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Acute Lymphoblastic Leukemia (ALL) is a life-threatening type of cancer wherein mortality rate is unquestionably high. Early detection of ALL can reduce both the rate of fatality as well as improve the diagnosis plan for patients. In this study, we developed the ALL Detector (ALLD), which is a deep learning-based network to distinguish ALL patients from healthy individuals based on blast cell microscopic images. We evaluated multiple DL-based models and the ResNet-based model performed the best with 98% accuracy in the classification task. We also compared the performance of ALLD against state-of-the-art tools utilized for the same purpose, and ALLD outperformed them all. We believe that ALLD will support pathologists to explicitly diagnose ALL in the early stages and reduce the burden on clinical practice overall. © 2022 The authors and IOS Press.

Black women faculty and administrators in the United States are tackling a force of socioeconomic and racial disparities, emotional tolls and invisible burdens within academia, political turmoil, social unrest, and public health crises. COVID-19 has added an additional layer related to work responsibilities, the overall well-being of Black women faculty and administrators and the diverse students they encounter, and management of work and home responsibilities. This paper discusses perspectives and evidence-based strategies regarding Black women faculty and administrators who navigate academia and teach during times of COVID-19 and social unrest. We also outline strategies for university leaders to mitigate cultural and racial gaps in the classroom or workplace and foster diversity and inclusion in academia. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

E-commerce giants like Amazon rely on consumer reviews to allow buyers to inform other potential buyers about a product’s pros and cons. While these reviews can be useful, they are less so when the number of reviews is large; no consumer can be expected to read hundreds or thousands of reviews in order to gain better understanding about a product. In an effort to provide an aggregate representation of reviews, Amazon offers an average user rating represented by a 1- to 5-star score. This score only represents how reviewers feel about a product without providing insight into why they feel that way. In this work, we propose an AI technique that generates an easy-to-read, concise summary of a product based on its reviews. It provides an overview of the different aspects reviewers emphasize in their reviews and, crucially, how they feel about those aspects. Our methodology generates a list of the topics most-mentioned by reviewers, conveys reviewer sentiment for each topic and calculates an overall summary score that reflects reviewers’ overall sentiment about the product. These sentiment scores adapt the same 1- to 5-star scoring scale in order to remain familiar to Amazon users. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Josiassen (2011) in a single cross-sectional survey investigated causal relations between consumer disidentification and domestic product judgments. The primary purpose of this replication paper is to evaluate the reliabilities of construct levels, as well as the significance, direction and magnitude of causal effects advanced in the original published structural model. The study measures relations between consumer disidentification (CDI) and domestic product judgments of American products over an extended 16 months period among second generation immigrants. In the present research the original CDI model fit was found to be longitudinally consistent and stable. Serendipitously, findings of the present study disclosed that over time baseline levels of consumer disidentification vary and actually declined significantly. Additionally, the negative effect of consumer disidentification on American product judgments significantly weakened over the course of the study. As an additional test of consumer predisposition reliability over time, the model in this study incorporated consumer xenocentrism (XEN) as a second predictor variable of domestic product judgments. Findings of this analysis were consistent with those found for CDI. These new phenomena have important theoretical and managerial implications. © 2022, University of South Australia. All rights reserved.

Dual-energy X-ray absorptiometry (DXA) has been traditionally used to assess body composition covering bone, fat and muscle content. Cardiovascular disease (CVD) has deleterious effects on bone health and fat composition. Therefore, early detection of bone health, fat and muscle composition would help to anticipate a proper diagnosis and treatment plan for CVD patients. In this study, we leveraged machine learning (ML)-based models to predict CVD using DXA, demonstrating that it can be considered an innovative approach for early detection of CVD. We leveraged state-of-the-art ML models to classify the CVD group from non-CVD group. The proposed logistic regression-based model achieved nearly 80% accuracy. Overall, the bone mineral density, fat content, muscle mass and bone surface area measurements were elevated in the CVD group compared to non-CVD group. Ablation study revealed a more successful discriminatory power of fat content and bone mineral density than muscle mass and bone areas. To the best of our knowledge, this work is the first ML model to reveal the association between DXA measurements and CVD in the Qatari population. We believe this study will open new avenues of introducing DXA in creating the diagnosis and treatment plan of cardiovascular diseases. © 2022 The authors and IOS Press.

We report on the measurements of directed flow v1 and elliptic flow v2 for hadrons (π±, K±, KS0, p, ϕ, Λ and Ξ−) from Au+Au collisions at sNN=3 GeV and v2 for (π±, K±, p and p‾) at 27 and 54.4 GeV with the STAR experiment. While at the two higher energy midcentral collisions the number-of-constituent-quark (NCQ) scaling holds, at 3 GeV the v2 at midrapidity is negative for all hadrons and the NCQ scaling is absent. In addition, the v1 slopes at midrapidity for almost all observed hadrons are found to be positive, implying dominant repulsive baryonic interactions. The features of negative v2 and positive v1 slope at 3 GeV can be reproduced with a baryonic mean-field in transport model calculations. These results imply that the medium in such collisions is likely characterized by baryonic interactions. © 2022 The Author(s)

In high-energy heavy-ion collisions, partonic collectivity is evidenced by the constituent quark number scaling of elliptic flow anisotropy for identified hadrons. A breaking of this scaling and dominance of baryonic interactions is found for identified hadron collective flow measurements in sNN = 3 GeV Au+Au collisions. In this paper, we report measurements of the first- and second-order azimuthal anisotropic parameters, v1 and v2, of light nuclei (d, t, 3He, 4He) produced in sNN = 3 GeV Au+Au collisions at the STAR experiment. An atomic mass number scaling is found in the measured v1 slopes of light nuclei at mid-rapidity. For the measured v2 magnitude, a strong rapidity dependence is observed. Unlike v2 at higher collision energies, the v2 values at mid-rapidity for all light nuclei are negative and no scaling is observed with the atomic mass number. Calculations by the Jet AA Microscopic Transport Model (JAM), with baryonic mean-field plus nucleon coalescence, are in good agreement with our observations, implying baryonic interactions dominate the collective dynamics in 3 GeV Au+Au collisions at RHIC. © 2022 The Author

Measurement by the STAR experiment at RHIC of the cold nuclear matter (CNM) effects experienced by inclusive J/ψ at mid-rapidity in 0-100% p+Au collisions at sNN = 200 GeV is presented. Such effects are quantified utilizing the nuclear modification factor, RpAu, obtained by taking a ratio of J/ψ yield in p+Au collisions to that in p+p collisions scaled by the number of binary nucleon-nucleon collisions. The differential J/ψ yield in both p+p and p+Au collisions is measured through the dimuon decay channel, taking advantage of the trigger capability provided by the Muon Telescope Detector in the RHIC 2015 run. Consequently, the J/ψ RpAu is derived within the transverse momentum (pT) range of 0 to 10 GeV/c. A suppression of approximately 30% is observed for pT<2 GeV/c, while J/ψ RpAu becomes compatible with unity for pT greater than 3 GeV/c, indicating the J/ψ yield is minimally affected by the CNM effects at high pT. Comparison to a similar measurement from 0-20% central Au+Au collisions reveals that the observed strong J/ψ suppression above 3 GeV/c is mostly due to the hot medium effects, providing strong evidence for the formation of the quark-gluon plasma in these collisions. Several model calculations show qualitative agreement with the measured J/ψ RpAu, while their agreement with the J/ψ yields in p+p and p+Au collisions is worse. © 2022 The Author(s)

We report a new measurement of the production cross section for inclusive electrons from open heavy-flavor hadron decays as a function of transverse momentum (pT) at midrapidity (|y|¡0.7) in p+p collisions at s=200 GeV. The result is presented for 2.5¡pT¡10 GeV/c with an improved precision above 6 GeV/c with respect to the previous measurements, providing more constraints on perturbative QCD calculations. Moreover, this measurement also provides a high-precision reference for measurements of nuclear modification factors for inclusive electrons from open-charm and -bottom hadron decays in heavy-ion collisions. © 2022 American Physical Society.

Research data collected from single respondents may raise concerns regarding common method variance (CMV), which is believed to threaten the validity of findings. The primary concern is that CMV can inflate substantive relationships, such that they appear statistically significant when they are not. Thus, understanding the nature of CMV is critical, especially when one considers the popularity—and sometimes necessity—of using self-report data. Research examining CMV has found conflicting evidence about the impact of CMV. Researchers who believe CMV influences findings have proposed solutions to combat any real or perceived potential bias, including changing survey instructions and using marker variables, but few studies have examined the efficacy of these approaches. The purpose of this study is to examine the impact of these techniques and the nature of CMV using an experimental design. To conduct the experiment, multiple versions of a survey, which vary in their use of the remedial approaches, are utilized to collect data, which resulted in 1,069 usable responses. The experimental design was based on the faking literature and included instructions intended to induce or reduce the levels of CMV. Further, two different marker variables are used to determine the degree to which they create a psychological separation in substantive variables. Correlation analysis and measurement invariance are used to analyze the data. This study posits that, if CMV is a substantial concern for self-report data and these approaches are effective, then findings will differ in surveys that incorporate such approaches from surveys that do not. Results indicate few differences in experimental conditions, meaning that regardless of instructions or marker variable, substantive item correlations remained statistically similar. The results indicate this is likely due to the minimal impact of CMV, given that the proposed methods of correction did not significantly influence research findings. These findings have implications for researchers in that they do not support that CMV, or at least its proposed remedies, significantly alter findings. However, support for the null conclusions, in spite of appropriate statistical power, warrant future research examining the nature and impact of CMV. © 2022,lectronic Journal of Business Research Methods. All Rights Reserved.

Freshwater unionid mussels produce a bilayered shell with the mineral proportion comprising an outer prismatic and an inner nacreous layer. The shell is the animals’ primary structural means of protection from predators and environmental challenges; therefore, variations in shell strength and properties may lead to differences in survival. Few studies have systematically assessed shell properties in unionids. A major challenge in such work is separating effects of environment from those of evolutionary history, because ultimately, both can affect shell properties. We collected eight species of unionids within a small area of the Allegheny River, Pennsylvania, that was relatively homogeneous in substratum type and other environmental characteristics. For each species, we quantified shell thickness, including thickness of the prismatic and nacreous layers, and shell micromechanical properties (microhardness and crack propagation, a measure of fracture resistance) in three regions of the shell. Shell thickness varied dramatically among species and was about five times greater in the thickest-shelled species, Pleurobema sintoxia, than in the thinnest-shelled species, Villosa iris. Because all species experienced similar environmental conditions, variation in shell thickness can be attributed largely to evolutionary history. In contrast, microhardness and crack propagation showed little variation among species. Given that micromechanical properties are similar among species, shell strength may be largely a function of thickness. These results have conservation implications, as differences in shell thickness could reflect relative vulnerability to predators and physical conditions

"This exciting volume brings to life the food culture of Mexico, detailing the development of the cuisine and providing practical information about ingredients and cooking techniques so that readers can replicate some of Mexico's most important traditional dishes"--

This is the third and final book in the series Transformative Pedagogies in Teacher Education. Like the first two books in the series it is geared towards practitioners in the field of teacher education. This third book focuses on transformative leadership in teacher education. In other words, the kind of leadership and practices that will be important and necessary to bring about the kind of changes that both teachers and students seek to improve educational outcomes for all students, but in particular Black, Indigenous and racialized students who have been traditionally underserved by the education system. Teacher leadership plays an important role in transformative educational change that challenges all forms of oppression and white supremacy. This book features chapters by a collection of scholars, teacher educators, researchers, teacher advocates and practitioners drawing on their research and experiences to explore critical issues in teacher education. The book will be useful to teacher educators working with teacher candidates in different contexts, experienced teachers and school leaders. Given demographic shifts and the need for educators to respond to growing diversity in schools, educators will find valuable strategies in Transformative Pedagogies in Teacher Education: Re-Imagining Transformative Leadership in Teacher Education they can employ in their own practice. In addition to valuable strategies, authors explore different approaches and perspectives critical in these changing and challenging times. Critical notions of education are posited from different perspectives and contexts. This book will be useful for teacher education programs, principal preparation programs, in-service teachers, school boards and districts engaging in ongoing professional development of teachers and school leaders.

Building from an interactionist view of ethics, this study sought to integrate individual and contextual factors for understanding ethical perceptions in teams. Given the proximal nature of team members, this study specifically explored how individuals comparatively evaluate their own ethical behaviors and team members’ ethical behaviors to arrive at a perception of ethical person–group (P–G) fit within a team. Grounding our theoretical arguments in relational schemas theory (Baldwin, Psychological Bulletin 112:461–484, 1992), we demonstrate that interpersonal ethical perceptions can have distal impacts on perceptions of team functioning. The results support the hypotheses that a perceived ethical incongruence between the self and other team members (i.e., lack of ethical P–G fit) negatively influenced perceptions of relationship conflict and ultimately information sharing. By exploring individual and team level aspects of ethics concurrently, we contribute to a deeper understanding of contextual forces in ethics through an interactionist approach.

COVID-19, the pandemic of highly contagious respiratory disease, presents a global public health emergency. The COVID-19 pandemic has increased awareness of the role of public health and its professionals in responding to the pandemic. Racial and ethnic minority groups in the United States are more likely to contract and die from COVID-19 versus Whites, highlighting health disparities. Higher education schools and programs in public health can help prepare students to address this global pandemic through expanded curriculum on social determinants of health disparities in COVID-19 outcomes, teachings on implicit bias and anti-racism, interprofessional education, and practice-based learning. Moreover, eliminating health disparities is a leading public health priority in the United States and can help attain the World Health Organization goal of achieving health equity. This chapter highlights the need for public health curriculum that outlines strategies to address racial and ethnic disparities in COVID-19 to prepare and motivate a future healthcare workforce. How to cite this chapter: Njoku, A. (2022). COVID-19 and health disparities opportunities for public health curriculum enhancement. In  R. Ammigan, R. Y. Chan, & K. Bista, (eds), COVID-19 and higher education in the global context: Exploring contemporary issues and challenges (pp. 139-153). STAR Scholars. https://starscholars.org/product/covid-19-and-higed/

The organic component of the molluscan shell allows for orderly biomineralization and ensures structural integrity that is crucial to survival. This organic contribution to the shell typically composes 2-5% of the total adult shell by weight. Because macro- and microstructure of the shell is known to vary with ontogeny and across taxa, we examined if the organic to mineral ratio components in shell also varied with growth across taxa. To assess intraspecific differences in the organic to mineral ratio of the shell during growth, we examined ratios in three marine [Crepidula fornicata (Linnaeus, 1758), Littorina littorea (Linnaeus, 1758), and Littorina saxatilis (Olivi, 1792)] and two freshwater [Corbicula fluminea (Müller, 1774) and Bellamya chinensis (Gray, 1834)] mollusks across size ranges. In the marine gastropods, the average organic component by weight of the small size class was significantly larger than the average organic proportions of the medium and large size classes. The smallest size class of L. saxatilis had an average shell organic proportion of 11.12%, while the smallest size classes of C. fornicata (3.53%) and L. littorea (2.60%) had percentages below 5%. The smallest size class of C. fluminea had a greater average shell organic proportion than the largest size class (6.19% vs 2.68% organics). Adult specimens of B. chinensis had an average shell organic proportion of 3.93%, while in utero shelled juveniles had an average of 10.05%. In both freshwater and marine species, the smallest size class had a greater organic proportion. As the organic matrix is energetically more expensive than the calcified shell portion, we hypothesize that energy expended in these smaller (usually pre-reproductive maturity) stages of growth allows for a more rapid production of shell and that this “expense” is a valuable trade-off for the protection the shell offers young mollusks.

Drawing on Wales, Monsen, and McKelvie's (2011, Entrepreneurship Theory and Practice, 35(5), 895–923) model of entrepreneurial orientation pervasiveness and the strong culture hypothesis (Denison, 1984, Organization Dynamics, 13, 4–22), this study investigates how entrepreneurial orientation (EO) strength, defined as the level of agreement in the shared perceptions of EO, serves as a boundary condition of the EO–firm performance relationship. Four field studies provide evidence for a valid and reliable 10-item multidimensional measure of entrepreneurial orientation, the EO-10, which in turn, may be used to assess EO strength. We establish content and construct validity of the EO-10 (study 1; n = 447 employees), criterion-related validity with revenue growth and sales growth (study 2; n = 412 employees in 43 profit centers), and convergent validity with Covin and Slevin's (1989, Strategic Management Journal, 10, 75–87) 9-item measure (study 3; n = 291 employees). Finally, in study 4 (n = 853 employees nested in 22 organizations), we demonstrate the interactive effects of EO and EO strength on profit growth and revenue growth. In sum, this study provides conceptual and empirical evidence for the importance of EO strength as a moderator of the EO–firm performance relationship.

The students’ performance prediction (SPP) problem is a challenging problem that managers face at any institution. Collecting educational quantitative and qualitative data from many resources such as exam centers, virtual courses, e-learning educational systems, and other resources is not a simple task. Even after collecting data, we might face imbalanced data, missing data, biased data, and different data types such as strings, numbers, and letters. One of the most common challenges in this area is the large number of attributes (features). Determining the highly valuable features is needed to improve the overall students’ performance. This paper proposes an evolutionary-based SPP model utilizing an enhanced form of the Whale Optimization Algorithm (EWOA) as a wrapper feature selection to keep the most informative features and enhance the prediction quality. The proposed EWOA combines the Whale Optimization Algorithm (WOA) with Sine Cosine Algorithm (SCA) and Logistic Chaotic Map (LCM) to improve the overall performance of WOA. The SCA will empower the exploitation process inside WOA and minimize the probability of being stuck in local optima. The main idea is to enhance the worst half of the population in WOA using SCA. Besides, LCM strategy is employed to control the population diversity and improve the exploration process. As such, we handled the imbalanced data using the Adaptive Synthetic (ADASYN) sampling technique and converting WOA to binary variant employing transfer functions (TFs) that belong to different families (S-shaped and V-shaped). Two real educational datasets are used, and five different classifiers are employed: the Decision Trees (DT), k-Nearest Neighbors (k-NN), Naive Bayes (NB), Linear Discriminant Analysis (LDA), and LogitBoost (LB). The obtained results show that the LDA classifier is the most reliable classifier with both datasets. In addition, the proposed EWOA outperforms other methods in the literature as wrapper feature selection with selected transfer functions.

We report high-precision measurements of the longitudinal double-spin asymmetry, ALL, for midrapidity inclusive jet and dijet production in polarized pp collisions at a center-of-mass energy of √s=200 GeV. The new inclusive jet data are sensitive to the gluon helicity distribution, Δg(x,Q2), for gluon momentum fractions in the range from x≃0.05 to x≃0.5, while the new dijet data provide further constraints on the x dependence of Δg(x,Q2). The results are in good agreement with previous measurements at √s=200 GeV and with recent theoretical evaluations of prior world data. Our new results have better precision and thus strengthen the evidence that Δg(x,Q2) is positive for x>0.05.

We present the first inclusive measurements of the invariant and softdrop jet mass in proton-proton collisions at √s=200 GeV at STAR. The measurements are fully corrected for detector effects, and reported differentially in both the jet transverse momentum and jet radius parameter. We compare the measurements to established leading-order Monte Carlo event generators and find that STAR-tuned pythia-6 reproduces the data, while LHC tunes of pythia-8 and herwig-7 do not agree with the data, providing further constraints on parameter tuning. Finally, we observe that softdrop grooming, for which the contribution of wide-angle nonperturbative radiation is suppressed, shifts the jet mass distributions into closer agreement with the partonic jet mass as determined by both pythia-8 and a next-to-leading-logarithmic accuracy perturbative QCD calculation. These measurements complement recent LHC measurements in a different kinematic region, as well as establish a baseline for future jet mass measurements in heavy-ion collisions at RHIC.