To enhance the sustainability of business operations, enterprises have interests in enterprise resource planning (ERP) transitions from an existing on-premise method to a cloud-based system This study conducts a comprehensive analysis using the technology-organization-environment, diffusion of innovation, and the model of innovation resistance frameworks The empirical analysis shows that the factors of organizational culture, regulatory environment, relative advantage, trialability, and vendor lock-in all had a significant influence on the intention to adopt cloud-based ERP, while information and communications technology skill, complexity, observability, data security, and customization had no significant influence on the intention to adopt cloud-based ERP This studys findings provide meaningful guidance for companies that want to adopt cloud-based ERP, governments that support enterprise digitalization, and vendors who sell cloud-based ERP systems

COVID-19 is breaking out and spreading globally, posing a severe threat to public health and economies worldwide due to its highly transmissible and pathogenic nature. Early, accurate and rapid diagnosis of COVID-19 can effectively stop the spread of the COVID-19 virus. Automatic diagnostic models based on deep learning can detect COVID-19 quickly and accurately. This paper uses a three-dimensional Convolutional Neural Network (3D CNN) to build a COVID-19 diagnostic prediction model for COVID-19 detection. All 192 sets of chest Computed Tomography(CT) data collected are used for this study, including 96 sets of confirmed COVID-19 patients and 96 sets of CT scans of normal human lungs. 5-fold cross-validation is used to train and validate the model. 154 data sets are used to train the model, and 38 sets are used for testing. All experimental data are segmented using a pre-trained SP-V-Net to obtain 3D lung masks fed into 3D CNN for training and validation of the prediction model. In addition, to verify the accuracy of the model predictions and provide interpretability for medical diagnosis, we visualize the experimental results using Class Activation Maps(CAM) to localize the predicted disease regions. The results from several experiments show that the accuracy of our prediction model is 0.911, the Area Under Curve (AUC) 0.976, for no-COVID-19(Precision, 0.902, Recall 0.911, F1-Score 0.900), COVID-19 (Precision, 0.932, Recall 0.911, F1-Score 0.902). The experimental results show that our established diagnostic model can help physicians make a rapid and accurate diagnosis of COVID-19 in response to the spread of COVID-19. ? 2021 IEEE.

Transgenic-Bacillus thuringiensis (Bt) crops express insecticidal proteins, which can accumulate in plants and soil where they may influence microbial populations. The impact of Bt crops on bacterial communities has only been assessed under short-term, and results have been contradictory. Here, we analyzed the bacterial communities in three niches, rhizosphere soil (RS), root endosphere (RE) and leaf endosphere (LE), of three Bt rice and their non-Bt parental lines for three consecutive years by high-throughput sequencing. In principal coordinate analysis (PCoA) and PERMANOVA (Adonis) analysis, operational taxonomic units (OTUs) were clustered primarily by niche type and differed significantly in the RE and LE but not in the RS between each of three Bt lines compared with the non-Bt rice line, and not in each respective niche among the three Bt rice lines. The bacterial communities in the RS of different rice lines over the 3 years were clustered mainly by year rather than by lines. The differential bacterial taxa among the lines did not overlap between years, presumably because Cry proteins are rapidly degraded in the soil. A network analysis of RS bacterial communities showed that the network complexity and density for the three Bt rice lines did not decrease compared with those for the non-Bt line. In conclusion, our results demonstrated that bacterial communities differed significantly in RE and LE between Bt and non-Bt rice lines, but the differences were mild and transient, and had no adverse impact on RS over the 3 years. This study provides favorable evidence in support of the commercialization of Bt rice.

Next generation life science technologies will require the integration of building blocks with tunable physical and chemical architectures at the microscale. A central issue is to govern the multidimensional anisotropic space that defines these microparticle attributes. However, this control is limited to one or few dimensions due to profound fabrication tradeoffs, a problem that is exacerbated by miniaturization. Here, a vast number of anisotropic dimensions are integrated combining SU-8 photolithography with (bio)chemical modifications via soft-lithography. Microparticles in a 15-D anisotropic space are demonstrated, covering branching, faceting, fiducial, topography, size, aspect ratio, stiffness, (bio)molecular and quantum dot printing, top/bottom surface coverage, and quasi-0D, 1D, 2D, and 3D surface patterning. The strategy permits controlled miniaturization on physical dimensions below 1 m and molecular patterns below 1 m2 . By combining building blocks, anisotropic microparticles detect pH changes, form the basis for a DNA-assay recognition platform, and obtain an extraordinary volumetric barcoding density up to 1093 codes m-3 in a 3 12 0.5 m3 volume.

Coronavirus has been determined to be the cause of the recent outbreak of severe acute respiratory syndrome (SARS). Human coronavirus 229E had been studied well and its receptor-binding domain was restricted to aa417C547 of S protein. However, this region has no homology with the newly separated SARS-associated virus (Hong Kong isolate CUHK-W1). Then we analyzed the phylogenesis of S1 subunit of the coronavirus spike protein (SARS-associated virus, Hong Kong isolate CUHK-W1). Interestingly, the highest homology between murine hepatitis virus (MHV) and SARS-associated coronavirus was found. And the important sites (aa62C65 and aa214C216) on the spike protein of MHV with receptor-binding capacity were highly conservative in comparison with the newly separated SARS-associated virus (the corresponding sites are aa51C54 and aal95C197). These results from bioinformatics analysis might help us to study the receptor-binding sites of SARS-associated virus and the mechanism of the virus entry into the target cell, and design antiviral drugs and potent vaccines.

CONTEXT: The COVID-19 pandemic has impacted healthcare environment. OBJECTIVE: To determine the impact of the pandemic on self-reported outcomes in patients with adrenal insufficiency (AI). DESIGN AND SETTING: Prospective longitudinal survey study at 2 tertiary centers. PARTICIPANTS: Patients with AI. INTERVENTION: Patient-centered questionnaire. MAIN OUTCOME MEASURES: Depression Anxiety Stress Scales-21, Short Form-36, and AI self-management. RESULTS: Of 342 patients, 157 (46%) had primary AI, 109 (32%) had secondary AI, and 76 (22%) had glucocorticoid-induced AI. When compared to prepandemic, daily glucocorticoid dose and number of adrenal crises did not change. However, patients reported a higher financial impact from AI (34% vs 23%, Pa? =a? 0.006) and difficulty accessing medical care (31% vs 7%, Pa? <a? 0.0001) during the pandemic. A third of patients reported difficulty managing AI during the pandemic. After adjusting for duration and subtypes of AI, younger patients [odds ratio (OR) 2.3, CI 95% 1.3-4.1], women (OR 3.7, CI 95% 1.9-7.1), poor healthcare access(OR 4.2, CI 95% 2.3-7.7), lack of good insurance support (OR 2.8, CI 95% 1.3-5.9), and those with a higher financial impact (OR 2.3, CI 95% 1.3-4.3) reported greater difficulties managing AI. Patients were more likely to report a higher anxiety score (&#8805;8) if they found managing AI challenging during the pandemic (OR 3.0, CI 95% 1.3-6.9), and had lower Physical Component Summary (OR 4.9, CI 95% 2.2-11.0) and Mental Component Summary (OR 4.1, CI 95% 1.8-9.5) scores prior to the pandemic. CONCLUSIONS: A third of patients with AI reported difficulties with management of AI during the pandemic, particularly in younger patients, women, and those with poor healthcare access.

Especially in the wake of the recent COVID-19 pandemic, which has caused universities across the globe to suspend in-person classes, online alternatives for laboratory activities are needed Here, we report a choose-your-own-adventure (CYOA)-style activity, in which undergraduate general chemistry students influence the observed outcome of a prerecorded electrochemistry lab experiment During the activity, students decide how to build an electrochemical cell by varying experimental parameters including electrode charge, power source voltage, and salt addition We show evidence that students' understanding of electrochemistry concepts improved after completing the CYOA-style activity We propose that CYOA-style activities strike a good balance between the demand for instructor time and student opportunity to develop laboratory decision-making skills We suggest the use of CYOA-style activities as a better alternative to simply having students watch prerecorded videos of laboratory experiments when a traditional in-laboratory activity is impossible ?

Background: The COVID-19 pandemic represents a global challenge which may have pervasive effects in several areas of community and individual life Consequently, the virus could generate fear and anxiety that must be managed in a new and unknown situation, such as that of lockdown, with potential consequences for mental health outcomes Therefore, with the theoretical guide of the Polyvagal perspective, this research aimed to analyse the mediation of social support, passive aggression, avoidance and dissociation in the relationship between fear and anxiety during the COVID-19 pandemic Methods: During the national COVID-19 lockdown phase, a sample of 992 Italian participants with a mean age of 35 07 years (SD = 12 11) completed the Ten Penn State Worry Questionnaire, State-Trait Anxiety Inventory C Form X3, Coping Orientation to Problems Experienced and Forty Item Defense Style Questionnaire, after providing written informed consent Results: Results showed that fear affected anxiety, both directly and indirectly, highlighting a serial multiple mediation model with two parallel chain of mediators Social support coping strategy negatively influenced fear and passive aggression, which instead were positively associated Furthermore, in the second chain, avoidance directly induced fear in the presence of anxiety, opposite of dissociation defense mechanism Conclusions: Such findings highlighted some possible answers that could be implemented as a consequence of the fear perception during the COVID-19 lockdown, according to the framework of the Polyvagal Theory These data could provide an important contribution in shedding light on mechanisms put in place during the pandemic, promoting valuable information for a more effective clinical practice ? Mediterranean Journal of Clinical Psychology, Messina, Italy

SARS-CoV-2 pandemic is having a devastating effect on human lives Recent reports have shown that majority of the individuals recovered from COVID-19 have serious health complications, which is going to be a huge economic burden globally Given the wide-spread transmission of SARS-CoV-2 it is almost impossible to test every individual in densely populated countries Recent reports have shown that sewage-based surveillance can be used as holistic approach to understand the spread of the pandemic within a population or area Here we have estimated the spread of SARS-CoV-2 in the city of Hyderabad, India, which is a home for nearly 10 million people The sewage samples were collected from all the major sewage treatment plants (STPs) and were processed for detecting the viral genome using the standard RT-PCR method Interestingly, inlet samples of STPs were positive for SARS-CoV-2, while the outlets were negative, which indicates that the standard sewage treatment methods are efficient in eliminating the SARS-CoV-2 viral particles Based on the detected viral gene copies per litre and viral particle shedding per individual, the total number of individuals exposed to SARS-CoV-2 was estimated Through this study we suggest that sewage-based surveillance is an effective approach to study the infection dynamics, which helps in efficient management of the SARS-CoV-2 spread

The need for increased testing for SARS-CoV-2, the virus that causes COVID-19, has resulted in an increase of testing facilities outside of traditional clinical settings and sample handling by individuals without appropriate biohazard and biocontainment training. During the repatriation and quarantine of passengers from the Grand Princess cruise ship at a U.S. military base, biocontainment of a potentially infectious sample from a passenger was compromised. This paper describes the steps taken to contain the spill, decontaminate the area, and discusses the needs for adequate training in a biohazard response.

In "Cellular Immunology and COVID-19" (a Special Issue of Cells), a panel of leading scientists provides an exhaustive overview of the different aspects of the immune mechanisms underlying COVID-19 [...].

Throughout this pandemic, neurology resident education and service has, and will continue to be, affected during this unprecedented time. Balancing the safety of our residents as well as the anticipated inpatient service demands, we have, and continue to, make changes to meet the needs of our community. Education certainly has been affected but we have made great effort to maintain normalcy. We are leveraging web-based technologies to continue formal didactics. The American Academy of Neurology has provided program directors with various tools to share to provide high-yield academic education. AAN Synapse, distance learning modules, and podcasts are a few examples. Each residency training program will likely face different challenges depending on location and community structure. We have an obligation to help all of our colleagues in the hospital in providing quality and compassionate care during this time of need. Our training and education will only benefit from this experience teaching us lessons on adaptability, the importance of teamwork, and self-sacrifice.

BACKGROUND: Acceptance of a vaccine against SARS-CoV-2 is critical to achieving high levels of immunization. The objectives of this study were to understand mothers SARS-CoV-2 vaccine intentions to explore reasons for and against SARS-CoV-2 vaccination. METHODS: Participants from the All Our Families pregnancy longitudinal cohort whose children had reached ages 9C12 years were invited in MayCJune 2020 to complete a survey on the impact of COVID-19. The survey covered topics about the impact of the pandemic and included 2 specific questions on mothers intentions to vaccinate their child against SARS-CoV-2. Current responses were linked to previously collected data, including infant vaccine uptake. Multinomial regression models were run to estimate associations between demographic factors, past vaccination status and vaccination intention. Qualitative responses regarding factors affecting decision-making were analyzed thematically. RESULTS: The response rate was 53.8% (1321/2455). A minority of children of participants had partial or no vaccinations at age 2 (n = 200, 15.1%). A total of 60.4% of mothers (n = 798) intended to vaccinate their children with the SARS-CoV-2 vaccine, 8.6% (n = 113) did not intend to vaccinate and 31.0% (n = 410) were unsure. Lower education, lower income and incomplete vaccination history were inversely associated with intention to vaccinate. Thematic analysis of qualitative responses showed 10 themes, including safety and efficacy, long-term effects and a rushed process. INTERPRETATION: Within a cohort with historically high infant vaccination, a third of mothers remained unsure about vaccinating their children against SARS-CoV-2. Given the many uncertainties about future SARS-CoV-2 vaccines, clear communication regarding safety will be critical to ensuring vaccine uptake.

It has been one year since the outbreak of the COVID-19 pandemic. The good news is that vaccines developed by several manufacturers are being actively distributed worldwide. However, as more and more vaccines become available to the public, various concerns related to vaccines become the primary barriers that may hinder the public from getting vaccinated. Considering the complexities of these concerns and their potential hazards, this study aims to offer a clear understanding about different population groups' underlying concerns when they talk about COVID-19 vaccines, particular those active on Reddit. The goal is achieved by applying LDA and LIWC to characterizing the pertaining discourse with insights generated through a combination of quantitative and qualitative comparisons. Findings include: 1) during the pandemic, the proportion of Reddit comments predominated by conspiracy theories outweighed that of any other topics; 2) each subreddit has its own user bases, so information posted in one subreddit may not reach those from other subreddits; 3) since users' concerns vary across time and subreddits, communication strategies must be adjusted according to specific needs. The results of this study manifest challenges as well as opportunities in the process of designing effective communication and immunization programs.

Introduction In this article we pose the questions of how to manage PDPH in the COVID-19 positive patient and more specifically, the use of epidural blood patch (EBP) EBP in COVID-19 Patients Carries Additional Risks A primary concern in the use of EBP in these patients is the possibility of seeding the virus in the CNS Another important concern is related to the known hypercoagulable state in COVID-19 positive patients and associated organ dysfunction that may alter the metabolism of anticoagulants The safety of the providers performing the EBP, the position of the patient and choices for image guidance (blind, fluoroscopic) are also key considerations to review It is also important to explore the current state of knowledge about using allogenic instead of autologous blood as well as emerging techniques to eliminate the coronavirus from the blood Other Options for Treating PDPH in COVID-19 Patients EBP is usually considered after the failure of conservative and pharmacological treatments Because of the additional risks of EBP in COVID-19 patients it is important to also consider less traditional pharmacological treatments such as theophylinnes and cosyntropin that may offer some additional benefit for COVID-19 patient Finally, other interventions other than EBP should also be considered including occipital nerve blocks, sphenopalatine ganglion blocks (infratemporal or transnasal) Clinical Recommendation We conclude our article with recommendations on how to approach the treatment of PDPH for their COVID-19 patients

The ongoing Coronavirus disease 2019 (COVID-19) is a major crisis that has significantly affected the healthcare sector and global economies, which made it the main subject of various fields in scientific and technical research. To properly understand and control this new epidemic, mathematical modelling is presented as a very effective tool that can illustrate the mechanisms of its propagation. In this regard, the use of compartmental models is the most prominent approach adopted in the literature to describe the dynamics of COVID-19. Along the same line, we aim during this study to generalize and ameliorate many existing works that consecrated to analyse the behaviour of this epidemic. Precisely, we propose an SQEAIHR epidemic system for Coronavirus. Our constructed model is enriched by taking into account the media intervention and vital dynamics. By the use of the next-generation matrix method, the theoretical basic reproductive number $R_0$ is obtained for COVID-19. Based on some nonstandard and generalized analytical techniques, the local and global stability of the disease-free equilibrium are proven when $R_0<1$. Moreover, in the case of $R_0>1$, the uniform persistence of COVID-19 model is also shown. In order to better adapt our epidemic model to reality, the randomness factor is taken into account by considering a proportional white noises, which leads to a well-posed stochastic model. Under appropriate conditions, interesting asymptotic properties are proved, namely: extinction and persistence in the mean. The theoretical results show that the dynamics of the perturbed COVID-19 model are determined by parameters that are closely related to the magnitude of the stochastic noise. Finally, we present some numerical illustrations to confirm our theoretical results and to show the impact of media intervention and quarantine strategies.

Home-based primary care (HBPC) practices rapidly adapted to maintain care during the COVID-19 pandemic. This mixed-methods national online survey of HBPC practices probed responses to COVID-19 surges, COVID-19 testing, the use of telemedicine, practice challenges due to COVID-19, and adaptations to address these challenges. Seventy-nine practices across 29 states were included in the analyses. Eighty-five percent of practices continued to provide in-person care and nearly half cared for COVID-19 patients. Most practices also pivoted to concurrent use of video visits. The top five practice challenges were: patient familiarity with telemedicine, patient and clinician anxiety, technical difficulties reaching patients, and supply shortages. Practices also described creative strategies to physically support the needs of patients. These findings illustrate the need to balance in-person and virtual care for this population, and attend to the emotional needs of patients and staff.

Due to the intrinsic complexity and nonlinearity of chemical reactions, direct applications of traditional machine learning algorithms may face with many difficulties. In this study, through two concrete examples with biological background, we illustrate how the key ideas of multiscale modeling can help to reduce the computational cost of machine learning a lot, as well as how machine learning algorithms perform model reduction automatically in a time-scale separated system. Our study highlights the necessity and effectiveness of an integration of machine learning algorithms and multiscale modeling during the study of chemical reactions.

BACKGROUND/PURPOSE: Oral exercise is a training method for swallowing dysfunction in older adults. The study investigated the effect of oral exercise on tongue pressure in older adults in Taiwanese community day care centers over a 3-month period. MATERIALS AND METHODS: Participants over age 50 who were able to communicate and participating for the duration of the 12-week period were recruited from five community day care centers. A 15-min weekly group oral exercise activity was conducted. The tongue pressures were measured and multivariable linear regression models were used to assess the effect of oral exercise intervention on the participants tongue pressures. RESULTS: A total of 66 older adult participants, among whom the mean age was 78.06 10.74 years. Tongue pressure continued improving during the intervention period, and the mean tongue pressure at the end of the study was 20.63 10.45 kPa, which was significantly higher than the baseline measurement (16.92 10.62 kPa, p < 0.001). Participants exhibited significant improvement in tongue pressure regardless of their age groups. Moreover, participants with one to seven pairs of functional tooth units (FTUs) exhibited significantly more improvement in tongue pressure (16.00 kPa, 95% CI = 2.58C29.43) than those without FTUs (p = 0.021). CONCLUSION: Oral exercise over a 3-month period significantly improved tongue pressure among the study participants regardless of their gender or age group. Oral exercise should be integrated into comprehensive health promotion programs to assist in the improvement and maintenance of oral function among older adults.

This qualitative study is part of Smart Indigenous Youth, a digital health community trial involving rural schools in Saskatchewan, Canada. Secondary school administrators and educators were engaged as citizen scientists in rural Indigenous communities to understand rapid decision-making processes for preserving school health during the COVID-19 pandemic, and to inform evidence-based safe school policies and practices. After COVID-19 restrictions were implemented, key informant interviews and focus groups were conducted with school administrators and educators, respectively, to understand the impact of school responses and decision-making processes. Two independent reviewers conducted thematic analyses and compared themes to reach consensus on a final shortlist. Four main themes emerged from the administrator interviews, and six main themes were identified from the educator focus group discussions which revealed a pressing need for mental health supports for students and educators. The study findings highlight the challenges faced by schools in rural and remote areas during the COVID-19 pandemic, including school closures, students' reactions to closures, measures taken by schools to preserve health during the pandemic, and different approaches to implement for future closures. Citizen scientists developed a set of recommendations, including the need for structured communication, reflection meetings, adequate funding, and external monitoring and evaluation to guide evidence-based safe school policies and practices during the pandemic.