Kennesaw State University
  • Kennesaw, Georgia, United States
Recent publications
The Practice Environment Scale of the Nursing Work Index, a widely used practice environment instrument, does not measure vital coworker interrelations. Team virtuousness measures coworker interrelations, yet the literature lacks a comprehensive instrument built from a theoretical foundation that captures the structure. This study sought to develop a comprehensive measure of team virtuousness built from Aquinas' Virtue Ethics Theory that captures the underlying structure. Subjects included nursing unit staff and master of business administration (MBA) students. A total of 114 items were generated and administered to MBA students. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were run on randomly split halves. Based on analyses, 33 items were subsequently administered to nursing unit staff. EFA and CFA were repeated on randomly split halves; CFA item loadings replicated EFA. Three components emerged from the MBA student data: integrity, α = .96; group benevolence, α = .70; and excellence, α = .91. Two components emerged from the nursing unit data: wisdom, α = .97; and excellence, α = .94. Team virtuousness varied significantly among units and correlated significantly with engagement. The two component instrument, named the Perceived Trustworthiness Indicator, is a comprehensive measure of team virtuousness built from a theoretical framework that captures the underlying structure, demonstrates adequate reliability and validity, and measures coworker interrelations on nursing units. Forgiveness and relational and inner harmony emerged as elements of team virtuousness, broadening understanding.
This study examines how taxpayer support for government spending can improve tax compliance. While there is ample evidence on the deterrent effect of audit probability on taxpayer noncompliance, there is no evidence related to the moderating role that taxpayer support may have on compliance behavior. We also examine the moderating role that taxpayer ethics plays in compliance decisions. Results of our study indicate that the level of taxpayer support influences taxpayer compliance decisions, in that those with greater support for how tax dollars are spent report higher amounts of taxable income. In addition, we find that audit probability influences taxpayer compliance decisions when there is support for the government’s use of tax dollars for non-welfare programs, such as defense. However, for welfare programs, such as healthcare, taxpayer support leads to increased compliance regardless of audit rate. When taxpayers do not support government programs, their compliance is lower regardless of the audit probability. This highlights the importance of gaining taxpayer support for government programs and indicates that attempts to align the interests of taxpayers with those of the government may increase voluntary compliance among taxpayers. Finally, we find that taxpayer ethics influences compliance such that, for individuals who have lower ethical standards, a high audit rate as well as support for a program may be necessary to improve compliance behavior. Theoretical and practical implications of these findings are discussed.
Urban plazas provide opportunities for children to play, learn and explore. In particular, public art in urban plazas can be a medium to absorb more children. This research has developed the Inclusive Urban Plaza Design (IUPD) assessment tool, which complies with the principles and features of urban plaza design based on the children’s preferences, needs, wishes, and perceptions for their healthy growth. The AHP (Analytical Hierarchy Process) decision-making method was applied to measure the weights of the feature. AHP analysis determined that motor skills ( W C1.1 = 0.127) have the highest impact on children’s growth among all sub-criteria, followed by space shape and size ( W C2.1 = 0.100) and cognitive development ( W C1.6 = 0.097). The IUPD toolkit was implemented in Vivacity plaza in Singapore to be validated. The implementation analysis showed that Vivacity plaza was a ‘gold’ grade. It is a well-designed urban plaza that supports children’s growth through interaction with various shapes, colors, textures, and materials (like sand and water) that children love. However, it needs minor improvements in terms of inventiveness and creativity (WSM C1.4 = 0.65), cognitive development (WSMC1.4 = 0.57), and time and program schedule (WSM C2.7 = 0.65). The IUPD toolkit showed to be a universal tool that can evaluate the performance of urban plazas in children’s growth.
The direct ink writing (DIW) method of 3D-printing liquid resins has shown promising results in various applications such as flexible electronics, medical devices, and soft robots. A cost-effective extrusion system for a two-part high-viscous resin is developed in this article to fabricate soft and immensely stretchable structures. A static mixer capable of evenly mixing two viscous resins in an extremely low flow regime is designed based on the required mixing performance through a series of biphasic computational fluid dynamics analyses. The printing parameters of the extrusion system are determined empirically , and the mechanical properties of the printed samples are compared to their molded counterparts. Furthermore, some potential applications of the system in soft robotics and medical training are demonstrated. This research provides a clear guide for utilizing DIW to 3D print highly stretchable structures.
Introduction: In the United States, substance addiction is a major contributing factor to incarceration of mothers and separation of children from their families. Five hundred Family Treatment Courts (FTC) operate across the country to combat the growing problem of women addicted to drugs. The FTC model provides mothers with substance addiction treatment, intensive judicial monitoring, repeated drug testing, counseling, incentives or sanctions, and case management with the goal of reaching long-term sobriety and reunification with their children. Design: This retrospective study examined the relationship between sociodemographic characteristics and substance use characteristics, in predicting participants' graduations from the FTC program. Methods: Data were gathered from 317 participants from five Family Treatment Courts in the southeastern United States and analyzed using logistic regression. Results: Participants who completed the FTC program were more likely to be older, completed Cognitive Behavioral Training, completed high school, and Caucasian. Conclusion: Age and completion of Cognitive Behavioral Therapy were the greatest predictors of graduating from the Family Treatment Court. These results convey the need for development of interventions tailored to each participant's age to maximize the success of the FTC participants. In addition, Cognitive Behavioral Therapy should be integrated into all FTC programs. Clinical relevance: The findings from this study will offer research scholars a foundation for designing future studies, aid researchers in creating interventions to increase success in substance addiction treatment programs, and contribute to the framework for theory development. In addition, understanding characteristics that may influence graduation from the Family Treatment Court will provide valuable information on developing interventions to support participants' success.
Additively manufactured (AM) composites based on short carbon fibers possess strength and stiffness far less than their continuous fiber counterparts due to the fiber’s small aspect ratio and inadequate interfaces with the epoxy matrix. This investigation presents a route for preparing hybrid reinforcements for AM that comprise short carbon fibers and nickel-based metal-organic frameworks (Ni-MOFs). The porous MOFs furnish the fibers with tremendous surface area. Additionally, the MOFs growth process is non-destructive to the fibers and easily scalable. This investigation also demonstrates the viability of using Ni-based MOFs as a catalyst for growing multi-walled carbon nanotubes (MWCNTs) on carbon fibers. The changes to the fiber were examined via electron microscopy, X-ray scattering techniques, and Fourier-transform infrared spectroscopy (FTIR). The thermal stabilities were probed by thermogravimetric analysis (TGA). Tensile and dynamic mechanical analysis (DMA) tests were utilized to explore the effect of MOFs on the mechanical properties of 3D-printed composites. Composites with MOFs exhibited improvements in stiffness and strength by 30.2% and 19.0%, respectively. The MOFs enhanced the damping parameter by 700%.
Objectives The prevalence of overweight and obesity is high in adolescents with intellectual and developmental disabilities (IDD), and the availability of and engagement in self-determined health and wellness programs is limited. The objective of the present study was to assess the effectiveness of the Mindfulness-Based Health Wellness (MBHW) program of using telehealth to enable families to teach a field-tested lifestyle change program to their adolescents with IDD. The program encouraged the adolescents to self-determine the parameters of the program that they could use to self-manage their weight through a lifestyle change process. Method Eighty adolescents were randomized into experimental (n = 42) and control (n = 38) groups. The experimental group engaged in the MBHW program as taught by their families, and the control group engaged in treatment as usual (TAU) in a randomized controlled trial. Adolescents in the experimental group self-determined the parameters of each of the five components of the MBHW program and engaged in self-paced weight reduction using a changing-criterion design. Results All 42 adolescents in the experimental group reached their target weights and, on average, reduced their weight by 38 lbs. The 38 adolescents in the control group reduced their weight by an average of 3.47 lbs. by the end of the study. There was a large statistically significant effect of the MBHW program on reduction of both weight and body mass index (BMI) for adolescents in the experimental group. Family members and adolescents rated the MBHW program as having high social validity, and the intervention was delivered with a high degree of fidelity. Conclusions Families can support adolescents with IDD to use the MBHW program to effectively self-manage their weight through a lifestyle change program. Future research should use an active control group, assess maintenance of weight loss across settings and time, use relative fat mass (RFM) for estimating body fat percentage, and evaluate the impact of consuming highly processed foods on weight loss interventions.
We study soft-gluon corrections for the associated production of a single top quark and a Z boson (tqZ production) at hadron colliders. We find that the radiative corrections are dominated by soft-gluon emission. We derive an approximate NNLO (aNNLO) cross section by adding second-order soft-gluon corrections to the exact NLO result. We calculate the aNNLO cross section at LHC energies, including uncertainties from scale dependence and from parton distributions. We also calculate differential distributions in top-quark rapidity. We show that the aNNLO corrections are significant and they enhance the NLO cross section while decreasing theoretical uncertainties.
Care experiences and health outcomes may suffer greatly because of healthcare professionals' deficient educational preparation and practices. The limited awareness about the impact of stereotypes, implicit/explicit biases, and Social Determinants of Health (SDH) may result in unpleasant care experiences and healthcare professional-patient relationships. Additionally, as healthcare professionals are no less prone to have biases than other people, it is essential to deliver the learning platform to enhance healthcare skills (e.g., awareness of the importance of cultural humility, inclusive communication proficiencies, awareness of the enduring impact of both SDH and implicit/explicit biases on health outcomes, and compassionate and empathetic attitude) of healthcare professionals which eventually help to raise health equity in society. Moreover, employing the “learning-by-doing” approach directly in real-life clinical practices is less preferable wherein high-risk care is essential. Thus, there is a huge scope to deliver virtual reality-based care practices by engaging the digital experiential learning and Human-Computer Interaction (HCI) approach to enhance patient care experiences, healthcare experiences, and healthcare skills. Thus, this research provides the Computer-Supported Experiential Learning (CSEL) approach-based tool or mobile application that facilitates virtual reality-based serious role-playing scenarios to enhance the healthcare skills of healthcare professionals and for public awareness.
A bstract We present all-order predictions for Higgs boson production plus at least one jet which are accurate to leading logarithm in $$ \hat{s}/{\left|{p}_{\perp}\right|}^2 $$ s ̂ / p ⊥ 2 . Our calculation includes full top and bottom quark mass dependence at all orders in the logarithmic part, and to highest available order in the tree-level matching. The calculation is implemented in the framework of High Energy Jets (HEJ). This is the first cross section calculated with log( $$ \hat{s} $$ s ̂ ) resummation and matched to fixed order for a process requiring just one jet, and our results also extend the region of resummation for processes with two jets or more. This is possible because the resummation is performed explicitly in phase space. We compare the results of our new calculation to LHC data and to next-to-leading order predictions and find a numerically significant impact of the logarithmic corrections in the shape of key distributions, which remains after normalisation of the cross section.
Background: Multi-modal learning is widely adopted to learn the latent complementary information between different modalities in multi-modal medical image segmentation tasks. Nevertheless, the traditional multi-modal learning methods require spatially well-aligned and paired multi-modal images for supervised training, which cannot leverage unpaired multi-modal images with spatial misalignment and modality discrepancy. For training accurate multi-modal segmentation networks using easily accessible and low-cost unpaired multi-modal images in clinical practice, unpaired multi-modal learning has received comprehensive attention recently. Purpose: Existing unpaired multi-modal learning methods usually focus on the intensity distribution gap but ignore the scale variation problem between different modalities. Besides, within existing methods, shared convolutional kernels are frequently employed to capture common patterns in all modalities, but they are typically inefficient at learning global contextual information. On the other hand, existing methods highly rely on a large number of labeled unpaired multi-modal scans for training, which ignores the practical scenario when labeled data is limited. To solve the above problems, we propose a modality-collaborative convolution and transformer hybrid network (MCTHNet) using semi-supervised learning for unpaired multi-modal segmentation with limited annotations, which not only collaboratively learns modality-specific and modality-invariant representations, but also could automatically leverage extensive unlabeled scans for improving performance. Methods: We make three main contributions to the proposed method. First, to alleviate the intensity distribution gap and scale variation problems across modalities, we develop a modality-specific scale-aware convolution (MSSC) module that can adaptively adjust the receptive field sizes and feature normalization parameters according to the input. Secondly, we propose a modality-invariant vision transformer (MIViT) module as the shared bottleneck layer for all modalities, which implicitly incorporates convolution-like local operations with the global processing of transformers for learning generalizable modality-invariant representations. Third, we design a multi-modal cross pseudo supervision (MCPS) method for semi-supervised learning, which enforces the consistency between the pseudo segmentation maps generated by two perturbed networks to acquire abundant annotation information from unlabeled unpaired multi-modal scans. Results: Extensive experiments are performed on two unpaired CT and MR segmentation datasets, including a cardiac substructure dataset derived from the MMWHS-2017 dataset and an abdominal multi-organ dataset consisting of the BTCV and CHAOS datasets. Experiment results show that our proposed method significantly outperforms other existing state-of-the-art methods under various labeling ratios, and achieves a comparable segmentation performance close to single-modal methods with fully labeled data by only leveraging a small portion of labeled data. Specifically, when the labeling ratio is 25%, our proposed method achieves overall mean DSC values of 78.56% and 76.18% in cardiac and abdominal segmentation, respectively, which significantly improves the average DSC value of two tasks by 12.84% compared to single-modal U-Net models. Conclusions: Our proposed method is beneficial for reducing the annotation burden of unpaired multi-modal medical images in clinical applications. This article is protected by copyright. All rights reserved.
There is concern about robots taking people’s jobs. Advances in automation risk bringing material and psychological harm to workers, so it is important to study the ethics of this engineering discipline. Existing work focuses on either policy to ameliorate workers’ income loss or the effects of losing agency. What is missing is a guide to help automation engineers and roboticists evaluate their moral responsibilities. This article addresses that gap by providing some motivation for these practitioners to consider the ethics of job obsolescence and tools to evaluate relevant professional choices.
Dysregulated cortical expression of the neural cell adhesion molecule (NCAM) and deficits of its associated polysialic acid (polySia) have been found in Alzheimer's disease and schizophrenia. However, the functional role of polySia in cortical synaptic plasticity remains poorly understood. Here, we show that acute enzymatic removal of polySia in medial prefrontal cortex (mPFC) slices leads to increased transmission mediated by the GluN1/GluN2B subtype of N-methyl-d-aspartate receptors (NMDARs), increased NMDAR-mediated extrasynaptic tonic currents, and impaired long-term potentiation (LTP). The latter could be fully rescued by pharmacological suppression of GluN1/GluN2B receptors, or by application of short soluble polySia fragments that inhibited opening of GluN1/GluN2B channels. These treatments and augmentation of synaptic NMDARs with the glycine transporter type 1 (GlyT1) inhibitor sarcosine also restored LTP in mice deficient in polysialyltransferase ST8SIA4. Furthermore, the impaired performance of polySia-deficient mice and two models of Alzheimer's disease in the mPFC-dependent cognitive tasks could be rescued by intranasal administration of polySia fragments. Our data demonstrate the essential role of polySia-NCAM in the balancing of signaling through synaptic/extrasynaptic NMDARs in mPFC and highlight the therapeutic potential of short polySia fragments to restrain GluN1/GluN2B-mediated signaling.
This research had two aims: (1) to assess how often bisexual and lesbian women self-report screening and counseling for alcohol use in primary care settings; and (2) understand how bisexual and lesbian women respond to brief messages that alcohol increases breast cancer risk. The study sample consisted of 4891 adult U.S. women who responded to an online, cross-sectional Qualtrics survey in September–October 2021. The survey included the Alcohol Use Disorders Identification Test (AUDIT), questions about alcohol screening and brief counseling in primary care, and questions assessing awareness of the link between alcohol use and breast cancer. Bivariate analyses and logistic regression were conducted. Bisexual and lesbian women had higher odds of harmful drinking (AUDIT score ≥ 8) than heterosexual women (adjusted odds ratio [AOR] = 1.26, 95% confidence interval [CI] = 1.01–1.57 for bisexual women; AOR =1.78, 95% CI = 1.24–2.57 for lesbian women). However, bisexual and lesbian women were no more likely than heterosexual women to be advised about drinking in primary care. In addition, bisexual, lesbian, and heterosexual women had similar reactions to messages highlighting that alcohol is a risk factor for breast cancer. Women across all three sexual orientations who are harmful drinkers more often agreed to search for more information online or talk to a medical professional compared to non-harmful drinkers.
Bulk aluminum nitride (AlN) crystals with different polarities were grown by physical vapor transport (PVT). The structural, surface, and optical properties of m-plane and c-plane AlN crystals were comparatively studied by using high-resolution X-ray diffraction (HR-XRD), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy. Temperature-dependent Raman measurements showed that the Raman shift and the full width at half maximum (FWHM) of the E2 (high) phonon mode of the m-plane AlN crystal were larger than those of the c-plane AlN crystal, which would be correlated with the residual stress and defects in the AlN samples, respectively. Moreover, the phonon lifetime of the Raman-active modes largely decayed and its line width gradually broadened with the increase in temperature. The phonon lifetime of the Raman TO-phonon mode was changed less than that of the LO-phonon mode with temperature in the two crystals. It should be noted that the influence of inhomogeneous impurity phonon scattering on the phonon lifetime and the contribution to the Raman shift came from thermal expansion at a higher temperature. In addition, the trend of stress with increasing 1000/temperature was similar for the two AlN samples. As the temperature increased from 80 K to ~870 K, there was a temperature at which the biaxial stress of the samples transformed from compressive to tensile stress, while their certain temperature was different.
Impostor Phenomenon (IP), also called impostor syndrome, involves feelings of perceived fraudulence, self-doubt, and personal incompetence that persist despite one’s education, experience, and accomplishments. This study is the first to evaluate the presence of IP among data science students and to evaluate several variables linked to IP simultaneously in a single study evaluating data science. In addition, it is the first study to evaluate the extent to which gender identification is linked to IP. We examined: (1) the degree to which IP exists in our sample; (2) how gender identification is linked to IP; (3) whether there are differences in goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value for different levels of IP; and (4) the extent to which goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value predict IP. We found that most students in the sample showed moderate and frequent levels of IP. Moreover, gender identification was positively related to IP for both males and females. Finally, results indicated significant differences in perfectionism, value, self-efficacy, anxiety, and avoidance goals by IP level and that perfectionism, self-efficacy, and anxiety were particularly noteworthy in predicting IP. Implications of our findings for improving IP among data science students are discussed.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.
6,236 members
Kojo Mensa-Wilmot
  • Molecular and Cellular Biology
Amir Ali Amiri Moghadam
  • Robotics and Mechatronics Engineering
Iván Manuel Jorrín Abellán
  • Department of Secondary and Middle Grades Education
Andrew D Haddow
  • Molecular and Cellular Biology
Katherine H Ingram
  • Department of Exercise Science and Sport Management
1000 Chastain Road, 30144, Kennesaw, Georgia, United States