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© 2021, The Author(s). During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading “Chinese virus” narrative, and the use of disinfectants to “cure” COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

COVID-19 vaccines are by no means a silver bullet. With more COVID-19 vaccines expecting approval in the coming months, it is necessary to note that vaccine availability does not equate to vaccine accessibility, nor vaccine efficacy. Some research suggests that approximately 9 out of 10 individuals living in lower-income countries will not have access to COVID-19 vaccines until 2023 or later. For higher-income countries, such as the United States, the prevalence of vaccine hesitancy may further compound the situation. These insights combined, in turn, emphasize the fact that even though COVID-19 vaccines are becoming more available, safety measures (e.g., face masks, personal hygiene, and social distancing) are still of pivotal importance in protecting personal and public health against COVID-19. Furthermore, this paper argues for the continued imperative for health experts and government officials to communicate and emphasize the importance of COVID-19 safety measures with the public, to make sure people are protected against COVID-19 till the pandemic ceases to pose a threat to personal or public health.

Background Health campaign interventions, particularly those tailored to the target audience’s needs and preferences, can cost-effectively change people’s attitudes and behaviors towards better health decision-making. However, there is limited research on how to best tailor seasonal influenza vaccination campaigns for young adults. Vaccination is vital in protecting young adults and their social circles (vulnerable populations like older adults) from the influenza virus and critical in shaping these emerging adults’ vaccination habits in the long run. However, amid the prevalence of easily-accessible, attention-grabbing, and often malicious false and misinformation (e.g., COVID-19 vaccine conspiracy theories), it may be more challenging to develop vaccination messages that resonate with young adults well enough to attract their attention. Therefore, to bridge the research gap, this study examines young adults’ preferences for seasonal influenza vaccination campaigns to inform effective intervention design and development. Methods Qualitative survey questions were developed to gauge young adults’ preferences for seasonal influenza vaccination campaigns. A total of 545 young adults (73.9% female, Mage = 19.89, SD = 1.44) from a large University offered complete answers to a cross-sectional online survey. Braun and Clarke’s thematic analysis procedures were adopted to guide the data analysis process. Results Thematic analysis revealed that young adults prefer seasonal influenza vaccination campaigns that rely on (1) quality and balanced information from (2) credible information sources, positioned in the (3) relevant health contexts, (4) emphasize actionable messages, and incorporate (5) persuasive campaign design. Interestingly, while many participants underscored the importance of fear-appeal messages in persuading them to take health actions, some young adults also suggested avoiding fear campaigns due to discomfort. Conclusions Insights of the study can inform seas

Background: Acculturation could cause grave health consequences in international students. However, there is a shortage of research into how acculturative stress might affect international students’ quality of life in light of their academic standing and experience. The lack of research is particularly pronounced among Chinese international students, representing the largest body of international students studying in the United States (U.S.). Thus, to bridge the research gap, this study aims to examine the interplay between international students’ acculturative stress, academic standing, and quality of life among a nationally representative sample of Chinese international students studying in the United States. Methods: An online survey that gauges Chinese international students’ levels of acculturative stress, academic standing, and quality of life was developed. Over 350 higher education institutions across the United States were approached, including public universities, private universities, and community colleges, among which approximately 220 institutions responded positively and supported survey distribution. A total of 751 students completed the survey. Multiple regression analyses were carried out to examine the associations between students’ acculturative stress, academic standing, and quality of life. Results: Findings reveal that acculturative stress negatively affects all four domains of Chinese international students’ quality of life, irrespective of their academic standing. Data analyses also show that compared to master’s and doctoral students, undergraduates experience the highest levels of acculturative stress. Furthermore, a significant difference emerged among undergraduate and doctoral international students’ acculturative stress levels, but not among undergraduate and master’s students, or master’s and doctoral students. Conclusion: Our study found that, compared to master’s and doctoral students, undergraduates had more significant acculturati

Background Health campaign interventions, particularly those tailored to the target audience’s needs and preferences, can cost-effectively change people’s attitudes and behaviors towards better health decision-making. However, there is limited research on how to best tailor seasonal influenza vaccination campaigns for young adults. Vaccination is vital in protecting young adults and their social circles (vulnerable populations like older adults) from the influenza virus and critical in shaping these emerging adults’ vaccination habits in the long run. However, amid the prevalence of easily-accessible, attention-grabbing, and often malicious false and misinformation (e.g., COVID-19 vaccine conspiracy theories), it may be more challenging to develop vaccination messages that resonate with young adults well enough to attract their attention. Therefore, to bridge the research gap, this study examines young adults’ preferences for seasonal influenza vaccination campaigns to inform effective intervention design and development. Methods Qualitative survey questions were developed to gauge young adults’ preferences for seasonal influenza vaccination campaigns. A total of 545 young adults (73.9% female, Mage = 19.89, SD = 1.44) from a large University offered complete answers to a cross-sectional online survey. Braun and Clarke’s thematic analysis procedures were adopted to guide the data analysis process. Results Thematic analysis revealed that young adults prefer seasonal influenza vaccination campaigns that rely on (1) quality and balanced information from (2) credible information sources, positioned in the (3) relevant health contexts, (4) emphasize actionable messages, and incorporate (5) persuasive campaign design. Interestingly, while many participants underscored the importance of fear-appeal messages in persuading them to take health actions, some young adults also suggested avoiding fear campaigns due to discomfort. Conclusions Insights of the study can inform seas

Background: Acculturation could cause grave health consequences in international students. However, there is a shortage of research into how acculturative stress might affect international students’ quality of life in light of their academic standing and experience. The lack of research is particularly pronounced among Chinese international students, representing the largest body of international students studying in the United States (U.S.). Thus, to bridge the research gap, this study aims to examine the interplay between international students’ acculturative stress, academic standing, and quality of life among a nationally representative sample of Chinese international students studying in the United States. Methods: An online survey that gauges Chinese international students’ levels of acculturative stress, academic standing, and quality of life was developed. Over 350 higher education institutions across the United States were approached, including public universities, private universities, and community colleges, among which approximately 220 institutions responded positively and supported survey distribution. A total of 751 students completed the survey. Multiple regression analyses were carried out to examine the associations between students’ acculturative stress, academic standing, and quality of life. Results: Findings reveal that acculturative stress negatively affects all four domains of Chinese international students’ quality of life, irrespective of their academic standing. Data analyses also show that compared to master’s and doctoral students, undergraduates experience the highest levels of acculturative stress. Furthermore, a significant difference emerged among undergraduate and doctoral international students’ acculturative stress levels, but not among undergraduate and master’s students, or master’s and doctoral students. Conclusion: Our study found that, compared to master’s and doctoral students, undergraduates had more significant acculturati

COVID-19 vaccines are by no means a silver bullet. With more COVID-19 vaccines expecting approval in the coming months, it is necessary to note that vaccine availability does not equate to vaccine accessibility, nor vaccine efficacy. Some research suggests that approximately 9 out of 10 individuals living in lower-income countries will not have access to COVID-19 vaccines until 2023 or later. For higher-income countries, such as the United States, the prevalence of vaccine hesitancy may further compound the situation. These insights combined, in turn, emphasize the fact that even though COVID-19 vaccines are becoming more available, safety measures (e.g., face masks, personal hygiene, and social distancing) are still of pivotal importance in protecting personal and public health against COVID-19. Furthermore, this paper argues for the continued imperative for health experts and government officials to communicate and emphasize the importance of COVID-19 safety measures with the public, to make sure people are protected against COVID-19 till the pandemic ceases to pose a threat to personal or public health.

© 2021, The Author(s). During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading “Chinese virus” narrative, and the use of disinfectants to “cure” COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

In this work, we perform semantic segmentation of multiple defect types in electron microscopy images of irradiated FeCrAl alloys using a deep learning Mask Regional Convolutional Neural Network (Mask R-CNN) model. We conduct an in-depth analysis of key model performance statistics, with a focus on quantities such as predicted distributions of defect shapes, defect sizes, and defect areal densities relevant to informing modeling and understanding of irradiated Fe-based materials properties. To better understand the performance and present limitations of the model, we provide examples of useful evaluation tests which include a suite of random splits, and dataset size-dependent and domain-targeted cross validation tests. Overall, we find that the current model is a fast, effective tool for automatically characterizing and quantifying multiple defect types in microscopy images, with a level of accuracy on par with human domain expert labelers. More specifically, the model can achieve average defect identification F1 scores as high as 0.8, and, based on random cross validation, have low overall average (+/- standard deviation) defect size and density percentage errors of 7.3 (+/- 3.8)% and 12.7 (+/- 5.3)%, respectively. Further, our model predicts the expected material hardening to within 10-20 MPa (about 10% of total hardening), which is about the same error level as experiments. Our targeted evaluation tests also suggest the best path toward improving future models is not expanding existing databases with more labeled images but instead data additions that target weak points of the model domain, such as images from different microscopes, imaging conditions, irradiation environments, and alloy types. Finally, we discuss the first phase of an effort to provide an easy-to-use, open-source object detection tool to the broader community for identifying defects in new images.

Neuroimaging data often take the form of high dimensional arrays, also known as tensors. Addressing scientific questions arising from such data demands new regression models that take multidimensional arrays as covariates. Simply turning an image array into a vector would both cause extremely high dimensionality and destroy the inherent spatial structure of the array. In a recent work, Zhou et al. (2013) proposed a family of generalized linear tensor regression models based upon the CP (CANDECOMP/PARAFAC) decomposition of regression coefficient array. Low rank approximation brings the ultrahigh dimensionality to a manageable level and leads to efficient estimation. In this article, we propose a tensor regression model based on the more flexible Tucker decomposition. Compared to the CP model, Tucker regression model allows different number of factors along each mode. Such flexibility leads to several advantages that are particularly suited to neuroimaging analysis, including further reduction of the number of free parameters, accommodation of images with skewed dimensions, explicit modeling of interactions, and a principled way of image downsizing. We also compare the Tucker model with CP numerically on both simulated data and a real magnetic resonance imaging data, and demonstrate its effectiveness in finite sample performance.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their adoption-a phenomenon that may be more pronounced amid "Operation Warp Speed"-it is important for public health professionals to thoroughly understand their "customers" (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their adoption-a phenomenon that may be more pronounced amid "Operation Warp Speed"-it is important for public health professionals to thoroughly understand their "customers" (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.

Extended Linear Duration Invariants (ELDI), an important subset of Duration Calculus, extends well-studied Linear Duration Invariants with logical connectives and the chop modality. It is known that the model checking problem of ELDI is undecidable with both the standard continuous-time and discrete-time semantics [12, 13], but it turns out to be decidable if only bounded execution fragments of timed automata are concerned in the context of the discrete-time semantics [36]. In this paper, we prove that this problem is still decidable in the continuous-time semantics, although it is well-known that model-checking Duration Calculus with the continuous-time semantics is much more complicated than the one with the discrete-time semantics. This is achieved by reduction to the validity of Quantified Linear Real Arithmetic (QLRA). Some examples are provided to illustrate the efficiency of our approach.

We prove the stability of the equivariant embedding of compact strictly pseudoconvex CR manifolds with transversal CR circle action under circle invariant deformations of the CR structures.

Let X be a compact connected strongly pseudoconvex Cauchy-Riemann (CR) manifold of real dimension 2n + 1, n >= 1 with a transversal CR S-1 action on X. We establish an asymptotic expansion for the mth Fourier component of the Szego kernel function as m -> infinity, where the expansion involves a contribution in terms of a distance function from lower dimensional strata of the S-1 action. We also obtain explicit formulas for the first three coefficients of the expansion.

We prove the stability of the equivariant embedding of compact strictly pseudoconvex CR manifolds with transversal CR circle action under circle invariant deformations of the CR structures.

Let X be a compact connected strongly pseudoconvex Cauchy-Riemann (CR) manifold of real dimension 2n + 1, n >= 1 with a transversal CR S-1 action on X. We establish an asymptotic expansion for the mth Fourier component of the Szego kernel function as m -> infinity, where the expansion involves a contribution in terms of a distance function from lower dimensional strata of the S-1 action. We also obtain explicit formulas for the first three coefficients of the expansion.

Background: Pharmacokinetic evaluation is one of the key processes in drug discovery and development. However, current absorption, distribution, metabolism, excretion prediction models still have limited accuracy. Aim: This study aims to construct an integrated transfer learning and multitask learning approach for developing quantitative structure-activity relationship models to predict four human pharmacokinetic parameters. Methods: A pharmacokinetic dataset included 1104 U.S. FDA approved small molecule drugs. The dataset included four human pharmacokinetic parameter subsets (oral bioavailability, plasma protein binding rate, apparent volume of distribution at steady-state and elimination half-life). The pre-trained model was trained on over 30 million bioactivity data. An integrated transfer learning and multitask learning approach was established to enhance the model generalization. Results: The pharmacokinetic dataset was split into three parts (60:20:20) for training, validation and test by the improved Maximum Dissimilarity algorithm with the representative initial set selection algorithm and the weighted distance function. The multitask learning techniques enhanced the model predictive ability. The integrated transfer learning and multitask learning model demonstrated the best accuracies, because deep neural networks have the general feature extraction ability, transfer learning and multitask learning improved the model generalization. Conclusions: The integrated transfer learning and multitask learning approach with the improved dataset splitting algorithm was firstly introduced to predict the pharmacokinetic parameters. This method can be further employed in drug discovery and development.

Current pharmaceutical formulation development still strongly relies on the traditional trial-and-error approach by individual experiences of pharmaceutical scientists, which is laborious, time-consuming and costly. Recently, deep learning has been widely applied in many challenging domains because of its important capability of automatic feature extraction. The aim of this research is to use deep learning to predict pharmaceutical formulations. In this paper, two different types of dosage forms were chosen as model systems. Evaluation criteria suitable for pharmaceutics were applied to assessing the performance of the models. Moreover, an automatic dataset selection algorithm was developed for selecting the representative data as validation and test datasets. Six machine learning methods were compared with deep learning. The result shows the accuracies of both two deep neural networks were above 80% and higher than other machine learning models, which showed good prediction in pharmaceutical formulations. In summary, deep learning with the automatic data splitting algorithm and the evaluation criteria suitable for pharmaceutical formulation data was firstly developed for the prediction of pharmaceutical formulations. The cross-disciplinary integration of pharmaceutics and artificial intelligence may shift the paradigm of pharmaceutical researches from experience-dependent studies to data-driven methodologies.

Prototyping is an effective and efficient way of requirement validation to avoid introducing errors in the early stage of software development. However, manually developing a prototype of a software system requires additional efforts, which would increase the overall cost of software development. In this paper, we present an approach with a developed tool to automatic generation of prototypes from formal requirements models. A requirements model consists of a use case diagram, a conceptual class diagram, use case definitions specified by system sequence diagrams and the contracts of their system operations. We propose a method to decompose a contract into executable parts and non-executable parts. A set of transformation rules is given to decompose the executable part into pre-implemented primitive operations. A non-executable part is usually realized by significant algorithms such as sorting a list, finding the shortest path or domain-specific computation. It can be implemented manually or by using existing code. A CASE tool is developed that provides an interface for developers to develop a program for each non-executable part of a contract, and automatically transforms the executables into sequences of pre-implemented primitive operations. We have conducted four cases studies with over 50 use cases. The experimental result shows that the 93.65% of requirement specifications are executable, and only 6.35% are non-executable such as sorting and event-call, which can be implemented by developers manually or invoking the APIs of advanced algorithms in Java library. The one second generated the prototype of a case study requires approximate nine hours manual implementation by a skilled programmer. Overall, the result is satisfiable, and the proposed approach with the developed CASE tool can be applied to the software industry for requirements engineering.

This paper takes up the problem of medical resource sharing through MicroService architecture without compromising patient privacy. To achieve this goal, we suggest refactoring the legacy EHR systems into autonomous MicroServices communicating by the unified techniques such as RESTFul web service. This lets us handle clinical data queries directly and far more efficiently for both internal and external queries. The novelty of the proposed approach lies in avoiding the data de-identification process often used as a means of preserving patient privacy. The implemented toolkit combines software engineering technologies such as Java EE, RESTful web services, JSON Web Tokens to allow exchanging medical data in an unidentifiable XML and JSON format as well as restricting users to the need-to-know principle. Our technique also inhibits retrospective processing of data such as attacks by an adversary on a medical dataset using advanced computational methods to reveal Protected Health Information (PHI). The approach is validated on an endoscopic reporting application based on openEHR and MST standards. From the usability perspective, the approach can be used to query datasets by clinical researchers, governmental or non-governmental organizations in monitoring health care and medical record services to improve quality of care and treatment., Comment: Extended from our conference paper: arXiv:1501.05916

Oral Disintegrating Tablets (ODTs) is a novel dosage form that can be dissolved on the tongue within 3min or less especially for geriatric and pediatric patients. Current ODT formulation studies usually rely on the personal experience of pharmaceutical experts and trial-and-error in the laboratory, which is inefficient and time-consuming. The aim of current research was to establish the prediction model of ODT formulations with direct compression process by Artificial Neural Network (ANN) and Deep Neural Network (DNN) techniques. 145 formulation data were extracted from Web of Science. All data sets were divided into three parts: training set (105 data), validation set (20) and testing set (20). ANN and DNN were compared for the prediction of the disintegrating time. The accuracy of the ANN model has reached 85.60%, 80.00% and 75.00% on the training set, validation set and testing set respectively, whereas that of the DNN model was 85.60%, 85.00% and 80.00%, respectively. Compared with the ANN, DNN showed the better prediction for ODT formulations. It is the first time that deep neural network with the improved dataset selection algorithm is applied to formulation prediction on small data. The proposed predictive approach could evaluate the critical parameters about quality control of formulation, and guide research and process development. The implementation of this prediction model could effectively reduce drug product development timeline and material usage, and proactively facilitate the development of a robust drug product., Comment: This is a post-peer-review, pre-copyedit version of an article published in Asian Journal of Pharmaceutical Sciences. The final authenticated version is available online at: https://doi.org/10.1016/j.ajps.2018.01.003

Unified Modeling Language (UML) is the de facto standard for requirements modeling and system design. UML as a visual language can tremendously help customers, project managers, and developers to specify the requirements of a target system. However, UML lacks the ability to specify the requirements precisely such as the contracts of the system operation, and verify the consistency and refinement of the requirements. These disadvantages result in that the potential faults of software are hard to be discovered in the early stage of software development process, and then requiring more efforts in software testing to find the bugs. Service refinement is a formal method, which could be a supplement to enhance the UML. In this paper, we show how to integrate UML with service refinement to specify requirements, and verify the consistency and refinements of the requirements through a case study of online shopping system. Particularly, requirements are modeled through UML diagrams, which includes a) use case diagram, b) system sequence diagrams and c) conceptual class diagram. Service refinement enhances the requirements model by introducing the contracts. Furthermore, the consistency and refinements of requirement model can be verified through service refinement. Our approach demonstrates integrating UML with service refinement can require fewer efforts to achieve the consistency requirements than only using UML for requirement modeling.

Legacy Electronic Health Records (EHRs) systems were not developed with the level of connectivity expected from them nowadays. Therefore, interoperability weakness inherent in the legacy systems can result in poor patient care and waste of financial resources. Large hospitals are less likely to share their data with external hospitals due to economic and political reasons. Motivated by these facts, we aim to provide a set of software implementation guidelines, i.e., MedShare to deal with interoperability issues among disconnected healthcare systems. The proposed integrated architecture includes: 1) a data extractor to fetch legacy medical data from a hemodialysis center, 2) converting it to a common data model, 3) indexing patient information using the HashMap technique, and 4) a set of services and tools that can be installed as a coherent environment on top of stand-alone EHRs systems. Our work enabled three cooperating but autonomous hospitals to mutually exchange medical data and helped them develop a common reference architecture. It lets stakeholders retain control over their patient data, winning the trust and confidence much needed towards a successful deployment of MedShare. Security concerns were effectively addressed that also included patient consent in the data exchange process. Thereby, the implemented toolset offered a collaborative environment to share EHRs by the healthcare providers., Comment: underview of J-BHI

With the advancement of software engineering in recent years, the model checking techniques are widely applied in various areas to do the verification for the system model. However, it is difficult to apply the model checking to verify requirements due to lacking the details of the design. Unlike other model checking tools, LTSA provides the structure diagram, which can bridge the gap between the requirements and the design. In this paper, we demonstrate the abilities of LTSA shipped with the classic case study of the steam boiler system. The structure diagram of LTSA can specify the interactions between the controller and the steam boiler, which can be derived from UML requirements model such as system sequence diagram of the steam boiler system. The start-up design model of LTSA can be generated from the structure diagram. Furthermore, we provide a variation law of the steam rate to avoid the issue of state space explosion and show how explicitly and implicitly model the time that reflects the difference between system modeling and the physical world. Finally, the derived model is verified against the required properties. Our work demonstrates the potential power of integrating UML with model checking tools in requirement elicitation, system design, and verification.

Let X be a compact strongly pseudoconvex CR manifold with a transversal CR -action. In this paper, we establish the asymptotic expansion of SzegA kernels of positive Fourier components, and by using the asymptotics, we show that X can be equivariant CR embedded into some equipped with a simple -action. An equivariant embedding of quasi-regular Sasakian manifold is also derived.

Let X be a compact strongly pseudoconvex CR manifold with a transversal CR -action. In this paper, we establish the asymptotic expansion of SzegA kernels of positive Fourier components, and by using the asymptotics, we show that X can be equivariant CR embedded into some equipped with a simple -action. An equivariant embedding of quasi-regular Sasakian manifold is also derived.

In this short paper we present our solution for the Compiler Optimization case study of the Transformation Tool Contest (TTC) 2011 using the QVTR-XSLT tool. The tool supports editing and execution of the graphical notation of QVT Relations language, Comment: In Proceedings TTC 2011, arXiv:1111.4407

In this short paper we present our solution for the Hello World case study of the Transformation Tool Contest (TTC) 2011 using the QVTR-XSLT tool. The tool supports editing and execution of the graphical notation of QVT Relations language. The case study consists of a set of simple transformation tasks which covers the basic functions required for a transformation language, such as creating, reading/querying, updating and deleting of model elements. We design a transformation for each of the tasks., Comment: In Proceedings TTC 2011, arXiv:1111.4407

Type 2 diabetes mellitus (T2DM) has insulin resistance (IR) or reduced β-cell mass, partially due to an increased β-cell apoptosis rate. Pancreatic stone protein/regenerating protein (PSP/reg) is a secretory protein produced in the pancreas and up-regulated dramatically during pancreatic disease. Recent studies revealed that β-cells undergoing apoptosis induce PSP/reg expression in surviving neighboring cells. Further experiments demonstrated that PSP/reg was elevated during disease progression in type 1 diabetes mellitus (T1DM). However, the association between PSP/reg and T2DM patients is unknown. The aim of this pilot study was to investigate PSP/reg in different clinical stages of T2DM and evaluate its correlation with chronic complications of diabetes. A total of 1,121 participants (479 males, 642 females; age range 23-80years) were enrolled in this study. PSP/reg serum values were measured by a newly developed enzyme-linked immunosorbent assay (ELISA). We analyzed its correlation with clinical and biochemical parameters in subjects with T2DM at different clinical phases. Statistical analyses were conducted using SPSS 17.0 software. Correlations of PSP/reg and clinical parameters were performed using Spearman's rank correlation coefficient. Differences between groups were determined by Nemenyi test. PSP/reg was elevated in high-risk and impaired glucose regulation (IGR) patients (p<0.05). PSP/reg was significantly up-regulated in newly diagnosed T2DM patients and long-term diabetes patients with complications (p<0.001). PSP/reg levels correlated with the duration of diabetes (p<0.001). The area under the curve (AUC) for presence of diabetes-onset and its chronic complications was 0.640 and 0.754, respectively. PSP/reg is significantly up-regulated in T2DM patients, and PSP/reg levels are related to the duration of diabetes. Therefore, PSP/reg might be useful as a predictor of T2DM and disease progression.

Su, Z., McDonnell, D., Shi, F., Liang, B., Li, X., Wen, J., . . . Yang, L. (2021). Chinese international students in the United States: The interplay of students’ acculturative stress, academic standing, and quality of life. Frontiers in Psychology, 12, article 625863. https://doi.org/10.3389/fpsyg.2021.625863

Su, Z., Wen, J., Abbas, J., McDonnell, D., Cheshmehzangi, A., Li, X., ... & Cai, Y. (2020). A race for a better understanding of COVID-19 vaccine non-adopters. Brain, behavior, & immunity-health, 100159. https://doi.org/10.1016/j.bbih.2020.100159

Su, Z., Wen, J., McDonnell, D., Goh, E., Li, X., Šegalo, S., ... Xiang, Y. T. (2021). Vaccines are not yet a silver bullet: The imperative of continued communication about the importance of COVID-19 safety measures. Brain, Behavior, & Immunity - Health, 12, article 100204. https://doi.org/10.1016/j.bbih.2021.100204

Su, Z., McDonnell, D., Wen, J., Cheshmehzangi, A., Ahmad, J., Goh, E., ... Wang, P. (2021). Young adults’ preferences for influenza vaccination campaign messages: Implications for COVID-19 vaccine intervention design and development. Brain, Behavior, & Immunity-Health, 14, article 100261. https://doi.org/10.1016/j.bbih.2021.100261

Su, Z., McDonnell, D., Wen, J., Kozak, M., Abbas, J., Šegalo, S., ... Xiang, Y. T. (2021). Mental health consequences of COVID-19 media coverage: The need for effective crisis communication practices. Globalization and Health, 17, article 4. https://doi.org/10.1186/s12992-020-00654-4

During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading “Chinese virus” narrative, and the use of disinfectants to “cure” COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their de facto adoption—a phenomenon that may be more pronounced amid “Operation Warp Speed”—it is important for public health professionals to thoroughly understand their “customers” (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.

During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading “Chinese virus” narrative, and the use of disinfectants to “cure” COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their de facto adoption—a phenomenon that may be more pronounced amid “Operation Warp Speed”—it is important for public health professionals to thoroughly understand their “customers” (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.

During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading “Chinese virus” narrative, and the use of disinfectants to “cure” COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their de facto adoption—a phenomenon that may be more pronounced amid “Operation Warp Speed”—it is important for public health professionals to thoroughly understand their “customers” (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.

During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading “Chinese virus” narrative, and the use of disinfectants to “cure” COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their de facto adoption—a phenomenon that may be more pronounced amid “Operation Warp Speed”—it is important for public health professionals to thoroughly understand their “customers” (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.

During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading “Chinese virus” narrative, and the use of disinfectants to “cure” COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their de facto adoption—a phenomenon that may be more pronounced amid “Operation Warp Speed”—it is important for public health professionals to thoroughly understand their “customers” (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.