Understanding lifetime and dispersion of cough-emitted droplets in air.

To understand the exact transmission routes of SARS-CoV-2 and to explore effects of time, space and indoor environment on the dynamics of droplets and aerosols, rigorous testing and observation must be conducted. In the current work, the spatial and temporal dispersions of aerosol droplets from a simulated cough were comprehensively examined over a long duration (70 min). An artificial cough generator was constructed to generate reliably repeatable respiratory ejecta. The measurements were performed at different locations in front (along the axial direction and off-axis) and behind the source in a sealed experimental enclosure. Aerosols of 0.3-10 µm (around 20% of the maximum nuclei count) were shown to persist for a very long time in a still environment, and this has a substantial implication for airborne disease transmission. The experiments demonstrated that a ventilation system could reduce the total aerosol volume and the droplet lifetime significantly. To explain the experimental observations in more detail and to understand the droplet in-air behaviour at various ambient temperatures and relative humidity, numerical simulations were performed using the Eulerian-Lagrangian approach. The simulations show that many of the small droplets remain suspended in the air over time instead of falling to the ground.

Application of machine learning for the low-cost prediction of soot concentration in a turbulent flame.

The second most potent forcer of climate change, soot, has severe harmful effects on both human health and the environment. Accurate numerical modeling of soot formation is extremely complex and has a high computational cost due to its dependence on many physical and chemical interactions, specifically in turbulent flames. The high computational cost of coupling chemistry, fluid dynamics, thermodynamics, and heat transfer raise the need for a novel, precise, and computationally cost-effective numerical technique for predicting soot concentrations. This study applies machine learning (ML) to predict soot formation in a turbulent flame. It has been discovered that the local soot volume fraction is correlated to the histories of gas properties strongly correlative to soot formation and oxidation. A library with the Lagrangian temporal histories of soot-containing fluid parcels is created from turbulent diffusion flame data computed using direct numerical simulation (DNS). This library is then used to train an ML algorithm to predict soot volume fraction along randomly selected trajectories (pathlines) in the domain. The prediction capability is tested over 10% of the entire dataset, and it is seen that soot volume fraction can be predicted well along the selected pathlines with low error and computational cost. To describe quantitative results, the calculated R2 in the current work is equal to 0.92, which shows good accuracy of the predictions.

A Case of Acrorenal Syndrome.

Urinary tract anomalies are common and comprise about 20% to 30% of total congenital anomalies. This spectrum consists of many different anomalies of the urinary tract that may be syndromic or nonsyndromic with different etiologies. In this case report, a patient with single kidney and urinary tract signs is introduced that was diagnosed accidentally. The finding of different anomalies in different organ systems should lead us to examination of the intactness of the urinary tract. In these disorders, if there is no need for immediate intervention, long-term follow-up can be helpful to postpone chronic kidney disease progression.

Vitamin D deficiency is associated with tibial bone pain and tenderness. A possible contributive role.

BACKGROUND: Vitamin D deficiency is associated with osteomalacia and a variety of musculoskeletal pain. This study aimed to determine the association of vitamin D deficiency with tibial bone pain and tenderness. METHODS: Patients with leg pain, defined as local pain and tenderness over tibial bones for ≥ 6 weeks were consecutively selected. Secondary causes of pain were excluded by appropriate clinical, radiological and laboratory examinations. Serum 25-hydroxyvitamin D (25-OHD) was assessed by enzyme-linked immunosorbent assay method and levels < 20 ng/mL were considered as deficiency. Age- and sex-matched subjects without leg pain served as controls. Multiple logistic regression analysis was used to determine associations. RESULTS: One hundred and eighteen patients and 114 controls aged 46.8 ± 14.8 and 44.6 ± 14.1 years, respectively (P = 0.93) were analyzed. Mean 25-OHD level was significantly lower (P = 0.001) and the prevalence of 25-OHD deficiency was significantly higher in the patients as compared with the controls (75.4% vs. 23.6%), odds ratio (OR) = 9.54 (95% CI, 5.22-17.45, P = 0.001). There was a negative dose-response relationship between serum 25-OHD and tibial bone pain by OR = 17.33 (95% CI, 6.48-46.3) in subjects with 25-OHD < 10 ng/mL, and OR = 14.7 (95% CI, 6.35-34.6) in serum 25-OHD levels at 10-19.9 ng/mL, and OR = 2.58 (95% CI, 1.08-6.1) in those with 25-OHD at 20-29.9 ng/mL as compared with 25-OHD ≥ 30 ng/mL. After controlling for demographic and biochemical factors, the association reached a stronger level of 19.8 (6.9-56.3) in subjects with serum 25-OHD < 10 ng/mL and 14.4 (5.8-34.6) in those with serum 25-OHD at levels of 10-19.9 ng/mL and 1.85 (0.73-4.6) in 20-29 ng/mL. CONCLUSION: These findings indicate a possible contributive role for serum 25-OHD deficiency in the development of pain and tenderness over the tibial bone.