The Dynamic of Foreign Visitors in Romania since 1990. Current Challenges of Romanian Tourism

This study represents a quantitative and qualitative analysis of the Romanian tourism phenomenon that focuses on the current challenges to which it has to adapt in order to become competitive on the European market and to overcome its current stage of subsistence tourism. One of the selected criteria for highlighting the main dysfunctions of the Romanian tourism and that also represents the goal of this research is one of the indicators that quantify the annual flow of international tourists that come to Romania. In Romania's post-communist economic development (a negative evolution, of course), tourism remains a real lever for national and regional economic development that can bring Romania numerous competitive advantages on the European Union market

3D Printing of Alginate-Natural Clay Hydrogel-Based Nanocomposites

Biocompatibility, biodegradability, shear tinning behavior, quick gelation and an easy crosslinking process makes alginate one of the most studied polysaccharides in the field of regenerative medicine. The main purpose of this study was to obtain tissue-like materials suitable for use in bone regeneration. In this respect, alginate and several types of clay were investigated as components of 3D-printing, nanocomposite inks. Using the extrusion-based nozzle, the nanocomposites inks were printed to obtain 3D multilayered scaffolds. To observe the behavior induced by each type of clay on alginate-based inks, rheology studies were performed on composite inks. The structure of the nanocomposites samples was examined using Fourier Transform Infrared Spectrometry and X-ray Diffraction (XRD), while the morphology of the 3D-printed scaffolds was evaluated using Electron Microscopy (SEM, TEM) and Micro-Computed Tomography (Micro-CT). The swelling and dissolvability of each composite scaffold in phosfate buffer solution were followed as function of time. Biological studies indicated that the cells grew in the presence of the alginate sample containing unmodified clay, and were able to proliferate and generate calcium deposits in MG-63 cells in the absence of specific signaling molecules. This study provides novel information on potential manufacturing methods for obtaining nanocomposite hydrogels suitable for 3D printing processes, as well as valuable information on the clay type selection for enabling accurate 3D-printed constructs. Moreover, this study constitutes the first comprehensive report related to the screening of several natural clays for the additive manufacturing of 3D constructs designed for bone reconstruction therapy

Imagistic findings using artificial intelligence in vaccinated versus unvaccinated SARS-CoV-2-positive patients receiving in-care treatment at a tertiary lung hospital

Abstract: Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30-39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology "Marius Nasta" in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation

Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital

Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30–39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology “Marius Nasta” in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation

Imagistic findings using artificial intelligence in vaccinated versus unvaccinated SARS-CoV-2-positive patients receiving in-care treatment at a tertiary lung hospital

Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30-39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology "Marius Nasta" in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation