metal‐coordinated polymer materials. Herein, rheology experiments and density functional theory calculations are used to characterize the stability of coordination complexes and establish the binding hierarchy of histamine and imidazole with Ni 2+ , Cu 2+ , and Zn 2+ . It is found that the binding hierarchy is driven by the specific affinity of the metal ions to different coordination states, which can be macroscopically tuned by changing the metal‐to‐ligand stoichiometry of the metal‐coordinated network. These findings facilitate the rational selection of metal ions for optimizing the mechanical properties of metal‐coordinated materials
Characterization of novel recombinant mycobacteriophages derived from homologous recombination between two temperate phages
No full textAbstract
Comparative analyses of mycobacteriophage genomes reveals extensive genetic diversity in genome organization and gene content, contributing to widespread mosaicism. We previously reported that the prophage of mycobacteriophage Butters (cluster N) provides defense against infection by Island3 (subcluster I1). To explore the anti-Island3 defense mechanism, we attempted to isolate Island3 defense escape mutants on a Butters lysogen, but only uncovered phages with recombinant genomes comprised of regions of Butters and Island3 arranged from left arm to right arm as Butters-Island3-Butters (BIBs). Recombination occurs within two distinct homologous regions that encompass lysin A, lysin B, and holin genes in one segment, and RecE and RecT genes in the other. Structural genes of mosaic BIB genomes are contributed by Butters while the immunity cassette is derived from Island3. Consequently, BIBs are morphologically identical to Butters (as shown by transmission electron microscopy) but are homoimmune with Island3. Recombinant phages overcome antiphage defense and silencing of the lytic cycle. We leverage this observation to propose a stratagem to generate novel phages for potential therapeutic use.</jats:p
An AI-based intervention for improving undergraduate STEM learning
No full textWe present results from a small-scale randomized controlled trial that evaluates the impact of just-in-time interventions on the academic outcomes of N = 65 undergraduate students in a STEM course. Intervention messaging content was based on machine learning forecasting models of data collected from 537 students in the same course over the preceding 3 years. Trial results show that the intervention produced a statistically significant increase in the proportion of students that achieved a passing grade. The outcomes point to the potential and promise of just-in-time interventions for STEM learning and the need for larger fully-powered randomized controlled trials.</jats:p
Effect of Urea-Calcium Sulfate Cocrystal Nitrogen Fertilizer on Sorghum Productivity and Soil N2O Emissions
No full textUrea cocrystal materials have recently emerged as high nitrogen (N) content fertilizers with low solubility capable of minimizing N loss and improving their use efficiency. However, their effects on crop productivity and N2O emissions remain underexplored. A greenhouse study was designed to evaluate sorghum (Sorghum bicolor (L.) Moench) yield, N uptake, and N2O emissions under six N treatments: C0 (without fertilizer), UR100 (urea), UC100 (CaSO4‚ãÖ4urea cocrystal) at 150 kg N ha‚àí1, and CaSO4‚ãÖ4urea cocrystal at 40%, 70%, and 130% of 150 kg N ha‚àí1 (UC40, UC70, and UC130, respectively). The results demonstrated that UR100, UC100, and UC130 had 51.4%, 87.5%, and 91.5% greater grain yields than the control. The soil nitrate and sulfur concentration, N uptake, and use efficiency were the greatest in UC130, while UR100 had significantly greater N2O loss within the first week of N application than the control and all the urea cocrystal treatments. UC130 minimized the rapid N loss in the environment as N2O emissions shortly after fertilizer application. Results of this study suggest the positive role of urea cocrystal in providing a balanced N supply and increasing crop yield in a more environmentally friendly way than urea alone. It could be good alternative fertilizer to minimize N loss as N2O emissions and significantly increase the N use efficiency in sorghum.</jats:p
Influence of the Grain-Flow Orientation after Hot Forging Process Evaluated through Rotational Flexing Fatigue Test
No full textThe hot forging process brings significant advantages in terms of improved mechanical properties of the part compared with other processes, such as casting or machining. The metal flow in the forging process leads to texture modifications and can be macroscopically visualized by the so-called grain-flow orientation (GFO). This study showed the effect of GFO on fatigue life by using a rotational flexing fatigue test. The tests that were performed using SAE 1045H steel material, at rolling and transverse directions, showed the influence of GFO on the specimens’ mechanical properties compared with the reference samples taken from the machined rolled bar. The experimental results showed that the forged samples with the GFO in the main deformation direction presented a higher fatigue life than the other tested configurations.</jats:p
Single-Cell Classification Based on Population Nucleus Size Combining Microwave Impedance Spectroscopy and Machine Learning
No full textMany recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorporated into image analysis for improving this process. Recently, impedance spectrometers have been shown to generate all-inclusive lab-on-a-chip platforms to detect nucleus abnormities. In this paper, a wideband electrical sensor and data analysis paradigm that can identify nuclear changes shows the realization of a single-cell microfluidic device to detect nuclei of altered sizes. To model cells of altered nucleus, Jurkat cells were treated to enlarge or shrink their nucleus followed by broadband sensing to obtain the S-parameters of single cells. The ability to deduce important frequencies associated with nucleus size is demonstrated and used to improve classification models in both binary and multiclass scenarios, despite a heterogeneous and overlapping cell population. The important frequency features match those predicted in a double-shell circuit model published in prior work, demonstrating a coherent new analytical technique for electrical data analysis. The electrical sensing platform assisted by ML with impressive accuracy of cell classification looks forward to a label-free and flexible approach to cancer diagnosis.</jats:p
