Stagebrogaard6694

Two hundred and twenty non-serious AEFI were reported within 48 hours of second dose. No AEFI was reported after 15 days for both the doses. We found no association of AEFI with sex and profession ( p >0.5). Significant association of AEFI was found with age ( p <0.01).

Short-term AEFI were predominantly observed in first 48 hours. Incidence decreased in subsequent weeks with no occurrence after 15 days in both doses. Symptoms were mild in severity and short-lived. No serious AEFI attributable to vaccines were reported.

Short-term AEFI were predominantly observed in first 48 hours. Incidence decreased in subsequent weeks with no occurrence after 15 days in both doses. Symptoms were mild in severity and short-lived. No serious AEFI attributable to vaccines were reported.

Efficacy of vaccines studied in clinical trial settings are likely to be different from their effectiveness in a real-world scenario. Indian Armed Forces launched its vaccine drive against COVID-19 on 16 Jan 2021. This study evaluated the effect of vaccination on mortality amongst hospitalized COVID patients.

A cross sectional study was done on all admitted moderate to severe COVID-19 patients at a designated COVID hospital in New Delhi. The primary outcome assessed the association of being fully vaccinated with mortality. Unadjusted odds ratios (OR) (with 95% CI) was performed for each predictor. Logistic regression was used for multivariable analysis and adjusted odds ratios obtained.

The 1168 patients included in the study had a male preponderance with a mean age of 54.6 (± 17.51) years. A total of 266 (23%) patients were partially vaccinated with COVISHIELD® and 184 (16%) were fully vaccinated. Overall, 518 (44.3%) patients had comorbidities and 332 (28.4%) died. Among those fully vaccinated, there was 12.5% (23/184) mortality while it was 31.45 % (309/984) among the unvaccinated (OR 0.3, 95% CI 0.2 to 0.5, p<0.0001). In a logistic regression model, complete vaccination status and younger age were found to be associated with survival.

Vaccination with two doses of COVISHIELD® was associated with lower odds of mortality among hospitalized patients with moderate to severe COVID.

Vaccination with two doses of COVISHIELD® was associated with lower odds of mortality among hospitalized patients with moderate to severe COVID.

The first dose of the ChAdOx1 nCoV- 19 Corona Virus Vaccine (Covishield) was administered to the eligible beneficiaries of tertiary care institute of Western Maharashtra on 16 Jan 21 and in the past three months almost 97% of the staff has been vaccinated. The present study analyses the incidence of COVID cases in the unvaccinated and vaccinated population of the institute.

All Covid 19 infections (RT-PCR positive) from 01 February 21 to 25 April 21 were included in the study and analyzed as per their vaccination status. To assess the COVID 19 transmission in contacts, Secondary Attack Rates (SAR) of the pre-vaccination period (Jun-Oct 20) was compared with the present SAR.

A total of 113 cases occurred in the study period (01 Feb to 25 Apr 21). Lower number of infections were observed among the fully vaccinated as compared to partially vaccinated and non-vaccinated. The overall vaccine effectiveness was found to be 88.6% (81.55-92.37) and 44.1% (4.55-67.3) in completely and partially vaccinated individuals respectively. Hazard Ratios for getting infected dropped significantly after 28 days of the second dose. The SAR in high risk contacts (HRCs) was found to be 4.25%, which was lower than SAR (20.6%) of pre-vaccination period.

This is one of the earliest studies in India to report the impact of COVID-19 vaccination. The results indicate that the vaccine provides effective protection against COVID-19 infection. However, given the complex dynamics of vaccination, the role of NPIs and implementation of COVID appropriate behavior cannot be undermined.

This is one of the earliest studies in India to report the impact of COVID-19 vaccination. The results indicate that the vaccine provides effective protection against COVID-19 infection. However, given the complex dynamics of vaccination, the role of NPIs and implementation of COVID appropriate behavior cannot be undermined.

On 16 Jan 2021, India launched its immunization program against COVID-19. Among the first recipients were 1.59 million Health Care Workers (HCWs) and Frontline Workers (FLWs) of the Indian Armed Forces, who were administered COVISHIELD (Astra Zeneca). We present an interim analysis of vaccine effectiveness (VE) estimates till 30 May 2021.

The VIN-WIN cohort study was carried out on anonymized data of HCWs and FLWs of Indian Armed Forces. The existing surveillance system, enhanced for COVID-19 monitoring, was sourced for data. The cohort transitioned from Unvaccinated (UV) to Partially Vaccinated (PV) to Fully Vaccinated (FV), serving as its own internal comparison. Outcomes studied in the three groups were breakthrough infections and COVID related deaths. Incidence Rate Ratio (IRR) was used to compare outcomes among the three groups to estimate VE.

Data of 1,595,630 individuals (mean age 27.6 years; 99% male) over 135 days was analysed. Till 30 May 21, 95.4% and 82.2% were partially and fully vaccinated. The UV, PV and FV compartments comprised 106.6, 46.7 and 58.7 million person-days respectively. The number of breakthrough cases in the UV, PV and FV groups were 10061, 1159 and 2512; while the deaths were 37, 16 and 7 respectively. Corrected VE was 91.8-94.9% against infections.

Interim results of the VIN-WIN cohort study of 1.59 million HCWs and FLWs of Indian Armed Forces showed a ∼93% reduction in COVID-19 breakthrough infections with COVISHIELD vaccination.

Interim results of the VIN-WIN cohort study of 1.59 million HCWs and FLWs of Indian Armed Forces showed a ∼93% reduction in COVID-19 breakthrough infections with COVISHIELD vaccination.Reinfections in COVID-19 are being reported all around the world and are a cause for concern, considering that a lot of our assumptions and modeling (including vaccination) related to the disease have relied on long-term immunity. We were one of the first groups to report a series of 4 healthcare workers to have been reinfected. This review article reports a scoping review of the available literature on reinfections, with a discussion of the implications of reinfections.Color appearance models use standard color matching functions to derive colorimetric information from spectral radiometric measurements of a visual environment, and they process that information to predict color perceptual attributes such as hue, chroma and lightness. That processing is usually done by equations with fixed numerical coefficients that were predetermined to yield optimal agreement for a given standard observer. Here we address the well-known fact that, among color-normal observers, there are significant differences of color matching functions. These cause disagreements between individuals as to whether certain colors match, an important effect that is often called observer metamerism. Yet how these individual sensitivity differences translate into differences in perceptual metrics is not fully addressed by many appearance models. It might seem that appearance could be predicted by substituting an individual's color matching functions into an otherwise-unchanged color appearance model, but this or most observers.California is widely seen as a climate and environmental policy leader in the U.S. and beyond. However, allowing local land use decisions to proceed as usual represents a major gap in the state's climate policy framework. Climate mitigation rules and formulae are utilized to claim zero net emissions for large-scale land development at the urban fringe. Such developments continue to destroy habitats and radically transform landscapes. Newhall Ranch, a subdevelopment at the edge of urbanized Los Angeles County, has claimed emissions offsets such that the development of 60,000 homes will have less than zero greenhouse gas emissions. Offsets largely rely on using disadvantaged communities, and significant threats to endangered species on site are compensated by payments to the project's environmental opponents. The net result is land development as usual, with a veneer of solarization and investments in GHG mitigation projects with poor quantification and verification. This situation demonstrates the enduring structures of land use development that drive GHG emissions and environmental change, and calls for stronger requirements for local compliance with state emissions-reductions targets.Continuum manipulators, inspired by nature, have drawn significant interest within the robotics community. They can facilitate motion within complex environments where traditional rigid robots may be ineffective, while maintaining a reasonable degree of precision. Soft continuum manipulators have emerged as a growing subfield of continuum robotics, with promise for applications requiring high compliance, including certain medical procedures. This has driven demand for new control schemes designed to precisely control these highly flexible manipulators, whose kinematics may be sensitive to external loads, such as gravity. This article presents one such approach, utilizing a rapidly computed kinematic model based on Cosserat rod theory, coupled with sensor feedback to facilitate closed-loop control, for a soft continuum manipulator under tip follower actuation and external loading. This approach is suited to soft manipulators undergoing quasi-static deployment, where actuators apply a follower wrench (i.e., one that is in a constant body frame direction regardless of robot configuration) anywhere along the continuum structure, as can be done in water-jet propulsion. In this article we apply the framework specifically to a tip actuated soft continuum manipulator. The proposed control scheme employs both actuator feedback and pose feedback. The actuator feedback is utilized to both regulate the follower load and to compensate for non-linearities of the actuation system that can introduce kinematic model error. Pose feedback is required to maintain accurate path following. Experimental results demonstrate successful path following with the closed-loop control scheme, with significant performance improvements gained through the use of sensor feedback when compared with the open-loop case.

In recent years, endovascular treatment has become the dominant approach to treat intracranial aneurysms (IAs). Despite tremendous improvement in surgical devices and techniques, 10-30% of these surgeries require retreatment. Previously, we developed a method which combines quantitative angiography with data-driven modeling to predict aneurysm occlusion within a fraction of a second. This is the first report on a semi-autonomous system, which can predict the surgical outcome of an IA immediately following device placement, allowing for therapy adjustment. Additionally, we previously reported various algorithms which can segment IAs, extract hemodynamic parameters via angiographic parametric imaging, and perform occlusion predictions.

We integrated these features into an Aneurysm Occlusion Assistant (AnOA) utilizing the Kivy library's graphical instructions and unique language properties for interface development, while the machine learning algorithms were entirely developed within Keras, Tensorflow and skLearn.