Comparative Analysis of Business Object Approaches

This paper presents a comparison of several technologies for developing distributed applications. The specific technologies into consideration are: one focused on COM/DCOM/COM and Microsoft technologies, Internet Explorer and ActiveX - and the other focused on Netscape, CORBA, JAVA/J2EE solutions.integrated technologies, interoperability, distributed systems, components, distributed architecture

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

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

The Renin-Angiotensin System: The Challenge behind Autoimmune Dermatological Diseases

Autoimmune dermatological diseases (AIDD) encompass a diverse group of disorders characterized by aberrant immune responses targeting the skin and its associated structures. In recent years, emerging evidence suggests a potential involvement of the renin–angiotensin system (RAS) in the pathogenesis and progression of these conditions. RAS is a multicomponent cascade, primarily known for its role in regulating blood pressure and fluid balance. All of the RAS components play an important role in controlling inflammation and other immune responses. Angiotensin II, the main effector, acts on two essential receptors: Angiotensin Receptor 1 and 2 (AT1R and AT2R). A disturbance in the axis can lead to many pathological processes, including autoimmune (AI) diseases. AT1R activation triggers diverse signaling cascades involved in inflammation, fibrosis and tissue remodeling. Experimental studies have demonstrated the presence of AT1R in various cutaneous cells and immune cells, further emphasizing its potential contribution to the AI processes in the skin. Furthermore, recent investigations have highlighted the role of other RAS components, beyond angiotensin-converting enzyme (ACE) and Ang II, that may contribute to the pathophysiology of AIDD. Alternative pathways involving ACE2, Ang receptors and Ang-(1-7) have been implicated in regulating immune responses and tissue homeostasis within the skin microenvironment. Understanding the intricate involvement of the RAS in AIDD may provide novel therapeutic opportunities. Targeting specific components of the RAS, such as angiotensin receptor blockers (ARBs), ACE inhibitors (ACEIs) or alternative RAS pathway modulators, could potentially ameliorate inflammatory responses, reduce tissue damage and lessen disease manifestations. Further research is warranted to outline the exact mechanisms underlying RAS-mediated immune dysregulation in AIDD. This abstract aims to provide a concise overview of the intricate interplay between the RAS and AIDD. Therefore, we elaborate a systematic review of the potential challenge of RAS in the AIDD, including psoriasis, systemic sclerosis, vitiligo, lupus erythematosus and many more