Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India.

Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of >50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi.

Severe acute respiratory illness surveillance for coronavirus disease 2019, India, 2020.

Background & objectives: Sentinel surveillance among severe acute respiratory illness (SARI) patients can help identify the spread and extent of transmission of coronavirus disease 2019 (COVID-19). SARI surveillance was initiated in the early phase of the COVID-19 outbreak in India. We describe here the positivity for COVID-19 among SARI patients and their characteristics. Methods: SARI patients admitted at 41 sentinel sites from February 15, 2020 onwards were tested for COVID-19 by real-time reverse transcription-polymerase chain reaction, targeting E and RdRp genes of SARS-CoV-2. Data were extracted from Virus Research and Diagnostic Laboratory Network for analysis. Results: A total of 104 (1.8%) of the 5,911 SARI patients tested were positive for COVID-19. These cases were reported from 52 districts in 20 States/Union Territories. The COVID-19 positivity was higher among males and patients aged above 50 years. In all, 40 (39.2%) COVID-19 cases did not report any history of contact with a known case or international travel. Interpretation & conclusions: COVID-19 containment activities need to be targeted in districts reporting COVID-19 cases among SARI patients. Intensifying sentinel surveillance for COVID-19 among SARI patients may be an efficient tool to effectively use resources towards containment and mitigation efforts.

Finite element analysis of customized implant in mandibular reconstruction after tumor resection with and without using customized surgical osteotomy guide.

OBJECTIVES: The aim of this work was to compare different 12 cases (3 patients * 4 cases = 12 cases) with varying gaps between implant and bone by analyzing the effect of these gaps on implant and screws using FEM. METHODS: In each patient's case 1 using CSOG and in case 2, 3, and 4 without using CSOG tumor cutting was done. Hence in each patient zero gaps at case 1 and overcutting at case 2, 3, and 4 have obtained at different locations. RESULTS: FEM results reveal that in each patient's case 4 (maximum gap) was more susceptible to loosening of the screws due to higher strains (37%) and implant failure due to higher stress (28%) concentration under the same loading conditions when compared with case 1 (zero gap). CONCLUSIONS: The study reveals that mandibular reconstruction with implant placement using CSOG can significantly enhance the stability and safety of the implant.

Comparison of model-based and conventional controllers on a pilot-scale heat exchanger.

This pilot-scale heat exchanger demonstration compares two relatively simple nonlinear model-based control strategies to conventional proportional-integral (PI) control. The two nonlinear controllers, generic model control (GMC) and process-model based control (PMBC), use a first-principles model thereby providing characterization of the nonlinear process throughout the operating range. There are two approaches to GMC, one uses a dynamic model, the other a steady-state model. This work uses the steady-state model; accordingly, will use the term GMC-SS, which can be classified as output characterization for a PI controller, making it relatively simple to implement. PMBC uses a dynamic model and adapts to represent the process. These two nonlinear controllers were selected for this application evaluation because of their simplicity (they can be implemented in-house within many commercial control systems), diversity (steady-state and dynamic models), and demonstrated utility for control of nonlinear single-input-single-output processes. The application and results are presented and discussed. Summarizing the results: Within a small temperature operating range PI provides good control, but over the full operating range, the nonlinear and variable delay of the process lead to poor control with PI. GMC can handle the nonlinear issues, but using the convenient steady-state model; it also, provides poor control because of the variable delay associated with flow rate. PMBC was able to provide good control throughout the entire operating range. PMBC has a further advantage of only having one tuning coefficient, while PI and GMC-SS have two.