A case report of extra-articular manifestation of rheumatoid arthritis: Rheumatoid nodules in lungs.

Rheumatoid arthritis is a systemic inflammatory disorder primarily affecting joints but not limited to the joints alone. Extra-articular manifestations involve skin, ocular, gastrointestinal, pulmonary, cardiac, renal, neurological, and hematological systems. Among them, skin manifestations (20%) are most common, presenting as nodules on the extensor surfaces of the upper and lower extremities. In rare cases these nodules can also be detected within the heart and lungs. Interestingly, rheumatoid nodules are often seen in patients on leflunomide, methotrexate, or tumor necrosis factor-alpha antagonists. Nevertheless, definitive diagnosis requires a histopathological analysis. In this case report, we presented a 49-year-old male patient with a relatively short period of disease activity leading to rheumatoid nodules in the lungs. Considering the ongoing COVID-19 pandemic and that tuberculosis was still endemic in Kazakhstan, achieving the definite diagnosis was challenging. Initial imaging study revealed bilateral polysegmental pneumonia. The tests for COVID-19 and pulmonary tuberculosis were negative. A follow-up chest computed tomography scan had signs of disseminated lung lesions of unknown origin. Lung biopsy showed a morphological picture of productive granulomas characteristic for tuberculosis. However, at the second look, typical scarring granulomas typically seen in rheumatoid nodules were observed.

Machine-Learning-Inspired Workflow for Camera Calibration.

The performance of modern digital cameras approaches physical limits and enables high-precision measurements in optical metrology and in computer vision. All camera-assisted geometrical measurements are fundamentally limited by the quality of camera calibration. Unfortunately, this procedure is often effectively considered a nuisance: calibration data are collected in a non-systematic way and lack quality specifications; imaging models are selected in an ad hoc fashion without proper justification; and calibration results are evaluated, interpreted, and reported inconsistently. We outline an (arguably more) systematic and metrologically sound approach to calibrating cameras and characterizing the calibration outcomes that is inspired by typical machine learning workflows and practical requirements of camera-based measurements. Combining standard calibration tools and the technique of active targets with phase-shifted cosine patterns, we demonstrate that the imaging geometry of a typical industrial camera can be characterized with sub-mm uncertainty up to distances of a few meters even with simple parametric models, while the quality of data and resulting parameters can be known and controlled at all stages.

Mass effects in muon and semileptonic b-->c decays.

Quantum chromodynamics (QCD) effects in the semileptonic decay b-->clnu are evaluated to the second order in the coupling constant, O(alpha(s){2}), and to several orders in the expansion in quark masses, m{c}/m{b}. Corrections are calculated for the total decay rate as well as for the first two moments of the lepton energy and the hadron system energy distributions. Translated into QED and applied to the muon decay, they decrease its predicted rate by -0.43 ppm.