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Evidence-based practice (EBP) has gained attention globally from healthcare professionals and researchers. The aim of this study was to assess Jordanian diagnostic radiographers' knowledge, attitude, education/knowledge, and skills related to EBP; and identify specific terms related to EBP. A paper-based, self-administered questionnaire with two sections was used. The first section included 11 socio-demographic questions and the second section contained 56 questions regarding EBP categorized under seven distinct subscales. The data were imported into SPSS for analysis. Responses were received from 203 radiographers, most of them 135 (66.5%) aged 21–30 years. The majority of radiographers agreed or strongly agreed that the application of EBP is necessary for radiography practice, and 129 (63.6%) of radiographers learned the foundations of EBP as part of their academic preparation. Less than half of the participants stated that they completely understood the research terminology listed in the survey. Most participants had access to the internet and research databases, 79.3% (n = 161). The majority of participants, 63.1% (n = 128) stated that they always used their personal experience, as a source to make a clinical decision in radiography practice. The most common barrier to the implementation of EBP was insufficient time (63.5%, n = 129). This study showed that despite the positive attitude, and beliefs of radiographers toward EBP, and access to information resources, radiographers still need a higher level of confidence in their ability to engage in and implement EBP; including increased education to support the research skills needs to search and interpret publications. The findings of this study may help inform restructure of the undergraduate radiography curriculum, training programs or other interventions required to promote or facilitate the adoption of EBP in Jordan. [ABSTRACT FROM AUTHOR]

Background: To date, there is no effective treatment for COVID-19. Vaccines are effective and safe strategies to control the pandemic.Objective: To measure consumers' maximum willingness to pay (WTP) for COVID-19 vaccines in Jordan and to identify the predictors of WTP.Method: An online survey was used to collect data related to sociodemographic factors and constructs from the Health Belief Model (HBM). The contingent valuation method using the payment card approach was used, whereby the respondents were asked to choose their maximum WTP value from a range of 5-200 Jordanian Dinar (JOD). The maximum WTP values were then categorized into several groups, and an ordered logistic model was used to generate adjusted odds ratios and estimate the significant predictors of maximum WTP.Results: A total of 3116 respondents completed the survey. More than half of the sample were not willing to pay out of pocket for the vaccine (57%). Among the respondents who were willing to pay any amount above zero, the mean maximum WTP was 28.1 JOD (39.63 USD), and the median WTP was 20 JOD (28.21 USD). The significant predictors of higher WTP values were being of younger age, higher income, being a healthcare provider, having one or more chronic diseases, previous history of receiving the seasonal influenza vaccine, having a family member/friend who has died from the COVID-19, lower perceived risk of the vaccine, higher perceived benefits of the vaccine, and having been recommended to get the vaccine.Conclusion: It is recommended to continue providing the vaccine free of charge to increase its uptake. Educational campaigns should focus on refuting myths related to the vaccine and promoting the benefits of receiving the vaccine in slowing the spread of the pandemic, and improving the economy. Healthcare providers' recommendations have the potential to increase WTP for the vaccine. [ABSTRACT FROM AUTHOR]

Chromium nitride thin films were prepared by reactive radio frequency magnetron sputtering on glass and Si(001) substrates. Thin films were grown at different nitrogen to argon flow rate ratio and their effect on the film composition, band gap and electronic phase transition was studied by different experimental technique. X-ray diffraction analyses establish that CrN films predominantly grow in [111] CrN and [002] CrN directions irrespective of the substrates used for the growths. The band gap was found to vary with the composition of the films. All films are semiconducting at room temperature and show discontinuity in their resistivity versus temperature curve indicating electronic transition. But the low temperature electronic phase depends on the growth conditions and composition of the films. [ABSTRACT FROM AUTHOR]

Population synthesis involves generating synthetic yet realistic representations of a target population of micro-agents for behavioral modeling and simulation. Traditional methods, often reliant on target population samples, such as census data or travel surveys, face limitations due to high costs and small sample sizes, particularly at smaller geographical scales. We propose a novel framework based on copulas to generate synthetic data for target populations where only empirical marginal distributions are known. This method utilizes samples from different populations with similar marginal dependencies, introduces a spatial component into population synthesis, and considers various information sources for more realistic generators. Concretely, the process involves normalizing the data and treating it as realizations of a given copula, and then training a generative model before incorporating the information on the marginals of the target population. Utilizing American Community Survey data, we assess our framework's performance through standardized root mean squared error (SRMSE) and so-called sampled zeros. We focus on its capacity to transfer a model learned from one population to another. Our experiments include transfer tests between regions at the same geographical level as well as to lower geographical levels, hence evaluating the framework's adaptability in varied spatial contexts. We compare Bayesian Networks, Variational Autoencoders, and Generative Adversarial Networks, both individually and combined with our copula framework. Results show that the copula enhances machine learning methods in matching the marginals of the reference data. Furthermore, it consistently surpasses Iterative Proportional Fitting in terms of SRMSE in the transferability experiments, while introducing unique observations not found in the original training sample. • A data fusion technique is formulated for the generation of synthetic populations at different geographical level. • A data normalization approach based on Copula is proposed to enhance machine learning methods. • The method allows for the transfer of a model learned from one population to another. • Test experiments encompass transfer tests between regions at the same geographical level, as well as to lower geographical levels. [ABSTRACT FROM AUTHOR]

Osteopontin (OPN) is a multifunctional matrix glycoprotein with neuroprotective and immunomodulatory properties. This study explored the potential of OPN-loaded acellular nerve allografts (ANAs) to repair sciatic nerves in male Wistar rats. The research also delved into the impact of OPN on macrophage phenotypes. We reconstructed a 10 mm nerve gap with ANAs containing OPN at 2 nM and 4 nM. The sciatic functional index (SFI) and paw withdrawal reflex latency (WRL) showed the significant efficacy of ANA/OPN (2 nM) in enhancement of target organ reinnervation and subsequent sensorimotor recovery compared to other groups. Electrophysiological and histomorphometric analyses further supported the regenerative properties of ANA/OPN (2 nM). Additionally, ANA/OPN (2 nM) promoted macrophage polarization towards an M2 phenotype and reduced proinflammatory cytokines at the injury site. In conclusion, the study suggested that ANA loaded with 2 nM OPN effectively repaired transected sciatic nerves in rats, potentially through enhancing axonal sprouting and exerting anti-inflammatory effects. • Inflammation is vital for nerve regeneration it eliminates growth-inhibiting components and creates a supportive environment for axonal regrowth. • Macrophages are essential for peripheral nerve regeneration and play a crucial role in the immune response and tissue repair. • Osteopontin is a multifunctional glycoprotein with both pro-inflammatory and anti-inflammatory properties. This dual functionality of osteopontin highlights its complex role in immune response modulation. [ABSTRACT FROM AUTHOR]

Kalman filter and its different variants are commonly used as optimal methods for fault detection in various types of system components. In this paper, a newly introduced type of aforementioned filters, called modal Kalman filter, is extended and utilized in order to estimate the states of nonlinear systems, for sensor fault detection purposes, in a class of nonlinear certain systems. This method, in contrast to the extended Kalman filter, which employs only the linear term of Taylor expansion, retains higher-order terms; as a result, the estimation error will reduce accordingly. Practicality and effectivity of this method, and its superiority over Kalman filter, in terms of accuracy and promptness of sensor fault detection, are also verified with simulation results. • A novel model-based fault detection approach, based on a new modification of Kalman filter is proposed. • This approach, called Modal Kalman filter, is based on modal series. • Applied to nonlinear systems for sensor fault detection. • Both bias fault and loss of effectiveness fault are taken into consideration. • The results approve the efficiency of the proposed filter. [ABSTRACT FROM AUTHOR]

To assess the prevalence of potential drug-drug interactions (pDDIs) among polypharmacy patients in Jordan using Lexicomp®. Additionally, this study aims to categorize and rate the identified pDDIs according to interaction risk, severity, and reliability. A descriptive cross-sectional study was conducted at six different hospitals representing different public health sectors in Jordan (ministry of health, royal medical services, and university-affiliated hospitals). Polypharmacy patients from outpatient clinics (e.g., cardiology,& and internal medicine) were identified, recruited, and interviewed by clinical pharmacists. pDDIs were assessed using the Lexicomp® mobile application and classified according to interaction risk rating, severity, and reliability rating. Furthermore, the prevalence of pDDIs across chronic medical conditions was assessed. P-value <0.05 was considered as significant. A total of 801 patients with polypharmacy were identified. The average number of drugs per patient was 6.6 ± 1.96, with an average of 4.2 ± 3.0 pDDIs per patient. Potential drug-drug interactions were detected in 769 patients (96%), with a total of 3359 interactions. Blood pressure lowering agents were involved in 39.9% of the pDDIs. Cardiovascular system drugs contributed to the largest share of pDDIs (46.6%). While diuretics had the major share of interactions among cardiovascular system drugs (16.2%), drugs used in diabetes had the highest share across all groups (17.1%). The majority of pDDIs were of "C" risk rating with a moderate interaction severity, whilst 1.6% of pDDIs could have been avoided in the first place as the concurrent administration of these agents is contraindicated (i.e., risk rating X). Patients with cardiovascular diseases, diabetes, chronic obstructive pulmonary disease, gout, and chronic kidney disease were associated with the highest number of potential drug-drug interactions. Our study showed that 96% of polypharmacy patients at outpatient clinics have at least one pDDI. Almost half of the detected interactions involved cardiovascular medications. The majority of these pDDIs had moderate severity, with no more than 10% of the interactions requiring therapy modification. [ABSTRACT FROM AUTHOR]