bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical characteristics and risk factors for mortality among COVID-19 hospitalized patients in UAE: Does ethnic origin have an impact
Authors: AbuRuz Salah , Al-Azayzih Ahmad , ZainAlAbdin Sham , Beiram Rami , Al Hajjar Mohammed 
Published: March 2022

Background
The relationship between COVID-19 patient’s clinical characteristics and disease manifestation remains incompletely understood. The impact of ethnicity on mortality of patients with COVID-19 infection is poorly addressed in the literature. Emerging evidence suggests that many risk factors are related to symptoms severity and mortality risk, emphasizing the necessity of fulfilling this knowledge gap that may help reducing mortality from COVID-19 infections through tackling the risk factors.

Aims
To explore epidemiological and demographic characteristics of hospitalized COVID-19 patients from different ethnic origins living in the UAE, compare them to findings reported across the globe and determine the impact of these characteristics and ethnicity on mortality during hospitalization.

Methods
A single center, retrospective chart review study of hospitalized COVID-19 patients was conducted in a large COVID-19 referral hospital in UAE. The following outcomes were assessed: patients’ clinical characteristics, disease symptoms and severity, and association of ethnicity and other risk factors on 30-day in hospital mortality.

Results
A total of 3296 patients were recruited in this study with an average age of 44.3±13.4 years old. Preliminary data analysis indicated that 78.3% (n = 2582) of cases were considered mild. Average duration of hospital stay was 6.0±7.3 days and 4.3% (n = 143) were admitted to ICU. The most frequently reported symptoms were cough (32.6%, n = 1075) and fever (22.2%, n = 731). The 30-day mortality rate during hospitalization was 2.7% (n = 90). Many risk factors were associated with mortality during hospitalization including: age, respiratory rate (RR), creatinine, and C-reactive protein, oxygen saturation (SaO2), hemoglobin, hematocrit, ferritin, creatinine, C-reactive protein, anemia, COPD, Chronic kidney disease, dyslipidemia, Vitamin-D Deficiency, and ethnic origin (p <0.05). Multiple logistic regression analysis showed that higher mortality rates during hospitalization was associated with anemia, chronic obstructive pulmonary disease (COPD), chronic kidney disease, and Middle Eastern origin (p<0.05).

Conclusion
The results indicated that most COVID-19 cases were mild and morality rate was low compared to worldwide reported mortality. Mortality rate during hospitalization was higher in patients from Middle East origin with preexisting comorbidities especially anemia, COPD, and chronic kidney disease. Due to the relatively small number of mortality cases, other identified risk factors from univariate analysis such as age, respiratory rate, and Vitamin-D (VitD) deficiency should also be taken into consideration. It is crucial to stratify patients on admission based on these risk factors to help decide intensity and type of treatment which, possibly, will reduce the risk of death.
Effect of flow diverter stent malposition on intracranial aneurysm hemodynamics—An experimental framework using stereoscopic particle image velocimetry
Authors: Roloff Christoph , Berg Philipp 
Published: March 2022

BackgroundFlow-diverting stents are increasingly used for the minimally-invasive treatment of intracranial aneurysms. However, a correct positioning of such devices can be challenging due to varying vessel diameters as well as the complex anatomy of the neurovasculature. As a consequence, unsuccessful treatment outcomes are increasingly reported requiring an improvement of the understanding of stent-induced flow modification.MethodsTo evaluate the effect of different degrees of flow diverter stent malposition on intra-aneurysmal hemodynamic changes, a controlled hemodynamic configuration was created using an idealized intracranial aneurysms model. Afterwards, four different treatment scenarios were reproduced comprising of 1) the ideal treatment, 2) an insufficient wall apposition in the region of the ostium, 3) a distorted device migrating into the aneurysm sac and 4) an inaccurately deployed stent due to wrong release location. For the assessment of the individual flow modifications, high-resolution stereoscopic particle image velocimetry (PIV) measurements were carried out.ResultsThe analysis of the precisein-vitroPIV measurements reveals that in all cases a considerable reduction of the cycle-averaged and peak-systolic velocity was obtained. Compared to the untreated aneurysm configuration, the flow reduction ranged from 63% (scenario 4) up to 89% (scenario 3). The ideal treatment reached a reduction of 78%, which is known to be sufficient for a successful therapy. However, inaccurate device positioning leads to increased oscillating flow towards the lateral directions reducing the chances of sufficient thrombus formation.ConclusionsHigh-resolutionin-vitroPIV measurements enable an accurate quantification of the treatment efficacy for flow-diverting devices. Furthermore, insufficient treatment outcomes can be reproduces allowing for an assessment of intra-aneurysmal hemodynamic changes.
Evaluation of pharmacovigilance systems for reporting medication errors in Africa and the role of patients using a mixed-methods approach
Authors: Sabblah George Tsey , Seaneke Seth Kwaku , Kushitor Mawuli , van Hunsel Florence , Taxis Katja , Duwiejua Mahama , van Puijenbroek Eugène 
Published: March 2022

Background
Reviewing the epidemiological profile of medication errors (MEs) reported by African countries and the systems put in place to report such errors is crucial because reporting plays an important role in improving patient safety. The objectives of this study were to characterize the profile of spontaneously reported MEs submitted by African countries to VigiBase; the World Health Organization (WHO) global database of individual case safety reports, describe systems in place for reporting these errors, and explore the challenges and facilitators for spontaneous reporting and understand the potential role of patients.

Methods
In the present study, we used, a mixed-methods sequential explanatory design involving a quantitative review of ME reports over a 21-year period (1997–2018) and qualitative interviews with employees from African countries that are members of the WHO Program for International Drug Monitoring (WHO PIDM). Descriptive statistics were used to summarize key variables of interest.

Results
A total of 4,205 ME reports were submitted by African countries to VigiBase representing 0.4% of all reports in the database. Only 15 countries out of the 37 WHO PIDM members from Africa contributed ME to reports, with 99% (3,874) of them reports originating from Egypt, Morocco, and South Africa. The reasons given for low reporting of MEs were weak healthcare and pharmacovigilance systems, lack of staff capacity at the national centers, illiteracy, language difficulties, and socio-cultural and religious beliefs. Some facilitators suggested by the participants to promote reporting included proactive engagement of patients regarding issues relating to MEs, leveraging on increased technology, benchmarking and mentoring by more experienced national centers. Sixteen of the twenty countries interviewed had systems for reporting MEs integrated into adverse drug reaction reporting with minimal patient involvement in seven of these countries. Patients were not involved in directly reporting MEs in the remaining 13 countries.

Conclusions
MEs are rarely reported through pharmacovigilance systems in African countries with limited patient involvement. The systems are influenced by multifactorial issues some of which are not directly related to healthcare.
COVID-19 related knowledge, attitudes, and practices in Indian Population: An online national cross-sectional survey
Authors: Singh Piyoosh Kumar , Anvikar Anup , Sinha Abhinav 
Published: March 2022

Introduction
This highly contagious zoonotic corona virus (SARS-CoV-2) spread to most parts of the world (200 countries) and created a public health emergency. Due to its novel nature and indistinctness, different sources of information and suggestions were developed to guide the individuals about its transmission and prevent its infection. Responses to the active intervention efforts have posed some relevant questions on population understanding and attitudes toward COVID-19. The present study is aims to assess the COVID-19 related knowledge, attitude, and practices (KAP) in a heterogeneous Indian population.

Material and methods
501 respondents across India participated in a questionnaire-based online survey from April 2020 to May 2020. The questionnaire incorporated 56 questions about demographic characteristics and KAP dimensions. The mixed (quantitative and qualitative) methods were employed to evaluate KAP dimensions. Descriptive analysis was estimated as means, SD, and proportion. The bivariate (χ2), correlation, and regression analysis were utilized for the response analysis. In addition, qualitative analysis, including content and thematic analysis were done for open-ended questions.

Result
High knowledge and positive attitude were reported in more than half of the study population, with a proportion of 58.6% and 62.1%, respectively. Education shows a significant difference in the knowledge and attitude dimensions. The good practice (50.5% of the total population) reported a significant difference in age and gender categories with the test of independence (χ2). Prevention (56.89%) in knowledge domain and risk (17.56%), information-seeking (45.51%), prevention (51.50%), and treatment-seeking (54.29%) in attitude domains recorded low proportion. KAP variables were found in association in Pearson correlation analysis. In logistic regression analysis, knowledge was the strongest predictor for the positive attitude, whereas attitude was reported as the best predictor for good practice outcome.

Conclusion
The study presents a moderate level of covid related knowledge, Attitudes, and Practices in Indian population.
The estimated benefits of increasing cigarette prices through taxation on the burden of disease and economic burden of smoking in Nigeria: A modeling study
Authors: Bardach Ariel , Casarini Agustín , Rodriguez Cairoli Federico , Adeniran Adedeji , Castradori Marco , Akanonu Precious , Onyekwena Chukwuka , Espinola Natalia , Pichon-Riviere Andrés , Palacios Alfredo 
Published: March 2022

Background
Globally, tobacco consumption continues to cause a considerable burden of preventable diseases. Although the smoking prevalence in Nigeria may be declining over the last years, the absolute number of active smokers remains one of the highest in Africa. Little is known about the disease burden and economic costs of cigarette smoking in Nigeria. Consequently, there is an evidence gap to inform the design and implementation of an effective policy for tobacco control.

Methods
We applied a microsimulation model to estimate the burden attributable to smoking in terms of morbidity, mortality, disability-adjusted life-years (DALYs), and direct medical costs and indirect costs (e.g., productivity loss costs, informal caregivers’ costs). We also modeled the health and economic impact of different scenarios of tobacco price increases through taxes.

Results
We estimated that smoking is responsible for approximately 29,000 annual deaths in Nigeria. This burden corresponds to 816,230 DALYs per year. In 2019, the total economic burden attributable to tobacco was estimated at ₦ 634 billion annually (approximately U$D 2.07 billion). If tobacco cigarettes’ prices were to be raised by 50% through taxes, more than 30,000 deaths from smoking-attributable diseases would be averted in 10 years, with subsequent savings on direct and indirect costs of ₦597 billion and increased tax revenue collection of ₦369 billion.

Conclusion
In Nigeria, tobacco is responsible for substantial health and economic burden. Increasing tobacco taxes could reduce this burden and produce net economic benefits.
Analysing the impact of COVID-19 risk perceptions on route choice behaviour in train networks
Authors: Shelat Sanmay , van de Wiel Thijs , Molin Eric , van Lint J. W. C. , Cats Oded 
Published: March 2022

Introduction
Unlike previous pandemics, COVID-19 has sustained over a relatively longer period with cyclical infection waves and numerous variants. Public transport ridership has been hit particularly hard. To restore travellers’ confidence it is critical to assess their risk determinants and trade-offs.

Methods
To this end, we survey train travellers in the Netherlands in order to: (i) quantify the impact of trip-specific, policy-based, and pandemic-related attributes on travellers’ COVID-19 risk perceptions; and (ii) evaluate the trade-off between this risk perception and other travel attributes. Adopting the hierarchical information integration approach, in a two-stage stated preference experiment, respondents are asked to first rate how risky they perceive different travel situations to be, and then to choose between different travel options that include their own perceived risk rating as an attribute. Perceived risk ratings and choices between travel options are modelled using a linear regression and a mixed multinomial logit model, respectively.

Results
We find that on-board crowding and infection rates are the most important factors for risk perception. Amongst personal characteristics, the vulnerability of family and friends has the largest impact—nearly twice that of personal health risk. The bridging choice experiment reveals that while values of time have remained similar to pre-pandemic estimates, travellers are significantly more likely to choose routes with less COVID-19 risk (e.g., due to lower crowding). Respondents making longer trips by train value risk four times as much as their shorter trip counterparts. By combining the two models, we also report willingness to pay for mitigating factors: reduced crowding, mask mandates, and increased sanitization.

Conclusion
Since we evaluate the impact of a large number of variables on route choice behaviour, we can use the estimated models to predict behaviour under detailed pandemic scenarios. Moreover, in addition to highlighting the importance of COVID-19 risk perceptions in public transport route choices, the results from this study provide valuable information regarding the mitigating impacts of various policies on perceived risk.
Genetic and hosts characterization of hantaviruses in port areas in Hainan Province, P. R. China
Authors: Wang Qiu-wei , Tao Li , Lu Su-ying , Zhu Chang-qiang , Ai Le-le , Luo Yizhe , Yu Rong-bin , Lv Heng , Zhang Yun , Wang Chong-cai , Tan Wei-long 
Published: March 2022

Background
Hantaviruses (HVs) are major zoonotic pathogens in China that cause hemorrhagic fever with renal syndrome (HFRS) posing a major threat to people’s health. Hainan Province, an island located in Southeast China, is an ideal region for sea ports. The unique tropical monsoon climate in Hainan provides sufficient living conditions for rodents, which help spread HVs and other rodent-borne diseases. In the routine monitoring of hantavirus, there was no evidence that rodents in Hainan carried hantavirus. No patients infected with hantavirus were found in the past. However, the surveillance of HVs-carrying rodents covering the whole territory of Hainan has not stopped.

Methodology/principal findings
For the monitoring of the prevalence of HVs in rodents and the search for theoretical reference for rodent control and HFRS prevention, a total of 60 rodents from 6 monitoring spots were trapped around main ports in Hainan between 2016 and 2019. HV positive samples were identified by a specific kit and sequenced. The data indicated that seven rodents (Rattus norvegicus) were positive for hantavirus with a positivity rate of 11.67%. Phylogenetic analysis suggested that the two complete sequence strains HN1 and HN4 in this research were highly similar to the sequence strains GZRn36 and GZRn148 isolated in Guangdong Province, and they located in the same phylogenetic tree branch which belongs to S2 subtype. Although the two partial sequences HT1 and HT2 isolated in Xisha Islands belong to S2 subtype according to the phylogenetic tree of L segment, they showed a great nucleotide difference with HN1 and HN4. We also found 13 amino acid variations compared with SEOV 80–39 and 6 amino acid mutations related to epitope, and the variations may reduce the effectiveness of the current HFRS vaccines used in humans.

Conclusions/significance
The study indicated HVs carried by rodents found in Hainan Province may be transmitted from Guangdong Province through trading ports and carriage of goods by sea. So it is of great significance to strengthen the surveillance of rodents in port areas especially capture and eliminate rodents on ship. Timely elimination of host animals of hantavirus in port areas is necessary to prevent an outbreak of HVs disease.
Using Artificial Intelligence for Analyzing Retinal Images (OCT) in People with Diabetes: Detecting Diabetic Macular Edema Using Deep Learning Approach
Authors: Daghistani Tahani 
Published: March 2022

Medical imaging evolved rapidly to play a vital role in diagnosis and treatment of a disease. Automate analysis of medical image analysis has increased effectively through the use of deep learning techniques to obtain much quicker classifications once trained and learn relevant features for specific tasks, shown to be assessable in clinical practice and valuable tool to support decision making in medical field. Within Opthalmology, Optical Coherence Tomography (OCT) is a volumetric imaging procedure that uses in the diagnosis, monitoring and measuring response to treatment in eyes. Early detection of eyes diseases including Diabetic Macular Edema (DME) is vital process to avoid complications such as blindness. This work employed a deep convolutional neural network (CNN) based method for DME classification task. To demonstrate the impact of convolutional, five models with different Convolutional layers built then the best one selected based on evaluation metrics. The accuracy of model improved while increasing the number of Convolutional Layers and achieved 82% by 5-Convolutional Layer, Precision and Recall of CNN model per DME class was 87%% and 74%, respectively. These results highlighted the potential of deep learning in assisting decision-making in patients with DME.
Nguyen’s tridents and the classification of semigraphical translators for mean curvature flow
Authors: Hoffman David , Martín Francisco , White Brian 
Published: March 2022

Abstract
We construct a one-parameter family of singly periodic translating solutions to mean
curvature flow that converge as the period tends to 0 to the union of a grim reaper surface
and a plane that bisects it lengthwise. The surfaces are semigraphical: they are properly embedded,
and, after removing a discrete
collection of vertical lines, they are graphs.
We also provide a nearly complete classification of semigraphical translators.
Spectral description of Fredholm operators via polynomially Riesz operators perturbation
Authors: Abdmouleh Faiçal , Khlif Hassen , Walha Ines 
Published: March 2022

Abstract
In this paper, we establish some spectral analysis in Fredholm theory involving the concept of a polynomially Riesz operators perturbation. Moreover, we apply the obtained results to analyze the incidence of some essential spectra of a perturbed operator via this kind of perturbation. Our approach allows us to investigate a new description in the theory of unbounded operator matrices defined with maximal domain via this kind of perturbation. Finally, we conclude by presenting some progress in the theory of polynomially operators and the theory of semi-Fredholm and semi-Browder operators.
Rheological Characterization of Sulfuric Acid Solutions of Poly(p-phenyleneterephthalamide)
Authors: Kim B. C. , Hwang S. S. , Kim K. U. 
Published: March 2022

Abstract
Several grades of poly(p-phenyleneterephthalamide) (PPD-T) with different molecular weights were prepared. The rheological properties of sulfuric acid solutions of PPD-T were measured. In the vicinity of the critical concentration tan <5 and η'/G' exhibited a minimum value, but G'/2G" and η* showed a maximum value. High concentrations produce an anisotropic phase. Tendencies of yield behavior were observed for these solutions in the anisotropic phase. Above the saturated concentration the solution system showed gel-like properties, i. e., with increasing concentration abrupt reduction of G'/2G” and abrupt increases of η*, η'/G' and tan δ were observed. With increasing temperature the viscosity of isotropic and anisotropic phases was decreased but that of biphase was increased. The critical concentration was reduced with increasing molecular weight, but increased with increasing temperature. Use of reduced variables seemed to eliminate molecular weight dependency on the critical concentration curve. The shear viscosity appeared to be proportional to (Mw)6,7.
Characterization of Distributive Mixing in Polymer Processing Equipment using Renyi Entropies
Authors: Wang W. , Manas-Zloczower I. , Kaufman M. 
Published: March 2022

Abstract
A new method for characterization of distributive mixing in processing equipment, based on Renyi entropies, was developed. This method was applied to a twin-flight single screw extruder, in which tracer positions were determined through computer simulations of the flow field. The various entropies were calculated using particle concentrations in equal area domains of the mixer. Renyi entropies, which are function of a parameter β, were calculated for extruders of different lengths. We discuss the merit of using Renyi entropies for different values of β by pointing to the different mixing characteristics they probe. The relative Renyi entropy varies between 0 and 1 and represents a measure of distributive mixing quality, with 1 corresponding to perfect mixing and 0 corresponding to poorest mixing. We compare this new method of distributive mixing characterization to traditional ones based on the concepts of Scale and Intensity of Segregation, and the calculations based on Pairwise Correlations and Correlation Sums. The results show good agreement between the relative Renyi entropy and the traditional methods. Other advantages of the Renyi entropy such as reduced calculation time and geometric independence are discussed. For the case of a twin-flight single screw extruder, it is shown that a longer extruder is not necessarily more beneficial to distributive mixing.
Direct Method for Deconvoluting Two Residence Time Distribution Curves
Authors: Canevarolo S. V. , Mélo T. J. A. , Covas J. A. , Carneiro O. S. 
Published: March 2022

Abstract
A pair of related Residence Time Distribution (RTD) curves obtained experimentally during extrusion, are deconvoluted using a methodology based on the concept of equivalent residence times. Two points of two RTD curves are equivalent when the same percentage of tracer has exited the system. The time scale of the deconvoluted curve is obtained by subtracting the two equivalent time values of the available RTD curves. The method was tested using simulated pulse-shaped RTD curves and also carrying out measurements on a twin screw extruder. Despite the experimental errors involved, the two tests seem to demonstrate the usefulness of the approach.